PRE-ECLAMPSIA DIAGNOSIS EXPERT SYSTEM USING FUZZY INFERENCE SYSTEM MAMDANI
DOI:
https://doi.org/10.33480/techno.v20i2.4622Keywords:
diagnosis, expert system, fuzzy enference mamdani system, preeclampsiaAbstract
Various institutions utilize computer information systems to analyze and process data. An expert system is an information system that is used to help analyze and determine decisions on a problem based on rules determined by experts. This research focuses on creating a prototype expert system for diagnosing pre-eclampsia or pregnancy poisoning in pregnant women based on measuring blood pressure and checking proteinuria. The existing data is then analyzed using the Mamdani system's fuzzy inference method. Supporting theory regarding the fuzzy inference system of Mamdani, pre-eclampsia and its examination indicators will be used as a basis for creating this expert system prototype. The data used were secondary data on preeclampsia patients in the form of medical records of blood pressure measurements, proteinuria examinations and doctor diagnoses of preeclampsia patients at two Regional General Hospitals (RSUD), namely Atambua and Kefamenanu, totaling 20 samples. The interface or user interface of this prototype system is made as simple as possible so that it can be operated by all ordinary people. The programming language used is Visual Basic (VB) with the Visual Studio 2010 developer application. The initial prototype of this system will continue to be developed until it can become a Information systems or real applications used in hospitals. The results of this research are that the expert system for diagnosing preeclampsia can be used well and easily by hospital staff and show congruence between the system diagnosis results and the diagnosis results from obstetricians or experts in the 20 processed data.
References
Ananta, P., Putra, D., Purnawan, I. K. A., Purnami, D., & Putri, S. (2018). Sistem Pakar Diagnosa Penyakit Mata dengan Fuzzy Logic dan Naïve Bayes. Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi), 6(1), 35–46.
Anindita, M., Pristyanto, Y., Sismoro, H., Nurmasani, A., & Nugraha, A. (2023). Diagnose Of Mental Illness Using Forward Chaining And Certainty Factor. Techno Nusa Mandiri: Journal of Computing and Information Technology, 20(2), 63–70.
Athiyah, U., Citra, F., Putri, D., Saputra, R. A., Hekmatyar, H. D., Satrio, T. A., & Perdana, A. I. (2021). Diagnosa Resiko Penyakit Jantung Menggunakan Logika Fuzzy Metode Tsukamoto. Jurnal Ilmiah Rekam Medis Dan Informatika Kesehatan (Infokes), 11(1), 31–40.
Bardja, S. (2020). Risk Factor for The Occurrence of Severe Preeclampsia / Eclampsia in Pregnant Woman. Jurnal Kebidanan EMBRIO, 12(1), 18–30.
Dona, Maradona, H., & Masdewi. (2021). Sistem Pakar Diagnosa Penyakit Jantung dengan Metode Case Based Reasoning (CBR). Jurnal Sistem Informasi ZONAsi, 3(1), 1–12.
Handayani, V. V. (2022, January 29). Ini Pemeriksaan untuk Deteksi Preeklamsia. Halodoc. https://www.halodoc.com/artikel/pemeriksaan-untuk-deteksi-preeklamsia
Hanif, K. H., Muntiari, N. R., Ramadhani, P. A., Komputer, T., Tarakan, U. B., Bangsa, U. H., … Factor, C. (2022). Penerapan Metode Certainty Factor untuk Mendiagnosa Penyakit Preekslamsia pada Ibu Hamil dengan Menggunakan Bahasa Pemrograman Python. Jurnal Teknik Informatika (INSECT) Informatics and Security, 7(2), 63–71.
Juwita, A., Sarjon, D., & Yuhandri, Y. (2021). Sistem Pakar Menggunakan Metode Forward Chaining pada Tingkat Kesembuhan Terapi Farmakologi dan Gaya Hidup Sehat Terhadap Pasien Hipertensi. Jurnal Informasi Dan Teknologi (JIdT), 3(1), 10–15. https://doi.org/10.37034/jidt.v3i1.82
Nassa, M. (2018). Analisis Program Revolusi Kesehatan Ibu dan Anak Dan Dampaknya Terhadap Penurunan Angka Kematian Ibu Dan Bayi. UGM Public Health Symposium, 14(1), 1.
Nizar, H., Shafira, A. S., Aufaresa, J., Awliya, M. A., & Athiyah, U. (2021). Perbandingan Metode Logika Fuzzy Untuk Diagnosa Penyakit Diabetes. Jurnal Sistem Informasi Dan Telematika (Telekomunikasi, Multimedia Dan Informatika), 12(1), 37–41.
Novianti, N., Pribadi, D., & Saputra, R. A. (2018). Sistem Pakar Diagnosa Pulmonary TB Menggunakan Metode Fuzzy Logic. Jurnal Informatika Bina Sarana Informatika (BSI), 5(2), 228–236.
Rizki, S., & Maulana, A. (2018). Jurnal Ilmiah Informatika ( JIF ) Artificial Intellegence Untuk Mendeteksi Penyakit Kelenjar Getah Bening. Jurnal Ilmiah Informatika (JIF) Universitas Putera Batam, 6(1), 54–61.
Rizky, R., & Hakim, Z. (2020). Sistem Pakar Menentukan Penyakit Hipertensi Pada Ibu Hamil Di RSUD Adjidarmo Rangkas Bitung Provinsi Banten. Jurnal SISFOKOM (Sistem Informasi Dan Komputer), 9(1), 30–34.
Simarmata, E. R. (2021). Sistem Pakar Diagnosis Penyakit Hipertensi dengan Menggunakan Metode Forward Chaining dan Teori Probabilitas. Jurnal Methodika, 7(1), 56–61.
Sitinjak, F. (2021). Sistem Pakar Mendiagnosa Penyakit Hipertensi Menggunakan Metode Dempster Shafer. Jurnal Teknologi Komputer Sean Institute, 15(1), 51–55.
Supriyono, & Fadila, E. (2022). Sistem Pakar Penegakan Diagnosa Penyakit Hipertensi dengan Inferensi Forward Chaining menggunakan Support Vector Machine (SVM). Jurnal Kesehatan Medika Udayana, 8(2), 207–221.
Surorejo, S., Chaeriko, Y. P., & Ananda, P. S. (2022). Penerapan Metode Naive Bayes pada Sistem Pakar untuk Diagnosa Penyakit Hipertensi. Indonesian Journal of Informatics and Research (IJIR), 3(1), 8–17.
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