Implementation of Expert System for Diabetes Diseases using Naïve Bayes and Certainty Factor Methods

Muhammad Ilham Insani, Alamsyah Alamsyah, Anggyi Trisnawan Putra

Abstract


Expert Systems is a computer systems that has been entered the base knowledge and a set of rules used to solve problems like an expert. Methods that can be used in the expert systems which is Naïve Bayes and Certainty Factor. Naïve Bayes method can handle quantitative calculations and discreate data and only requires a little research data to estimate the parameters needed in the clasification and Certainty Factor which is suitable for measuring something whether it is certain or not in diagnosing. Diabetes is one of the most frequent diseases suffered in Indonesia. The purpose of this research is implementation expert systems used Naïve Bayes and Certainty Factor in diagnosing diabetes and knowing the level of accuracyof the systems. Data that is used by researchers as much 100 data medical record, obtained from the medical record RSUD Bendan Kota Pekalongan. The variabels used in this research is age, gender, the symptoms of the desease diabetes and result diagnose desease from expert. The accuracy rate of this system derived from the scenario distribution data 70 training data and 30 testing data that is equal to 100% according to the doctor's diagnosis.


Keywords


Expert Systems, Disease Diabetes, Naïve Bayes, Certainty Factor.

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References


Hustinawaty & Aprianggi R. (2014). The Development of Web Based Expert System for Diagnosing Children Diseases Using PHP and MySQL. International Journal of Computer Trends and Technology (IJCTT), 10(4): 197-202.

Naik, M.V. & Lokhanday S. (2012). Building a Legal Expert System for Legal Reasoning in Specific Domain-A Survey. International Journal of Computer Science & Information Technology (IJCSIT), 4(5): 175.

Pramesti, A.A., Arifudin R., & Sugiharti E. (2016). Expert System for Determination of Type Lenses Glasses using Forward Chaining Method. Scientific Journal of Informatics, 3(2): 177.

Kusumadewi, S. (2003). Artificial Intelligence (Teknik dan Aplikasinya). Yogyakarta: Graha Ilmu.

Setyabudi, W.U., Sugiharti E., & Arini F.Y. (2017). Expert System Diagnosis Dental Disease Using Certainty Factor Method. Scientific Journal of Informatics, 4(1): 44.

Josephine, M.S. & Jeyabalaraja V. (2012). Expert System and Knowledge Management for Software Developer in Software Companies. International Journal of Information and Communication Technology Research, 3(2): 243.

Muslim, M.A., Kurniawati I., & Sugiharti E. (2015). Expert System Diagnosis Chronic Kidney Disease Based on Mamdani Fuzzy Inference System. Journal of Theoretical and Applied Information Technology, 78(1): 70.

Prayoga, ND., Hidayat N., & Dewi RK. 2017. Sistem Diagnosis Penyakit Hati Menggunakan Metode Naïve Bayes. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2 (8): 2666-2671.

Ferdiansyah, W. R., Muflikhah, L., & Adinugroho. (2018). Sistem Pakar Diagnosis Penyakit Pada Kucing Menngunakan Metode Naive Bayes dan Certainty Factor. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2(2): 451-458.

Suprayogi, AA., Hidayat, N., & Fanani, L. (2018). Sistem Pakar Diagnosis Penyakit Kucing Menggunakan Metode Naïve Bayes – Certainty Factor Berbasis Android. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2(2): 650-658.

Han, J., Kamber, M., & Pei, J. (2012). Data Mining: Concepts and Techniques(3nd ed). Waltham: Morgan Kaufmann.

Kusrini., (2008). APLIKASI SISTEM PAKAR. Menentukan Faktor Kepastian Penggunadengan Metode Kuantifikasi Pertanyaan.Yogyakarta: Andi.

American Diebetes Association (ADA). (2014). Diagnosis and Classification of Diabetes Mellitus. Diabetes Care, 37(1): 2-4.

Darmono, dkk. (2007). Naskah lengkap diabetes melitus di tinjau dari berbagai aspekpenyakit dalam . Semarang: Badan penerbit universitas Diponegoro

Olson & Delen. (2008). Advanced Data Mining Techniques. USA: Springer- Verlag Berlin Heidelberg.

Sutojo. (2010). Kecerdasan Buatan. Yogyakarta: Penerbit Andi.




DOI: https://doi.org/10.15294/sji.v5i2.16143

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