Prediksi Risiko Stunting Prakehamilan Menggunakan Sistem Pakar Certainty Factor Berbasis Mobile

Muhamad Hadi Arfian; Noviandi Noviandi; Fahmi Zain

doi:10.30998/fkkvhz11

Authors

Muhamad Hadi Arfian Universitas Esa Unggul Author
Noviandi Noviandi Universitas Esa Unggul Author
Fahmi Zain Universitas Esa Unggul Author

DOI:

https://doi.org/10.30998/fkkvhz11

Keywords:

Mobile application, Certainty factor, Early detection, Expert system, Pre-pregnancy stunting

Abstract

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.

Downloads

Download data is not yet available.

References

Arifin, S. R. (2024). System Usability Scale (SUS) implementation in Ruang Baca Virtual – UT Library. MATRIX: Jurnal Manajemen Teknologi Dan Informatika, 14(1), 1–8. https://doi.org/10.31940/matrix.v14i1.1-8.

Desnelita, Y., Cesar, M., Gustientiedina, G., Hajjah, A., & Putri, R. N. (2025). Implementation of Certainty Factor Method in Mental Health Diagnosis Expert System in Adolescents Aged 18 – 24 Years. Journal of Applied Business and Technology, 6(1), 42–51. https://doi.org/10.35145/jabt.v6i1.195.

Dhamnetiya, D., Jha, R. P., Shalini, S., & Bhattacharyya, K. (2022). How to Analyze the Diagnostic Performance of a New Test? Explained with Illustrations. Journal of Laboratory Physicians, 14(01), 090–098. https://doi.org/10.1055/s-0041-1734019.

Erika, K. A., Fadilah, N., Latif, A. I., Hasbiah, N., Juliaty, A., Achmad, H., & Bustamin, A. (2024). Stunting Super App as an Effort Toward Stunting Management in Indonesia: Delphi and Pilot Study. JMIR Human Factors, 11. https://doi.org/10.2196/54862.

Haque, R., Alam, K., Rahman, S. M., Mustafa, M. U. R., Ahammed, B., Ahmad, K., Hashmi, R., Wubishet, B. L., & Keramat, S. A. (2022). Nexus between maternal underweight and child anthropometric status in South and South-East Asian countries. Nutrition, 98. https://doi.org/10.1016/j.nut.2022.111628.

Kementerian Kesehatan RI. (2025). SSGI 2024: Prevalensi Stunting Nasional Turun Menjadi 19,8%. https://kemkes.go.id/id/ssgi-2024-prevalensi-stunting-nasional-turun-menjadi-198?.

Musgrave, L., Cheney, K., Dorney, E., Homer, C. S. E., & Gordon, A. (2023). Addressing Preconception Behavior Change Through Mobile Phone Apps: Systematic Review and Meta-analysis. Journal of Medical Internet Research, 25. https://doi.org/https://doi.org/10.2196/41900.

Muttaqin, M., & Pratama, R. A. (2022). Rancang Bangun Sistem Informasi Pendataan dan Monitoring Tumbuh Kembang Anak Sebagai Upaya Pencegahan Stunting Desa Kotapari. Jurnal Nasional Teknologi Komputer, 2(4).

Nadhiroh, S. R., Micheala, F., Tung, S. E. H., & Kustiawan, T. C. (2023). Association between maternal anemia and stunting in infants and children aged 0–60 months: A systematic literature review. In Nutrition (Vol. 115). Elsevier Inc. https://doi.org/10.1016/j.nut.2023.112094.

Ng, K. Y. B., Steegers-Theunissen, R., Willemsen, S., Wellstead, S., Cheong, Y., & Macklon, N. (2021). Smartphone-based lifestyle coaching modifies behaviours in women with subfertility or recurrent miscarriage: a randomized controlled trial. RBMO, 43(1). https://doi.org/10.1016/j.rbmo.2021.04.003.

Noviandi, N., Aryani, D., & Ichwani, A. (2022). Sistem Pakar Diagnosis Tingkat Stres Berbasis Android dengan Metode Certainty Factor. Jurnal Media Informatika Budidarma, 6(4), 2367. https://doi.org/10.30865/mib.v6i4.4727.

Oostingh, E. C., Koster, M. P. H., van Dijk, M. R., Willemsen, S. P., Broekmans, F. J. M., Hoek, A., Goddijn, M., Klijn, N. F., van Santbrink, E. J. P., Steegers, E. A. P., Laven, J. S. E., & Steegers-Theunissen, R. P. M. (2020). First effective mHealth nutrition and lifestyle coaching program for subfertile couples undergoing in vitro fertilization treatment: a single-blinded multicenter randomized controlled trial. Fertility and Sterility, 114(5), 945–954. https://doi.org/10.1016/j.fertnstert.2020.04.051.

Ratnawati, F., Hardinata, N., & Supendi. (2025). Development of a Certainty Factor-Based Expert System for Nutrition Consultation and Stunting Prevention in Coastal Areas: A Case Study of Bengkalis Regency. Jurnal Teknologi Dan Open Source, 8(2), 539–553. https://doi.org/10.36378/jtos.v8i2.4858.

Sa, M. R., Siregar, adah, & Amanda Putri, R. (2023). Sistem Informasi Geografis Dalam Monitoring Daerah Prioritas Penanganan Stunting Pada Anak Di Kota Medan. Journal of Science and Social Research, 6(3), 643–648. http://jurnal.goretanpena.com/index.php/JSSR.

Saibene, A., Assale, M., & Giltri, M. (2021). Expert systems: Definitions, advantages and issues in medical field applications. In Expert Systems with Applications (Vol. 177). Elsevier Ltd. https://doi.org/10.1016/j.eswa.2021.114900.

Sembiring, A. S., Sulindawaty, Manahan, O., Napitupulu, M. H., Hasugian, P. S., Riandari, F., Mahdalena Simanjorang, R., Simangunsong, A., Utami, Y., & Sihotang, H. T. (2019). Implementation of Certainty Factor Method for Expert System. Journal of Physics: Conference Series, 1255(1). https://doi.org/10.1088/1742-6596/1255/1/012065.

Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach’s alpha. In International journal of medical education (Vol. 2, pp. 53–55). https://doi.org/10.5116/ijme.4dfb.8dfd.

Word Health Organization (WHO). (2024, March 1). Malnutrition. https://www.who.int/news-room/fact-sheets/detail/malnutrition?.

Young, M. F., Nguyen, P. H., Casanova, I. G., Addo, O. Y., Tran, L. M., Nguyen, S., Martorell, R., & Ramakrishnan, U. (2018). Role of maternal preconception nutrition on offspring growth and risk of stunting across the first 1000 days in Vietnam: A prospective cohort study. PLoS ONE, 13(8). https://doi.org/10.1371/journal.pone.0203201.

Zolfagharnasab, M. H., Damari, S., Soltani, M., Ng, A., Karbalaeipour, H., Haghdadi, A., Saghayan, M. H., & Matinfar, F. (2025). A novel rule-based expert system for early diagnosis of bipolar and Major Depressive Disorder. Smart Health, 35. https://doi.org/10.1016/j.smhl.2024.100525.