Sistem Pakar Diagnosa Penyakit Ganguan Kehamilan Menggunakan Metode Berbasis WEB
DOI:
https://doi.org/10.55606/juisik.v5i3.1791Keywords:
Certainty Factor, Diagnosis, Expert Systems, Pregnancy Disorders, WebAbstract
Regnancy is a physiological stage that requires intensive monitoring and attention because various complications can arise and potentially threaten the safety of the mother and fetus. The limited number of medical personnel and the low level of health literacy of pregnant women regarding the symptoms of pregnancy disorders are often factors causing delays in the diagnosis and early treatment process. Therefore, this study proposes the design of a web-based expert system that functions as an aid in diagnosing pregnancy disorders by applying the Certainty Factor (CF) method. The Certainty Factor method was chosen because it is able to represent the level of expert confidence in a hypothesis based on symptoms provided by the user, thus resulting in more measured decisions. The system was developed using the PHP programming language with MySQL database support, and is designed to be accessible online through a web-based interface. Test results show that the system has a fairly high level of accuracy, with the diagnosis concordance rate reaching approximately 90% with the expert.
References
Agusli, R., Iqbal, M., & Saputra, F. (2020). Sistem pakar diagnosa penyakit pada ibu hamil dengan metode certainty factor berbasis web. AJCSR: Academic Journal of Computer Science Research, 2(1). https://doi.org/10.38101/ajcsr.v2i1.264
Anam, A. S. M. A. R. (2021). Penentuan ekstrakurikuler siswa sesuai minat bakat dengan case-based reasoning dan certainty factor. Jurnal Teknik Informatika dan Sistem Informasi, 7(3), 627–642. https://doi.org/10.28932/jutisi.v7i3.4011
Arsyad, M. Z., Mary, T., & Junaidi, S. (2025). Perancangan sistem informasi akademik (SIAKAD) berbasis web di SMK Negeri 1 Sijunjung. Jurnal Ilmiah Sistem Informasi dan Teknik Informatika (JISTI), 8(1), 65–75. https://doi.org/10.57093/jisti.v8i1.275
Badan Pusat Statistik. (2023). Survei Demografi dan Kesehatan Indonesia (SDKI) 2022. Badan Pusat Statistik.
Damayanti, N. A., Wulandari, R. D., & Ridlo, I. A. (2023). Maternal health care utilization behavior, local wisdom, and associated factors among women in urban and rural areas, Indonesia. International Journal of Women's Health, 15, 665–677. https://doi.org/10.2147/IJWH.S379749
Hariyanto, R. D., & Leidiyana, H. (2020). Sistem pakar untuk mendiagnosa penyakit persendian menggunakan metode certainty factor. Jurnal Komtika (Komputasi dan Informatika), 4(1), 27–34. https://doi.org/10.31603/komtika.v4i1.3701
Hendrian, S. (2025). Implementasi metode forward chaining pada sistem pakar pemilihan jurusan sekolah menengah atas. Jurnal Teknik Mesin, Industri, Elektro dan Informatika, 4(1), 295–302. https://doi.org/10.55606/jtmei.v4i1.4822
Ismail. (2023). Sistem pendukung keputusan penentuan jurusan menggunakan metode multi factor evaluation process (MFEP) di SMAN 5 Soppeng. Jurnal Ilmiah Sistem Informasi dan Teknik Informatika (JISTI), 6(1), 9–19. https://doi.org/10.57093/jisti.v6i1.143
Iswanti, S., Syaifudin, M., & Korayanto, D. (2021). Aplikasi pendiagnosa cedera lutut dan saran fisioterapinya berbasis sistem pakar. Jurnal Inovtek Polbeng, 6(2), 194–204. https://doi.org/10.35314/isi.v6i2.2052
Kementerian Kesehatan Republik Indonesia. (2019). Laporan nasional Riset Kesehatan Dasar (Riskesdas) 2018. Badan Penelitian dan Pengembangan Kesehatan.
Kusumah, I. M. Y., Apriyanti, L., & Rafki, P. R. (2022). Sistem pakar diagnosa stres pada mahasiswa tingkat akhir dengan menggunakan metode certainty factor berbasis Android. Jurnal Teknologi Informasi dan Komunikasi, 11(1), 9–18. https://doi.org/10.58761/jurtikstmikbandung.v11i1.165
Lourdusamy, R., & Gnanaprakasam, J. (2023). Expert systems in AI: Components, applications, and characteristics focusing on chatbot. In Data science with semantic technologies (pp. 217–231). CRC Press. https://doi.org/10.1201/9781003310792-13
Mapari, S. A., Shrivastava, D., Dave, A., Bedi, G. N., Gupta, A., Sachani, P., Kasat, P. R., & Pradeep, U. (2024). Revolutionizing maternal health: The role of artificial intelligence in enhancing care and accessibility. Cureus, 16(9). https://doi.org/10.7759/cureus.69555
Negnevitsky, M. (2025). The history of artificial intelligence. WIT Transactions on Information and Communication Technologies, 19.
Pambudi, Y. T., Tampubolon, R., & Mangalik, G. (2022). Faktor penyebab kematian ibu hamil dengan preeklampsia di wilayah kerja Puskesmas Klareyan Kabupaten Pemalang. Jurnal Keperawatan Muhammadiyah, 7(2).
Purnama, P. A. W., Putra, T. A., Afira, R., & Putra, O. E. (2022). Sistem pakar untuk mengetahui gaya belajar anak menggunakan metode forward chaining. REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer, 6(2), 124–129.
Ramakrishnan, R., Rao, S., & He, J.-R. (2021). Perinatal health predictors using artificial intelligence: A review. Women's Health, 17. https://doi.org/10.1177/17455065211046132
Syairaji, M., Nurdiati, D. S., Wiratama, B. S., Prüst, Z. D., Bloemenkamp, K. W. M., & Verschueren, K. J. C. (2024). Trends and causes of maternal mortality in Indonesia: A systematic review. BMC Pregnancy and Childbirth, 24(1), 515. https://doi.org/10.1186/s12884-024-06687-6
Wijaya, B. A., & Tanjung, J. P. (2020). Expert system diagnosis human eye diseases using certainty factor method web-based. Sinkron: Jurnal dan Penelitian Teknik Informatika, 5(1), 78–83. https://doi.org/10.33395/sinkron.v5i1.1057
World Health Organization. (2023). Maternal mortality: Levels and trends 2023.
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