Expert System for Diagnosing Pregnancy Complaints by Forward Chaining
DOI:
10.33395/sinkron.v5i1.10593Keywords:
diagnose; complaints; pregnancy; midwife; forward chainingAbstract
Limited time in consulting becomes an obstacle for midwives in diagnosing complaints in pregnant women, especially those who are already in the III trimester and approaching the labor process. Misdiagnosis results in inaccuracies in the provision of solutions and actions. Initial treatment that corresponds to the complaints of pregnant women especially the third trimester is expected to reduce mortality rates in the mother and fetus. Expert System can be a timely solution with not too long so as to improve the quality of examination on midwives. The methods used are identification, primary and secondary data collection, forward chaining data analysis combined with bayesian, and evaluation with the calculation of the percentage of system success. Samples taken by 20 patients and 4 patients were declared unsyed because they had only one complaint. Meanwhile, 16 patients had some complaints that complied with the Rules. A total of 11 out of 16 patients or about 70% had valid results between the diagnosis of experts/midwives with the system. It can be concluded that the system works well to diagnose complaints in patients with a third trimester gestational age so that midwives can provide appropriate initial solutions and treatment in reducing maternal and infant mortality.
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References
Avrizal, R. (2019). Sistem Pakar Mendiagnosa Penyakit Flu Babi Menerapkan Metode Hybrid Case Based. Jurnal Riset Komputer (JURIKOM), 6(2), 204–210.
B A Sitorus, Aris, Pribowo, P., & Irawati, A. R. (2018). Expert System for Pregnant Mothers Treatment and Early Disease Detection for Infants and Toddlers Based on Android (Kasih Ibu). In ICASMI (pp. 1–6). Bandar Lampung: IOP Publishing.
Gunawan, A., Defit, S., & Sumijan. (2020). Sistem Pakar dalam Mengidentifikasi Penyakit Kandungan Menggunakan Metode Forward Chaining Berbasis Android. Jurnal Sistem Informasi Dan Teknologi, 2(1), 15–22.
Hasbiyanor, A., & Bahar. (2017). Sistem Pakar Diagnosa Keluhan Selama Masa Kehamilan Menggunakan Metode Certainty Factor Berbasis Web. JUTISI, 6, 1345–1356.
Hasniati, Arianti, & Philip, W. (2019). RAPAN METODE BAYESIAN NETWORK MODEL PADA SISTEM DIAGNOSA PENYAKIT SESAK NAFAS BAYI. Jurnal IKRA-ITH Informatika, 3(2), 19–26.
Hatta, H. R., Ulfah, F., Khairina, D. M., Hamdani, H., & Maharan, S. (2017). Web-expert system for the detection of early symptoms of the disorder of pregnancy using a forward chaining and Bayesian method. Journal of Theoretical and Applied Information Technology, 95(11), 2589–2599.
Hayadi, B. H., & Rukun, K. (2016). What is Expert System. Yogyakarta: Deepublish.
Maryani, R., & Haryanto, D. (2018). SISTEM PAKAR DIAGNOSA PENYAKIT PADA IBU HAMIL DENGAN METODE FORWARD CHAINING. JUMANTAKA, 1, 151–160.
Munti, N. Y. S., & Effindri, F. A. (2017). Perancangan Aplikasi Sistem Pakar Diagnosa Penyakit Ginekologi Menggunakan Metode Forward Chaining Berbasis Web Mobile. Media Infotama, 13, 67–72.
Ramanda, K. (2015). PENERAPAN SISTEM PAKAR UNTUK MENDIAGNOSA PENYAKIT PADA KEHAMILAN. Jurnal Pilar Nusa Mandiri, 11(2), 179–185.
Umoh, U., & Nyoho, E. (2015). A Fuzzy Intelligent Framework for Healthcare Diagnosis and Monitoring of Pregnancy Risk Factor in Women. Journal of Health, Medicine and Nursing, 18, 97–112.
Widyaningsih, P., & Astutiningsih, A. (2016). APLIKASI SISTEM PAKAR BERBASIS WEB UNTUK KONSULTASI MASALAH KEHAMILAN MENGGUNAKAN FORWARD CHAINING DAN PRODUCTION RULE. INFOKES, 6, 14–20.