Analisa Dan Perancangan Sistem Pakar Identifikasi Penyakit Diabetes Pada Remaja Dengan Metode Fuzzy Berbasis Website

Hatta Agus Hairul; Hidayatullah Al Islami

Authors

Hatta Agus Hairul Universitas Pamulang
Hidayatullah Al Islami Universitas Pamulang

Keywords:

Expert System, Identification, Diabetes in Adolescents, Tsukamoto's fuzzy logic

Abstract

At this time many teenagers are at risk of diabetes, according to data from IDAI (Ikatan Dokter Anak Indonesia) which states that the number of diabetes that occurs in children and adolescents in Indonesia in the age range 0-18 years has increased by 700% in a period of 10 years. From September 2009 to September 2018 there were 1213 cases of diabetes in children and adolescents. To overcome this problem, an Expert System is needed to identify diabetes based on a website using the fuzzy method as a source of information and as an alternative to consult so that the risk of diabetes can be known from an early age so that can reduce the number of diabetics. The Tsukamoto fuzzy method was chosen because it has a fairly high level of accuracy and is easy to apply. In his inference, the Tsukamoto method has several stages, namely: fuzzification, formation of a knowledge base or rules, inference engine, and defuzzification. In determining the identification of diabetes risk, it is determined based on 4 input variables, namely: medical history, diet, lifestyle, and understanding and health checks. Each variable has several questions, each question has several choices where each choice has a weighted value. The data was obtained from interviews with doctors and based on related literature studies. This research can make it easier to determine the results of diabetes risk decisions in adolescents and get solutions for handling and preventing them with an accuracy rate of 81.5%.

References

Andini, A., & Awwalia, E. S. (2018). Studi Prevalensi Risiko Diabetes Melitus Pada Remaja Usia 15–20 Tahun Di Kabupaten Sidoarjo. Medical and Health Science Journal, 2(1), 19–22.

dr. Widharto. (2018). Kencing Manis (Diabetes) (Edisi Pertama). PT. Sunda Kelapa Pustaka.

Fitriana, S., & Kristania, Y. M. (2021). Perancangan Sistem Informasi Klinik Hewan Berbasis Android. EVOLUSI: Jurnal Sains Dan Manajemen, 9(2).

Marpaung, J. Y., Ginting, G. L., & Silalahi, N. (2020). Penerapan Metode Fuzzy Tsukamoto Dalam Penentuan Harga Laptop Bekas. Building of Informatics, Technology and Science (BITS), 2(2), 115–126.

Mulyono, I. U. W., Kusumawati, Y., Susanto, A., & Ihyaâ, D. I. (2021). E-Sistem Pakar Diagnosa Dini Penyakit Diabetes Menggunakan Metode Fuzzy Tsukamoto. Prosiding Seminar Nasional Lppm UMP, 2, 515–522.

Naomi, M. (2019). Analisa Dan Perancangan Sistem Pengaduan Mahasiswa Berbasis Web (Studi Kasus: Universitas Mercu Buana Kranggan). JUSIBI (Jurnal Sistem Informasi Dan E-Bisnis), 1(5).

P, N., Arianto, F. S. D., & Firgia, L. (2022). Teori Dan Aplikasi ARTIFICIAL INTELLIGENCE Studi Kasus Menggunakan Pemrograman Web. Uwais Inspirasi Indonesia. https://books.google.co.id/books?id=5ZOjEAAAQBAJ

P2PTM Kemenkes RI. (2018, October 31). Anak Juga Bisa Diabetes. P2PTM Kemenkes RI.

Prasetya, A. F., Sintia, S., & Putri, U. L. D. (2022). Perancangan Aplikasi Rental Mobil Menggunakan Diagram UML (Unified Modelling Language). Jurnal Ilmiah Komputer Terapan Dan Informasi, 1(1), 14–18.

Sugiono, S., & Junior, A. (2022). Klasifikasi Sistem Pakar Untuk Mendiagnosa Penyakit Diabetes Menggunakan Metode Fuzzy Sugeno. Jurnal Pendidikan Dan Konseling (JPDK), 4(5), 766–773.

Widodo, Y. B., Anggraeini, S. A., & Sutabri, T. (2021). Perancangan Sistem Pakar Diagnosis Penyakit Diabetes Berbasis Web Menggunakan Algoritma Naive Bayes. J. Teknol. Inform. Dan Komput, 7(1), 112–123.