Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
type: channel
description: Subjects Area : Ilmu Komputer, Sistem Informasi, Rekayasa Perangkat Lunak, Interaksi Manusia dan Komputer, Sistem Berbasis Pengetahuan, E-Commerce
publisher: Program Studi Teknik Informatika, FTIK, Universitas Indraprasta PGRI
language: en
publication name: Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
issn: 2715-8756
items: Analisis Perbandingan VPN Tunneling Pada Multi-Cloud Untuk Optimalisasi Performa dan Skalabilitas
items: Sistem Pendukung Keputusan Pemilihan Murid Berprestasi Terbaik Pada SMP PGRI Surya Kencana Menggunakan Metode SAW
items: Implementasi Steganografi dengan Metode Least Significant Bit (LSB) Untuk Penyisipan Dalam Data Gaji pada PT Nusa Network Pratama
items: Sistem Pendukung Keputusan untuk Pemilihan Mobil Bekas Terbaik dengan Metode AHP pada Showroom Bin Mahmoed Motor
items: Penerapan Metode Indobert untuk Deteksi Berita Hoaks pada Media Digital Berbahasa Indonesia
items: Prediksi Risiko Stunting Prakehamilan Menggunakan Sistem Pakar Certainty Factor Berbasis Mobile
items: Pengembangan Hybrid Recommender System Menggunakan Scikit-Learn dan Pandas untuk Rekomendasi Film
items: Penerapan Algoritma KMP dalam Pencarian Data Sertifikasi ISO PT Era Kualitas Informasi
items: Sistem Pendukung Keputusan Menentukan Pilihan Bahan Kaos Sablon Terbaik pada PT Urusdo Kreasi Indonesia Berbasis Simple Additive Weighting
items: Implementasi Sistem Perpustakaan Digital dengan Fitur Peminjaman Buku Berbasis Barcode untuk Meningkatkan Efisiensi dan Akurasi di MTS NU 01 Pecalungan
items: Implementasi dan Pengujian Performa Server High Availability Menggunakan Metode Horizontal Scaling dengan Studi Kasus: Marketplace XYZ
items: Analisis Strategi Penerimaan Peserta Didik Baru Menggunakan K-Means Clustering dengan Optimasi Elbow
items: Sistem Pendukung Keputusan dalam Menentukan Kepuasan Masyarakat Terhadap Pelayanan di Kelurahan Kebon Pala dengan Metode TOPSIS
items: Penentuan Jumlah Produksi pada CV Rairaka Konveksi Menggunakan Metode Fuzzy Tsukamoto
items: Sistem Informasi Monitoring dan Evaluasi Kegiatan Mengajar Guru Berbasis Web pada SD Negeri 23 Ugyehek
items: Penerapan Rule-Based Classifier untuk Menentukan SLA Rate Pada PT Nettocyber Indonesia
items: Implementasi Metode Forward Chaining untuk Deteksi Dini Serangan Jamur pada Tanaman Padi Berdasarkan Gejala Visual
items: Implementasi Algoritma Apriori Untuk Prediksi Pola Penjualan Produk Fashion pada Toko Innari G-Style
items: Software Quality Tourism Industry: Analisis Aplikasi Mobile Nusatrip dengan Metode System Usability Scale (SUS)
items: Aplikasi Klasifikasi Penyakit Kentang Menggunakan Algoritma Convolution Neural Network (CNN)
items: Perancangan Aplikasi Deteksi Plagiarisme dengan TF-IDF dan Cosine Similarity
items: Sistem Pakar Untuk Identifikasi Kerusakan Sepeda Motor Menggunakan Metode Forward Chaining pada Bengkel AKC Workshop
items: Sistem Pakar Pendeteksi Kerusakan Sepeda Motor Matik Injeksi Menggunakan Metode Forward Chaining
items: Analisis Prediktif Dropout Mahasiswa Berdasarkan Kinerja Akademik Semester Awal Menggunakan Machine Learning
items: Sistem Monitoring Suhu Dan Humidity pada Data Center PT Elga Yasa Media Menggunakan IoT
items: Network Automation dengan Metode NDLC Menggunakan Bahasa Pemrograman Python
items: Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik dengan Metode Simple Additive Weighting (SAW) pada PT Satria Antaran Prima (SAP)
items: Perancangan Pembelajaran Online dengan Fitur Simulasi Tes Kerja Menggunakan Metode Simple Additive Weighting (SAW) pada SMK Ganesa Satria 2 Depok
items: Analisis Sentimen Kenaikan Pbb Berbasis Tiktok Menggunakan Support Vector Machine
items: Sistem Pendukung Keputusan Penerimaan Karyawan Baru pada PT Kalingga Prima Bangun Setia dengan Metode SAW

Analisis Perbandingan VPN Tunneling Pada Multi-Cloud Untuk Optimalisasi Performa dan Skalabilitas
type: item
description: Multi-cloud infrastructure is increasingly being used in network service provisioning due to its ability to improve availability and reduce reliance on a single provider. However, the performance of VPN tunneling services in multi-cloud environments can vary significantly across providers due to differences in infrastructure characteristics, data centre locations, and network capacity. This study aims to compare the performance of SSH Tunneling and Xray VMess Non-TLS across five cloud providers, including DigitalOcean, UCloud Global, Biznet GioCloud, PT Media Antar Nusa, and CV Atha Media Prima. The method used was a comparative experiment with quantitative descriptive analysis, measuring four key metrics: latency, jitter, download throughput, and upload throughput, with each scenario repeated three times. The results show that Xray VMess Non-TLS outperforms in latency and upload throughput, with Biznet GioCloud recording the lowest latency at 31.30 ms and the most stable jitter at 7.00 ms, while PT Media Antar Nusa recorded the highest upload throughput at 62.60 Mbps. Conversely, SSH Tunneling demonstrated superiority in several download throughput scenarios, with PT Media Antar Nusa recording the highest value of 45.20 Mbps. These findings indicate that the selection of protocols and cloud providers should be tailored to the specific needs of the workload, and a multi-cloud approach offers significant flexibility in optimising VPN tunneling performance.
subject: Articles
  topic: section
subject: network performance
  topic: keywords
subject: Xray VMess
  topic: keywords
subject: SSH tunneling
  topic: keywords
subject: VPN Tunneling
  topic: keywords
subject: multi-cloud
  topic: keywords
subject: Information Technology
  topic: disciplines
creator: Muhammad Jundy Rabbani
creator: Reza Maulana
rights: Copyright (c) 2026 Muhammad Jundy Rabbani, Reza Maulana (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 391
ending page: 398
doi: 10.30998/ccs7h187

Sistem Pendukung Keputusan Pemilihan Murid Berprestasi Terbaik Pada SMP PGRI Surya Kencana Menggunakan Metode SAW
type: item
description: This research aims to create a decision support system that can be used in selecting the best achieving students at PGRI Surya Kencana Middle School, with the hope of helping schools determine superior students objectively and accurately. The system designed uses the simple additive weighting method to process assessment data based on predetermined academic criteria. The assessment process is carried out using a computer with a web display so that it is more structured, clear and efficient. The results of this research are in the form of a sequence of outstanding students which is presented in the form of a report based on the criteria of average academic grades, attendance, attitude, discipline and activeness. So that it can be a reference for schools in making more precise and fair decisions, as well as reducing the element of subjectivity in assessing student achievement in the educational environment.
subject: Articles
  topic: section
subject: SAW Method
  topic: keywords
subject: Achievement
  topic: keywords
subject: Students
  topic: keywords
subject: Decision Support System
  topic: keywords
subject: Teknik Informatika
  topic: disciplines
creator: Raihan M Rabbani
creator: Mei Lestari
creator: Ek Ajeng Rahmi Pinahayu
rights: Copyright (c) 2026 Raihan M. Rabbani, Mei Lestari, Ek Ajeng Rahmi Pinahayu (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 417
ending page: 426
doi: 10.30998/k3veph95

Implementasi Steganografi dengan Metode Least Significant Bit (LSB) Untuk Penyisipan Dalam Data Gaji pada PT Nusa Network Pratama
type: item
description: This research was conducted with the aim of enhancing information security for employee salary data at PT Nusa Network Pratama through the application of steganography methods. Given the importance of salary confidentiality as part of the company’s sensitive information, a system is needed that can hide this data without being detected visually or digitally by unauthorised parties. The method used in this study is Least Significant Bit (LSB)-based steganography, a data-embedding technique that replaces the least significant bit of each pixel in a digital image. This approach was chosen for its ability to embed data without significantly affecting the visual quality of the image. The implementation process involved testing data embedding and extraction to ensure that salary data could be hidden and retrieved with high accuracy. The results of the study indicate that the LSB method can be effectively used to embed salary data into images without compromising the visual appearance of the image. The embedded data can be extracted with a 100% success rate, without any damage to the original data or the image file. Thus, the implementation of LSB steganography has proven to be feasible and secure as an alternative for distributing salary data internally within a corporate environment.
subject: Articles
  topic: section
subject: PT Nusa Network Pratama
  topic: keywords
subject: Salary Data, Digital Image
  topic: keywords
subject: Data Security
  topic: keywords
subject: Steganography, Least Significant Bit
  topic: keywords
subject: Steganography
  topic: keywords
subject: Artikel teknik: Engineering
  topic: disciplines
creator: Freddi Moriston Alfa Doli
creator: Lukman Lukman
creator: Meri Chrismes Aruan
rights: Copyright (c) 2026 Freddi Moriston Alfa Doli, Lukman, Meri Chrismes Aruan (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 382
ending page: 390
doi: 10.30998/p30cba56

Sistem Pendukung Keputusan untuk Pemilihan Mobil Bekas Terbaik dengan Metode AHP pada Showroom Bin Mahmoed Motor
type: item
description: This research aims to analyze the used car market using the Analytical Hierarchy Process method to select the best used cars at the Bin Mahmoed Motor Showroom. This study employs a literature review, interviews, and observations to collect data. The research findings indicate that the implementation of AHP in the decision support system can augment the comprehension of this methodology within the automotive sector and elevate customer satisfaction by delivering precise and customized recommendations. The system developed using HTML, CSS, JavaScript, PHP, and MySQL ensures that criteria such as price, year, fuel consumption, and capacity can be effectively integrated, thereby facilitating the process of selecting used cars more quickly and accurately.
subject: Articles
  topic: section
subject: Mobil Bekas
  topic: keywords
subject: Analytical Hierarchy Process
  topic: keywords
subject: Kepuasan Pelanggan
  topic: keywords
subject: Sistem Pendukung Keputusan
  topic: keywords
creator: Sultan Badai Ady Dewa
creator: Dewi Anjani
creator: Lies Sunarmintyastuti
rights: Copyright (c) 2026 Sultan Badai Ady Dewa, Dewi Anjani, Lies Sunarmintyastuti (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 307
ending page: 315
doi: 10.30998/evzs2329

Penerapan Metode Indobert untuk Deteksi Berita Hoaks pada Media Digital Berbahasa Indonesia
type: item
description: This study focuses on the implementation of the IndoBERT method for detecting hoax news in Indonesian digital media and examining the model’s performance and generalization ability. The dataset consists of primary data obtained from a Kaggle dataset and secondary data collected through web scraping from various sources, which are then combined and preprocessed. The model is trained using a fine-tuning approach with variations in parameters such as learning rate, batch size, and epoch to achieve optimal results. The experimental results indicate that the best configuration is achieved at epoch 4, learning rate 5e-5, and batch size 16, producing an accuracy of 0.9868 along with the lowest validation loss. Evaluation using a confusion matrix shows a relatively low error rate for both classes. Testing on new data reveals that the model correctly classifies 26 out of 30 samples, indicating good generalization capability, although some misclassifications still occur in factual news that share similar characteristics with hoaxes.
subject: Articles
  topic: section
subject: natural language processing
  topic: keywords
subject: fine-tuning
  topic: keywords
subject: klasifikasi teks
  topic: keywords
subject: deteksi hoaks
  topic: keywords
subject: IndoBERT
  topic: keywords
subject: Artificial Intelligence
  topic: disciplines
creator: I Gede Bagus Surya Wibawa
creator: I Nyoman Eddy Indrayana
creator: Made Pasek Agus Ariawan
rights: Copyright (c) 2026 I Gede Bagus Surya Wibawa, I Nyoman Eddy Indrayana, Made Pasek Agus Ariawan (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 326
ending page: 333
doi: 10.30998/94zt3k10

Prediksi Risiko Stunting Prakehamilan Menggunakan Sistem Pakar Certainty Factor Berbasis Mobile
type: item
description: Stunting still a serious public health issue, and the risk often originates as early as the pre-prenant phase. However, digital solutions that specifically integrate individual risk screening, expert-based reasoning, and mobile access for expectant mothers are still limited, which hinders the ability to effectively address the stunting risk during the critical pre-prenant phase. This study aims to develop a Certainty Factor-based expert system mobile application capable of independently, quickly, and educationally predicting the risk of stunting during the pre-prenant phase. This study employs a design and development research approach encompassing needs identification, knowledge acquisition, the formulation of a knowledge base and inference rules, system design, and mobile application implementation. The knowledge base was designed for three user categories: women in the pre-prenant stage, women who have given birth, and 19-year-old adolescents. Evaluation results showed that system performance varied across groups, with an accuracy of 0.67 for the adolescent and postpartum groups and 0.52 for the pre-prenant group. The precision and recall values also show a similar pattern, indicating that the system performs better in groups with more structured risk characteristics than in groups with more complex risk determinants. These findings suggest that the integration of a CF-based expert system with a mobile platform is not only capable of supporting the early detection of stunting risk but also provides an adaptive approach to differences in user characteristics, so that it has potential to increase the effectiveness of life-cycle-based screening.
subject: Articles
  topic: section
subject: Pre-pregnancy stunting
  topic: keywords
subject: Expert system
  topic: keywords
subject: Early detection
  topic: keywords
subject: Certainty factor
  topic: keywords
subject: Mobile application
  topic: keywords
subject: statistik terapan
  topic: disciplines
subject: Ilmu Kesehatan
  topic: disciplines
subject: Teknik Informatika
  topic: disciplines
creator: Muhamad Hadi Arfian
creator: Noviandi Noviandi
creator: Fahmi Zain
rights: Copyright (c) 2026 Muhamad Hadi Arfian, Noviandi, Fahmi Zain (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 372
ending page: 381
doi: 10.30998/fkkvhz11

Pengembangan Hybrid Recommender System Menggunakan Scikit-Learn dan Pandas untuk Rekomendasi Film
type: item
description: The rapid growth of digital streaming services has led to an increase in the amount of available film content, creating a problem of information overload for users when selecting content that matches their preferences. Therefore, recommendation systems have become an essential solution to help users efficiently and personally discover relevant films. This study aims to develop a film recommendation system based on a hybrid recommender system by combining collaborative filtering and content-based filtering methods to improve the accuracy and diversity of recommendations. The CF method is used to leverage interaction patterns and similarities in preferences among users, while the CBF method utilizes film content features such as genre to determine item similarity. The system was implemented using the Python programming language with the scikit-learn and pandas libraries for data processing and model development. The dataset used is MovieLens 100k, consisting of 100,000 ratings from 943 users for 1,682 movies, along with movie metadata. System performance was evaluated using the mean squared error and precision@K metrics. The test results indicate that the hybrid system achieved a precision@5 value of 0.6000, indicating that 60% of the recommendations provided were relevant to user preferences. Furthermore, the hybrid approach proved to be more stable and accurate than single methods and was able to address cold-start problems and data sparsity. Thus, the developed system is capable of providing more relevant, diverse, and personalized movie recommendations. This study demonstrates that the hybrid approach is an effective solution for improving the quality of recommendation systems, particularly in user-data-based movie recommendation applications.
subject: Articles
  topic: section
subject: MovieLens.
  topic: keywords
subject: Scikit-learn
  topic: keywords
subject: Content-Based Filtering
  topic: keywords
subject: Hybrid Filtering
  topic: keywords
subject: Recommender System
  topic: keywords
subject: Informatics Engineering
  topic: disciplines
creator: Muhammad Fabian Hartono
creator: Opitasari Opitasari
creator: Ivan Firdaus
rights: Copyright (c) 2026 Muhammad Fabian Hartono, Opitasari Opitasari, Ivan Firdaus (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 408
ending page: 416
doi: 10.30998/8n8ms865

Penerapan Algoritma KMP dalam Pencarian Data Sertifikasi ISO PT Era Kualitas Informasi
type: item
description: This research aims to address the issues occurring at PT Era Kualitas Informasi in ISO certification database management so that it can be organized neatly, systematically, quickly, and accurately in searches. In the development of this system, the researcher used the Knuth-Morris-Pratt algorithm implemented with the NetBeans IDE 8.2 software and MySQL database. The Knuth-Morris-Pratt algorithm is one of the algorithms used in string searching. This research implements the Knuth-Morris-Pratt algorithm in the string search process for ISO certification data retrieval. The research methodology used in the ISO certification data processing system includes data collection techniques such as interviews with relevant parties and documentation to obtain the necessary information. Additionally, the researchers also conducted literature research relevant to the issues of the ISO certification data search system. After conducting research, analyzing the problems, and resolving the proposed issues, the researchers concluded that the existing system is still operated using simple applications like Microsoft Office. Therefore, by building a client database system at PT Era Kualitas Informasi, it will facilitate the data entry department in carrying out its tasks.
subject: Articles
  topic: section
subject: NetBeans
  topic: keywords
subject: Pencarian Data
  topic: keywords
subject: Algoritma Knuth-Morris-Pratt
  topic: keywords
creator: Rossa Arganita Pradana
creator: Achmad Sarwandianto
creator: Ambar Tri Hapsari
rights: Copyright (c) 2026 Rossa Arganita Pradana, Achmad Sarwandianto, Ambar Tri Hapsari (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 298
ending page: 306
doi: 10.30998/f1hfk035

Sistem Pendukung Keputusan Menentukan Pilihan Bahan Kaos Sablon Terbaik pada PT Urusdo Kreasi Indonesia Berbasis Simple Additive Weighting
type: item
description: Selecting the best fabric for screen-printed T-shirts is a multi-criteria decision-making process that considers factors such as fabric surface quality, comfort, durability, and price to support production and sales at PT Urusdo Kreasi Indonesia. Currently, this process is still carried out manually and subjectively, leading to time inefficiencies and the risk of incorrect fabric selection. This study applies a decision support system using the simple additive weighting method to provide objective recommendations. The data was processed through stages of decision matrix normalisation and criterion weighting (C1: 0.35, C2: 0.3, C3: 0.2, C4: 0.15). The results of the study indicate that polyester (A4) is the best choice, with the highest preference value of 0.81. The implementation of this system has proven effective in helping management make material procurement decisions in a more transparent and efficient manner.
subject: Articles
  topic: section
subject: teknik informatika
  topic: disciplines
creator: Muhammad As'ad Difinubun
creator: Yulianingsih Yulianingsih
creator: Dian Novita
rights: Copyright (c) 2026 Muhammad As'ad Difinubun, Yulianingsih, Dian Novita (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 364
ending page: 371
doi: 10.30998/0q7wym55

Implementasi Sistem Perpustakaan Digital dengan Fitur Peminjaman Buku Berbasis Barcode untuk Meningkatkan Efisiensi dan Akurasi di MTS NU 01 Pecalungan
type: item
description: This study aims to develop and implement a barcode-based digital library system at MTS NU 01 Pecalungan, to improve service time efficiency and accuracy in data recording. The method used is a mixed-method sequential explanatory design, with two stages: quantitative and qualitative. In the quantitative phase, system testing was conducted to obtain data that would later be used to compare processing time and data accuracy levels between when using manual and barcode-based systems. The results showed an increase in time efficiency from an average of 122.4 seconds to 33 seconds for borrowing and data accuracy from 82% to 97%. Functional testing of this system used Blackbox testing to test all features in the system, ensuring all features run well. Meanwhile, the results of the analysis of the questionnaire with 82 respondents showed that the majority of users were satisfied with this system, with a level of accuracy of satisfaction classification using the Naive Bayes algorithm of 82.35%. It can be concluded that the implementation of the barcode system effectively increases the efficiency of school library services.
subject: Articles
  topic: section
subject: SDLC
  topic: keywords
subject: Perpustakaan Digital
  topic: keywords
subject: Mixed-methods Sequential Explanatory
  topic: keywords
subject: Educational Technology
  topic: disciplines
subject: Digital Library
  topic: disciplines
subject: Software Engineering
  topic: disciplines
creator: Nadya Angelica Wimara
creator: Iwan Setiawan Wibisono
rights: Copyright (c) 2026 Nadya Angelica Wimara, Iwan Setiawan Wibisono (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 316
ending page: 325
doi: 10.30998/zh0x2423

Implementasi dan Pengujian Performa Server High Availability Menggunakan Metode Horizontal Scaling dengan Studi Kasus: Marketplace XYZ
type: item
description: Online marketplaces have become popular among the Indonesian public lately. This trend has an impact on the increasing visitor traffic, making the server's performance in handling requests heavier. Another impact that arises is the decline in web server performance accompanied by lag or network disruptions that cause web page responses to become slow. This issue can be addressed using load balancing, which is a method that distributes traffic across multiple servers to prevent load accumulation on a single server. Testing 10,000 requests with Apache Bench resulted in a response time of 7.725 ms for a server cluster (3 servers) using the round-robin algorithm. In comparison, the least connection algorithm produced a response time of 7.496 ms, while a single server resulted in 119.656 ms. In a stress test using JMeter with 10,000 requests, the server cluster produced a response time of 60 ms, while a single server resulted in 39.418 ms. In the failover implementation, load balancing works well in distributing requests to the available servers, ensuring that even during high traffic or server failures, the system maintains optimal performance and minimizes response times. Failover is the process of redirecting requests from a dead/broken server to another active server.
subject: Articles
  topic: section
subject: Algoritma round-robin dan least connection
  topic: keywords
subject: Failover
  topic: keywords
subject: Web Server
  topic: keywords
subject: Marketplace Daring
  topic: keywords
subject: Load balancing
  topic: keywords
subject: Ops
  topic: disciplines
subject: Software Engineering
  topic: disciplines
subject: Informatics
  topic: disciplines
creator: Achmad Nur Fauzy
creator: Muhammad Anis Al Hilmi
creator: Ilman Kadori
rights: Copyright (c) 2026 Achmad Nur Fauzy, Muhammad Anis Al Hilmi, Ilman Kadori (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 289
ending page: 297
doi: 10.30998/nv5r9785

Analisis Strategi Penerimaan Peserta Didik Baru Menggunakan K-Means Clustering dengan Optimasi Elbow
type: item
description: New Student Admission is an annual routine activity at schools, including SMP Citra Negara Depok. Every year, the school receives a large amount of registration data, but it has not been optimally utilized to determine the new student admission strategy for the following year, resulting in a decrease in the number of applicants. This study aims to cluster effective new student admission strategies using the K-Means clustering method optimized with the Elbow method and min-max normalization. The dataset used is derived from the registration data for the 2021–2022 and 2022–2023 academic years, with attributes including school name, number of classes, number of registrants, and difference. The Elbow Method results indicate that the optimal number of clusters is three. The K-Means process stops at the 7th iteration out of a maximum of 10 iterations. The clustering results in three strategies: a 55% discount during the October–December period, a brochure distribution strategy, and a 50% discount during the January–June period. The research findings indicate that the K-Means method optimized with the Elbow Method can help determine a more effective new student admission strategy for the school.
subject: Articles
  topic: section
subject: Strategi PPDB
  topic: keywords
subject: K-Means Clustering
  topic: keywords
subject: Data Mining
  topic: keywords
subject: Optimasi Metode Elbow
  topic: keywords
subject: Metode Min-Max
  topic: keywords
subject: Clustering
  topic: keywords
subject: Computer Science
  topic: disciplines
creator: Abdul Hadi
creator: Decky Ryansyah
creator: Goenawan Brotosaputro
rights: Copyright (c) 2026 Abdul Hadi, Decky Ryansyah, Goenawan Brotosaputro (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 280
ending page: 288
doi: 10.30998/b4efjt07

Sistem Pendukung Keputusan dalam Menentukan Kepuasan Masyarakat Terhadap Pelayanan di Kelurahan Kebon Pala dengan Metode TOPSIS
type: item
description: Public satisfaction assessment of services is one of the important indicators in improving service quality in government institutions, especially at the sub-district level. However, the Kebon Pala sub-district still conducts the evaluation of public satisfaction conventionally and subjectively because it has not yet used a structured decision-making method. This research aims to build a decision support system to determine the level of community satisfaction with services in Kebon Pala Village using the Technique for Order of Preference by Similarity to Ideal Solution method. The TOPSIS method is used to process community satisfaction data based on several service criteria, namely service time, staff friendliness, availability of facilities, clarity of information, and certainty of time and procedures. Research data were obtained through observation, interviews, and the distribution of questionnaires to the community receiving the service. The research results indicate that the system developed is capable of generating preference values and ranking the level of public satisfaction objectively and measurably, thus helping the sub-district authorities in evaluating service quality and determining priorities for public service improvements
subject: Articles
  topic: section
subject: Technique for Order of Preference by Similarity to Ideal Solution
  topic: keywords
subject: Kepuasan Masyarakat
  topic: keywords
subject: Pelayanan Publik
  topic: keywords
subject: Sistem Pendukung Keputusan
  topic: keywords
creator: Dimas Kurniawan
creator: Rayung Wulan
creator: Bondan Dwi Hatmoko
rights: Copyright (c) 2026 Dimas Kurniawan, Rayung Wulan, Bondan Dwi Hatmoko (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 270
ending page: 279
doi: 10.30998/tyembb21

Penentuan Jumlah Produksi pada CV Rairaka Konveksi Menggunakan Metode Fuzzy Tsukamoto
type: item
description: The CV Rairaka Konveksi system is currently still using a manual system. This causes the production quantity to be inaccurate due to demand uncertainty and fluctuations in raw material supply. There is a need for efforts to ensure that the production quantity can be calculated accurately. This research aims to design and build a decision support system to assist the CV Rairaka Konveksi in determining the optimal production quantity. The fuzzy Tsukamoto method is used because of its ability to handle uncertain data and provide output in crisp form. The research was conducted through stages of observation, interviews, system design, implementation, and testing. The system is designed with two input variables, namely demand and supply, and one output variable in the form of production quantity. The results of the testing by user application testing show that the system built is capable of providing accurate and efficient production quantity recommendations.
subject: Articles
  topic: section
subject: Fuzzy Tsukamoto
  topic: keywords
subject: Jumlah Produksi
  topic: keywords
subject: Sistem Pendukung Keputusan
  topic: keywords
creator: Sindi Apriantika Sari
creator: Abdurahman Abdurahman
creator: EK Ajeng Rahmi Pinahayu
rights: Copyright (c) 2026 Sindi Apriantika Sari, Abdurahman, EK Ajeng Rahmi Pinahayu (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 260
ending page: 269
doi: 10.30998/cwvz6570

Sistem Informasi Monitoring dan Evaluasi Kegiatan Mengajar Guru Berbasis Web pada SD Negeri 23 Ugyehek
type: item
description: A Web-Based Information System for Monitoring and Evaluating Teaching Activities at Ugyehek State Elementary School 23. At Ugyehek State Elementary School 23, the process of monitoring teaching activities is still carried out conventionally, which often results in information bottlenecks, a lack of accuracy, and the complexity of teacher performance evaluations. The research conducted is useful for designing and developing technology and innovations that can be used to monitor teachers’ teaching activities efficiently, accurately, and in an integrated manner. The Waterfall method was selected for system development, comprising the planning, analysis, design, coding, and testing phases. This project was built using the PHP platform and a database for data management. Test results show that the system is capable of recording teachers’ schedules and teaching activity reports, displaying summary data, which can be accessed by the school principal and relevant parties. Through this application, monitoring of teaching activities can be effective, transparent, and well-documented.
subject: Articles
  topic: section
subject: Web-Based
  topic: keywords
subject: Elementary Schools
  topic: keywords
subject: Teaching Activities
  topic: keywords
subject: Monitoring
  topic: keywords
subject: Information System
  topic: keywords
subject: Information Technology
  topic: disciplines
creator: Farida Nelce Indou
creator: Sofyan Sofyan
creator: Risma Petrus
creator: Mardewi Mardewi
rights: Copyright (c) 2026 Farida Nelce Indou, Sofyan Sofyan, Risma Petrus, Mardewi Mardewi (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 399
ending page: 407
doi: 10.30998/3525q026

Penerapan Rule-Based Classifier untuk Menentukan SLA Rate Pada PT Nettocyber Indonesia
type: item
description: Internet service providers are required to maintain service quality and reliability in order to enhance customer satisfaction and corporate value. One key indicator in service evaluation is the Service Level Agreement, which is calculated based on incident ticket data. However, at PT. Nettocyber Indonesia, the process of recording tickets and calculating SLAs is still done manually, which has the potential to cause errors, data inconsistencies, and low work efficiency. This study aims to develop a structured desktop-based system for recording incident tickets that can automatically classify and calculate SLAs. The system is built using the Java programming language with a MySQL database and employs a rule-based classifier method to group tickets based on specific parameters such as incident type, customer priority, and service impact. The results of this study indicate that the developed system improves the accuracy of ticket recording and classification and accelerates the SLA calculation process compared to manual methods. Consequently, this system can help enhance work efficiency and quality of service evaluation at internet service providers
subject: Articles
  topic: section
subject: Rule-Based Classifier
  topic: keywords
subject: Service Level Agreement
  topic: keywords
subject: Internet Service Provider
  topic: keywords
subject: Computer Science / Engineering
  topic: disciplines
subject: Teknik Informatika
  topic: disciplines
creator: Ahmad Juve Perdana
creator: Nofita Rismawati
creator: Norma Pravitasari
rights: Copyright (c) 2026 Ahmad Juve Perdana (Translator); Nofita Rismawati, Norma Pravitasari (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 354
ending page: 363
doi: 10.30998/bykg0t17

Implementasi Metode Forward Chaining untuk Deteksi Dini Serangan Jamur pada Tanaman Padi Berdasarkan Gejala Visual
type: item
description: In Indonesia, Oryza sativa is a major food commodity, and disease attacks, particularly those caused by fungal infections, greatly affect its productivity. Fungal infections in rice plants are often difficult to detect early due to the similarity of visual symptoms among different types of diseases and the limited knowledge of farmers. This research aims to implement an expert system that uses the forward chaining method to detect fungal attacks on rice plants early, based on visual symptoms. The forward chaining method is used as an inference mechanism by utilizing IF–THEN rules compiled based on interviews with agricultural experts and literature studies. The expert system was developed in the form of a web-based application and designed using UML modeling. The data used includes visual symptoms, types of fungi, and control methods. System testing is conducted using the black-box testing method to ensure functionality and diagnostic accuracy. The research results indicate that the system is capable of identifying the type of fungus on rice plants well based on the given symptoms and producing appropriate control recommendations. Thus, this expert system is expected to become an effective tool for farmers in detecting and handling fungal attacks more quickly and accurately.
subject: Articles
  topic: section
subject: gejala visual
  topic: keywords
subject: penyakit jamur
  topic: keywords
subject: tanaman padi
  topic: keywords
subject: forward chaining
  topic: keywords
subject: sistem pakar
  topic: keywords
creator: Bagus Sajiwo
creator: Rendi Prasetya
rights: Copyright (c) 2026 Bagus Sajiwo, Rendi Prasetya (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 250
ending page: 259
doi: 10.30998/cmq4vs65

Implementasi Algoritma Apriori Untuk Prediksi Pola Penjualan Produk Fashion pada Toko Innari G-Style
type: item
description: This research is motivated by the low utilization of transaction data among MSMEs, specifically at Toko Innari G-Style, which still records transactions manually, leading to sales data not being leveraged for strategic analysis. The objective of this research is to develop a web-based sales information system equipped with an analysis feature to identify purchasing patterns using the Apriori algorithm. The research method employs the association rule technique from Data Mining with the Apriori algorithm. Sales transaction data from December 2022 to March 2025 are processed through a pre-processing stage to generate association rules based on support, confidence, and lift values. The result of this research is an information system that successfully and accurately automates transaction recording and reporting. Furthermore, the implementation of the Apriori algorithm successfully identified patterns of frequently co-purchased products, which can be utilized to develop data-driven marketing strategies such as product recommendations and merchandise layout.
subject: Articles
  topic: section
subject: sales information system
  topic: keywords
subject: association rule
  topic: keywords
subject: msme
  topic: keywords
subject: java
  topic: keywords
subject: apriori
  topic: keywords
subject: Ilmu Komputer
  topic: disciplines
creator: Isa Subani
creator: Ni Wayan Parwati Septiani
rights: Copyright (c) 2026 Isa Subani, Ni Wayan Parwati Septiani (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-15
publication date: 2026-01-15
starting page: 201
ending page: 210
doi: 10.30998/km3mqr23

Software Quality Tourism Industry: Analisis Aplikasi Mobile Nusatrip dengan Metode System Usability Scale (SUS)
type: item
description: Industry using the System Usability Scale. SUS, or the System Usability Scale, was chosen because of its ease in providing a quantitative picture of an application's usability. This study includes the OVO, Spotify, and Mysurabaya applications to explore user perceptions of the interface and functionality of the applications. The research method uses a descriptive quantitative approach with the SUS questionnaire distributed to 42 active user respondents. The SUS score is calculated by summing the scores of each question item and multiplying it by a factor of 2.5. The Cronbach’s alpha test results show excellent internal consistency (0.793). The results indicate that the tested applications received an average SUS score that demonstrates excellent usability, such as NusaTrip with a score of 72.14, above the global average of 68. However, there is variation in user experience that indicates some aspects of the application need improvement. High-scoring items indicate an intuitive interface and well-integrated features, but low-scoring items emphasize the need to reduce the learning curve for new users. The research recommends adding tutorials or a help system to enhance the user experience.
subject: Articles
  topic: section
subject: User Experience (UX)
  topic: keywords
subject: Aplikasi Mobile
  topic: keywords
subject: Usability Evaluation
  topic: keywords
subject: System Usability Scale (SUS)
  topic: keywords
subject: AI
  topic: disciplines
subject: Informatic
  topic: disciplines
subject: Information Technology
  topic: disciplines
subject: Digital Heritage
  topic: disciplines
subject: Testing System
  topic: disciplines
subject: Usability System
  topic: disciplines
subject: Human Computer Interaction
  topic: disciplines
creator: Gde Brahupadhya Subiksa
creator: I Putu Astya Prayudha
creator: Ni Gusti Ayu Putu Harry Saptarini
creator: I Putu Bagus Arya Pradnyana
rights: Copyright (c) 2026 Gde Brahupadhya Subiksa, I Putu Astya Prayudha, Ni Gusti Ayu Putu Harry Saptarini, I Putu Bagus Arya Pradnyana (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 240
ending page: 249
doi: 10.30998/8rg2k952

Aplikasi Klasifikasi Penyakit Kentang Menggunakan Algoritma Convolution Neural Network (CNN)
type: item
description: Potatoes are an important horticultural commodity that is susceptible to various diseases such as black scurf, blackleg, common scab, dry rot, and pink rot. Early disease detection is crucial for reducing losses and increasing productivity. This study aims to develop an image-based potato disease classification model using the Convolutional Neural Network method. The dataset consists of 1,760 images divided into eight classes, with a data split of 70% training data, 20% validation data, and 10% test data. The data processing involves preprocessing and augmentation to improve the model’s generalisation. The convolutional neural network architecture used consists of four convolutional layers combined with batch normalisation, max pooling, dropout, and fully connected layers. The model was trained using the Adam optimiser with a learning rate of 0.0003 and a batch size of 32. Testing results show that the model achieved an accuracy of 86%, with an average precision of 0.87, a recall of 0.86, and an F1-score of 0.86. The evaluation results indicate that the model is capable of recognising most classes well, although errors still occur in those with high visual similarity. This study demonstrates that the CNN method is effective for classifying potato diseases based on digital images and has the potential for further development on larger datasets.
subject: Articles
  topic: section
subject: Digital Image
  topic: keywords
subject: CNN
  topic: keywords
subject: Potato diseases
  topic: keywords
subject: Classification
  topic: keywords
subject: Information Technology
  topic: disciplines
creator: I Putu Astya Prayudha
creator: Gde Brahupadhya Subiksa
creator: Putu Satya Saputra
creator: I Nyoman Rai Widartha Kesuma Kesuma
creator: Vianne Clarinta Putri Gurning
rights: Copyright (c) 2026 I Putu Astya Prayudha, Gde Brahupadhya Subiksa, Putu Satya Saputra, I Nyoman Rai Widartha Kesuma, Vianne Clarinta Putri Gurning (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 344
ending page: 353
doi: 10.30998/q2r2wm73

Perancangan Aplikasi Deteksi Plagiarisme dengan TF-IDF dan Cosine Similarity
type: item
description: Plagiarism is a serious challenge in the academic world that threatens scientific integrity. Access to commercial plagiarism detection tools like Turnitin is often limited due to high costs, while free tools have word count limitations and data privacy issues. This research aims to develop an offline plagiarism detection application based on natural language processing using the term frequency-inverse document frequency (TF-IDF) and cosine similarity algorithms. This application is designed to operate without an internet connection and without word count limitations and guarantees data security. The development method uses Python 3.13 with the PySide6 framework for the user interface and SQLite as the database. The test results on 1 test document and 9 comparison documents show a detection accuracy with an overall score of 9.38% (SkLearn method). The processing time for each is 8.55 seconds. This application is expected to be an alternative solution for students and educational institutions in independently and safely detecting plagiarism.
subject: Articles
  topic: section
subject: Python
  topic: keywords
subject: Cosine Similarity
  topic: keywords
subject: TF-IDF
  topic: keywords
subject: Natural Language Processing
  topic: keywords
subject: Deteksi Plagiarisme
  topic: keywords
creator: Shandy Arkan
creator: Heru Sulistiono
creator: Irawan Setiadi
rights: Copyright (c) 2026 Shandy Arkan, Heru Sulistiono, Irawan Setiadi (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 230
ending page: 239
doi: 10.30998/nz32fq32

Sistem Pakar Untuk Identifikasi Kerusakan Sepeda Motor Menggunakan Metode Forward Chaining pada Bengkel AKC Workshop
type: item
description: Rapid advancements in information technology have driven significant transformations across various sectors, including the automotive industry. One of the challenges faced by motorcycle repair shops is the diagnostic process, which is still performed manually and relies on the technician’s intuition, often leading to inefficiencies and potential errors in identifying issues. This study aims to develop an expert system based on the forward chaining method to facilitate a faster and more accurate initial diagnosis of motorcycle malfunctions. A case study was conducted at AKC Workshop, which faced similar challenges. This expert system was developed using a rule-based approach to mimic an expert’s thought process in diagnosing faults. Based on the test results, when the motorcycle exhibited symptoms G9, G10, G11, and G16, the system successfully identified the fault with a 100% match rate on rule 2 (R2), indicating that the motorcycle had a battery issue (weak battery). These results demonstrate that the developed expert system is capable of providing accurate diagnoses and has the potential to improve the efficiency and accuracy of services at motorcycle repair shops
subject: Articles
  topic: section
subject: Forward Chaining
  topic: keywords
subject: Java
  topic: keywords
subject: Expert system
  topic: keywords
subject: Teknik Informatika
  topic: disciplines
creator: Erlan Ramadhan
creator: Wanti Rahayu
creator: Sugeng Haryono
rights: Copyright (c) 2026 Erlan Ramadhan, Wanti Rahayu, Sugeng Haryono (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 334
ending page: 343
doi: 10.30998/zgfwew80

Sistem Pakar Pendeteksi Kerusakan Sepeda Motor Matik Injeksi Menggunakan Metode Forward Chaining
type: item
description: <p class="MsoNormal" style="mso-para-margin-top: 0cm; mso-para-margin-right: 0cm; mso-para-margin-bottom: 0cm; mso-para-margin-left: 0gd; text-align: justify; text-indent: -.2pt; mso-char-indent-count: 0; line-height: normal; mso-outline-level: body-text; mso-hyphenate: auto; tab-stops: 45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt; mso-vertical-align-alt: auto; margin: 0cm 0cm 0cm .1pt;">Currently, there is no expert system application specifically designed to diagnose damage to motorcycle engines, especially automatic injection types. Along with the rapid development of information technology, the implementation of computing technology has become crucial in overcoming various technical problems, including those in vehicle engines. The process of detecting damage to injection motorcycles requires in-depth knowledge and experience that is often not possessed by all mechanics, especially lay users. Therefore, the development of an expert system with the Forward Chaining method is a highly urgent solution. This system is expected to be able to detect damage to automatic injection motorcycles precisely, minimize repair errors (human error), and increase diagnostic accuracy.
subject: Articles
  topic: section
subject: Automatic Scooter
  topic: keywords
subject: Damage
  topic: keywords
subject: Forward Chaining
  topic: keywords
subject: Expert System
  topic: keywords
subject: Computer Science
  topic: disciplines
creator: Galih Mustopa
creator: Muhamad Irsan
creator: Muhammad Soleh Ritonga
rights: Copyright (c) 2026 Muhamad Irsan, Galih Mustopa, Muhammad Soleh Ritonga (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-15
publication date: 2026-01-15
starting page: 192
ending page: 200
doi: 10.30998/3m9dec54

Analisis Prediktif Dropout Mahasiswa Berdasarkan Kinerja Akademik Semester Awal Menggunakan Machine Learning
type: item
description: Student dropout is a critical issue in higher education. This study aims to develop a predictive model of dropout based on early academic performance using Random Forest and Gradient Boosting algorithms. The dataset, sourced from the UCI Repository, contains 4,424 student records. Key features analyzed include the number of enrolled courses, evaluations, average grades, and enrollment age. Results show that the Gradient Boosting algorithm achieved 70.05% accuracy, while Random Forest reached 70.16%, both performing best in classifying graduates. The model successfully identifies high-risk students, although challenges remain in predicting “enrolled” status. These findings highlight the potential of machine learning for early dropout detection and support more targeted academic interventions.
subject: Articles
  topic: section
subject: Gradient Boosting
  topic: keywords
subject: Random Forest
  topic: keywords
subject: machine learning
  topic: keywords
subject: academic performance
  topic: keywords
subject: dropout
  topic: keywords
subject: Data Science
  topic: disciplines
subject: Teknologi Informasi
  topic: disciplines
creator: Putu Satya Saputra
rights: Copyright (c) 2026 Putu Satya Saputra (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-15
publication date: 2026-01-15
starting page: 164
ending page: 171
doi: 10.30998/ed38e865

Sistem Monitoring Suhu Dan Humidity pada Data Center PT Elga Yasa Media Menggunakan IoT
type: item
description: The purpose of this final project is to design a temperature and humidity monitoring system in the data center with in the scope of PT Elga Yasa Media to carry out a manual data acquisition process followed by the development of a monitoring system to facilitate access and accurate monitoring, and be able to provide fast and precise information to make reports that are more structured and in accordance with direct data in the field. The research method is still done manually for the initial data, then the results of the research will produce a system that is installed in the data center of PT Elga Yasa Media, and test the temperature and humidity sensors. The method used for this final project research is the fuzzy method. fuzzy which is one of the software development methods for handling uncertainty and ambiguity in data center environment data. The results achieved are that the temperature and humidity monitoring system at the PT Elga Yasa Media data center is well programmed so that the design for detecting temperature and humidity becomes more effective and efficient, and can be monitored directly without having to make a physical visit to the data center. In building this system, a system design tool, namely Use Case Diagram, for IoT devices and sensors using ESP32 and DHT22, using the C language, using the PHP programming language, MySQL database with XAMPP, and the Laravel framework as a website display of the temperature and humidity monitoring system.
subject: Articles
  topic: section
subject: DHT22
  topic: keywords
subject: Humidity
  topic: keywords
subject: Temperature
  topic: keywords
subject: IoT
  topic: keywords
subject: Data Center
  topic: keywords
subject: Ilmu Komputer
  topic: disciplines
creator: Rivaldo Ibrahim
creator: Achmad Birowo
creator: Aan Risdiana
rights: Copyright (c) 2026 Rivaldo Ibrahim Desi, Achmad Birowo, Aan Risdiana (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-15
publication date: 2026-01-15
starting page: 157
ending page: 163
doi: 10.30998/4rrndr47

Network Automation dengan Metode NDLC Menggunakan Bahasa Pemrograman Python
type: item
description: The development of information technology is so rapid, especially on computer networks. Network complexity is a challenge for network administrators in managing many devices, performing maintenance and facing increasingly sophisticated security threats. In this case, network automation is the solusiton. With network automation, the configuration of several network devices can be done simultaneously. The network devices are Cisco routers and switches. The purpose of this research is to create a web-based network design to be carried out with the initial stage of network analysis and problems that arise when building large-svale networks. By utilizing the python programming language, network automation can be implemented. Python has paramiko library that functions as an ssh client. The results of this research built a network automation web for Cisco router and switch network devices, with django as a web developer. So, several devices can be configured simultaneously through web network automation
subject: Articles
  topic: section
subject: Python
  topic: keywords
subject: NDLC Method
  topic: keywords
subject: Network Automation
  topic: keywords
subject: Ilmu Komputer
  topic: disciplines
creator: Achmad Fauzi
creator: Desi Desi
creator: Ade Kurnia Solihin
rights: Copyright (c) 2026 Achmad Fauzi, Desi Desi, Ade Kurnia Solihin (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-15
publication date: 2026-01-15
starting page: 149
ending page: 156
doi: 10.30998/zxyn8s47

Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik dengan Metode Simple Additive Weighting (SAW) pada PT Satria Antaran Prima (SAP)
type: item
description: The decision-making process objectively and measurably based on a set of predetermined criteria. This research aims to develop a decision support system capable of providing recommendations for the best employees at PT. Satria Antaran Prima using the Simple Additive Weighting method. This system evaluates employee performance based on several criteria such as attendance, discipline, productivity, cooperation, and responsibility. Data is obtained through performance evaluations, interviews with human resource managers, and the results of the company's routine assessments. The calculation process is carried out by weighting each criterion and normalizing the data using the SAW method to determine the highest total score as an indicator of the best employee. The research results indicate that the application of the SAW method can produce objective, transparent, and efficient assessments, thereby assisting management in accurately determining high-performing employees. The implementation of this system is expected to enhance work motivation, strengthen the performance appraisal system, and support strategic decision-making within the company environment.
subject: Articles
  topic: section
subject: Simple Additive Weighting
  topic: keywords
subject: Karyawan Terbaik
  topic: keywords
subject: Sistem Pendukung Keputusan
  topic: keywords
creator: Raihan Raihan
creator: Laksana Priyo Abadi
creator: Muhammad Ardiansyah
rights: Copyright (c) 2026 raihan, Laksana Priyo Abadi, Muhammad Ardiansyah (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 221
ending page: 229
doi: 10.30998/jhjz9515

Perancangan Pembelajaran Online dengan Fitur Simulasi Tes Kerja Menggunakan Metode Simple Additive Weighting (SAW) pada SMK Ganesa Satria 2 Depok
type: item
description: Vocational High School graduates are required to have well-prepared work readiness to face competition in the industrial world. However, at SMK Ganesa Satria 2 Depok, the process of evaluating students' readiness through work test simulations is still conducted conventionally, making the assessment tend to be subjective and time-consuming. This research aims to design an online learning system that integrates a work test simulation feature by applying the Simple Additive Weighting method as a decision support system to evaluate student readiness. The system development method used is the Waterfall model, which includes requirements analysis, design, implementation, and testing. The SAW calculation is performed by considering criteria such as answer accuracy, completion speed, and understanding of basic concepts. The research results indicate that the system developed is capable of automatically processing simulation data and providing an objective ranking of student readiness. The implementation of this system is expected to assist the school in monitoring student progress and to make it easier for students to prepare for actual job selection processes.
subject: Articles
  topic: section
subject: Sistem Pendukung Keputusan
  topic: keywords
subject: SMK
  topic: keywords
subject: Simple Additive Weighting
  topic: keywords
subject: Simulasi Tes Kerja
  topic: keywords
subject: E-learning
  topic: keywords
creator: Ramadhanu Kadir Rachono
creator: Aswin Fitriansyah
creator: Sutrisno Sutrisno
rights: Copyright (c) 2026 Ramadhanu Kadir Rachono, Aswin Fitriansyah, Sutrisno (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 211
ending page: 220
doi: 10.30998/bnhrsh88

Analisis Sentimen Kenaikan Pbb Berbasis Tiktok Menggunakan Support Vector Machine
type: item
description: The increase in Land and Building Tax for Rural and Urban Areas (PBB-P2) has generated diverse public reactions that are widely expressed through social media platforms. TikTok, characterized by high user engagement and informal communication patterns, provides a relevant medium for observing public sentiment toward fiscal policies. This study examines public sentiment regarding the PBB-P2 increase by applying a Support Vector Machine (SVM)–based classification approach. Two kernel configurations, Linear and Polynomial, are compared to identify differences in classification behavior when handling social media text data. User comments were collected automatically and processed through text cleaning, feature extraction, and sentiment labeling stages prior to model training. Model performance was analyzed using confusion matrix–based evaluation to observe prediction patterns across sentiment classes. The findings indicate noticeable differences in classification stability between the two kernel types, with the Linear kernel showing more consistent behavior when applied to imbalanced sentiment distributions. These results suggest that selecting a kernel aligned with the characteristics of textual data is an important consideration in social media–based sentiment analysis of public policy issues
subject: Articles
  topic: section
subject: Public Policy
  topic: keywords
subject: TikTok
  topic: keywords
subject: Support Vector Machine
  topic: keywords
subject: PBB-P2
  topic: keywords
subject: Sentiment Analysis
  topic: keywords
subject: Informatika; Data Mining; Machine Learning
  topic: disciplines
creator: Erhan Perdana
creator: Anggun Mentari
creator: Uci Azhari Chaniago
creator: Juniardo Purba
creator: Agus Perdana Windarto
rights: Copyright (c) 2026 Erhan Perdana, Anggun Mentari, Uci Azhari Chaniago, Juniardo Purba, Agus Perdana Windarto (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-15
publication date: 2026-01-15
starting page: 182
ending page: 191
doi: 10.30998/d0qg9387

Sistem Pendukung Keputusan Penerimaan Karyawan Baru pada PT Kalingga Prima Bangun Setia dengan Metode SAW
type: item
description: The development of information technology has brought significant changes in various fields, including human resource management at PT Kalingga Prima Bangun Setia, a construction and property development company in Bekasi City. The manual process of recruiting new employees is a major challenge, as it results in low efficiency and is prone to errors. To address this issue, this study proposes the development of a decision support system based on the Simple Additive Weighting (SAW) method using JAVA Netbeans. This system aims to optimize the employee selection process by applying more standardized and professional criteria while also enhancing HRD's role in ensuring more accurate and efficient decisions. The implementation of this system is also expected to replace manual data archiving methods, speed up information access, and reduce data processing errors, thereby supporting the company's sustainability and success amid global competition.
subject: Articles
  topic: section
subject: SAW Method
  topic: keywords
subject: New Employees
  topic: keywords
subject: Employee Recruitment
  topic: keywords
subject: Decision Support System
  topic: keywords
subject: Computer Science
  topic: disciplines
creator: Age Rusdiyanto
creator: Rahmatika
creator: Rini Widia Putri Z
rights: Copyright (c) 2026 Age Rusdiyanto, Rahmatika, Rini Widia Putri Z (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-01-15
publication date: 2026-01-15
starting page: 140
ending page: 148
doi: 10.30998/jc17qa67