AN EXPERT SYSTEM FOR DETECTION OF DIABETES MELLITUS WITH FORWARD CHAINING METHOD

  • Tati Mardiana (1*) Information System, Universitas Bina Sarana Informatika, Jakarta, Indonesia
  • Ega Maulana Ditama (2) Information System, STMIK Nusa mandiri, Jakarta, Indonesia
  • Tuslaela Tuslaela (3) Information System, STMIK Nusa mandiri, Jakarta, Indonesia

  • (*) Corresponding Author
Keywords: Diabetes Mellitus, Forward Chaining, Expert Systems, Health, Disease detection

Abstract

In recent years, the diabetes mellitus in Indonesia has become a health problem in the community because its population has increased 2-3 times faster than other countries. Diabetes prevalence in Indonesia ranks 4th highest in the world after China, India and the United States. People can prevent complications and premature death if they detect early symptoms of diabetes. However, people do not know that they are at risk of diabetes, not had knowledge about the symptoms of diabetes, complexity of the process diagnosis and the high cost of examinations. Therefore, we need an application that can provide the results of the type of diabetes and its management solutions as practiced by experts. The aim of this research is to develop an expert system for detection types of diabetes such as: type one diabetes, type two diabetes, neuropathy diabetes, diabetes retinopathy, and diabetes nephropathy. The object of this research is diabetes carried out in March to April 2019 in the Klinik Pratama Desa Putera. This study uses primary data from patients who had a history of diabetes at Klinik Pratama Desa Putra and secondary data in the form of literature, research journals, and data documents needed to compile this study. In addition, we generated a knowledge base using forward chaining. The test results show that the expert system meets the functional requirements and the system performance reaches an accuracy of 100%. This expert system helps people in Indonesia to detect diabetes early so that it can prevent complications.

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References

Andriyanto, I., & Santoso, E. (2017). Pemodelan Sistem Pakar Untuk Menentukan Penyakit Diabetes Mellitus Menggunakan Metode Naive Bayes Studi Kasus : Puskesmas Poncokusumo Malang. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer (J-PTIIK) Universitas Brawijaya, 2(2), 880–887.

Erawantini, F., Farlinda, S., & Wulandari, R. A. (2019). Perancangan Aplikasi Penentu Faktor Risiko Diabetes Melitus Tipe 2 Secara Dini Berbasis Web. Jurnal Kesehatan, 5(1), 30–33. https://doi.org/10.25047/j-kes.v5i1.48

Ginting, B. S., & Novriyeni, N. (2012). Perancangan Sistem Pakar Untuk Diagnosa Penyakit Diabetes Dengan Metode Forward Chaining. Jurnal Kaputama, 6(1), 33–40. https://doi.org/10.1017/CBO9781107415324.004

Harum, A., Larasati, T., & Zuraida, R. (2013). Hubungan Diet Serat Tinggi Dengan Kadar Hba1c Pasien Diabetes Melitus Tipe 2 DI RSUD DR.H. Abdul Moeloek Provinsi Lampung. Medical Journal of Lampung University, 2(4), 79–87.

Inayati, I., & Qoriani, H. F. (2016). Sistem Pakar Deteksi Penyakit Diabetes Melitus (DM) Dini Berbasis Android. Jurnal Link, 25(2), 10–15.

Mardiana, T., Ditama, E. M., & Tuslaela, T. (2019). Final Research Report: Expert System for Diagnosing Diabetes Mellitus with the Forward Chaining Method. STMIK Nusa Mandiri.

Ministry of Cooperatives Small and Medium Enterprises. (2015). Building cooperatives and SMEs as National Economic Resilience. 122.

Niswati, Z., Paramita, A., & Mustika, F. A. (2016). Aplikasi Fuzzy Logic dalam Diagnosa Penyakit Diabetes Mellitus pada PUSKESMAS di Jakarta Timur. Jurnal Nasional Teknologi Dan Sistem Informasi, 2(3), 21–30. https://doi.org/10.25077/teknosi.v2i3.2016.21-30

Raditiya, B., & Aditya, M. (2016). Penatalaksanaan Diabetes Melitus Tipe 2 dengan Hiperkolesterolemia pada Seorang Pria Usia 60 Tahun dengan Pendekatan Kedokteran Keluarga Family Medicine Approach Management of 60 Years Old Man with Diabetes. Medula Unila, 5(2), 9–17.

Riadi, A. (2017). Penerapan Metode Certainty Factor Untuk Sistem Pakar Diagnosa Penyakit Diabetes Melitus Pada RSUD Bumi Panua Kabupaten Pohuwato. ILKOM Jurnal Ilmiah, 9(3), 309. https://doi.org/10.33096/ilkom.v9i3.162.309-316

Zubaedah, R. (2017). Penerapan Case Based Reasoning Untuk Diagnosis Diabetes Mellitus. Jurnal Ilmiah Mustek Anim Ha, 6(2), 224–235.

Published
2020-03-16
How to Cite
Mardiana, T., Ditama, E., & Tuslaela, T. (2020). AN EXPERT SYSTEM FOR DETECTION OF DIABETES MELLITUS WITH FORWARD CHAINING METHOD. Jurnal Riset Informatika, 2(2), 69-76. https://doi.org/10.34288/jri.v2i2.121
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