EXPERT SYSTEM FOR DIAGNOSIS OF BONE DISEASE USING CASE-BASED REASONING METHOD

Authors

  • Amarul Ahmad

    Program Studi Teknik Informatika, Fakultas Teknik, Universitas Khairun Jl. Jati Metro, Kota Ternate Selatan , Program Studi Teknik Informatika, Fakultas Teknik, Universitas Khairun Jl. Jati Metro, Kota Ternate Selatan

  • Hairil Kurniadi Sirajuddin

    Program Studi Teknik Informatika, Fakultas Teknik, Universitas Khairun Jl. Jati Metro, Kota Ternate Selatan , Program Studi Teknik Informatika, Fakultas Teknik, Universitas Khairun Jl. Jati Metro, Kota Ternate Selatan

  • Rosihan

    Program Studi Teknik Informatika, Fakultas Teknik, Universitas Khairun Jl. Jati Metro, Kota Ternate Selatan , Program Studi Teknik Informatika, Fakultas Teknik, Universitas Khairun Jl. Jati Metro, Kota Ternate Selatan

DOI:
https://doi.org/10.33387/jati.v1i1.36
Keywords:
Expert System, Bone Disease, Case Based Reasoning Method
Abstract

This research focuses on the implementation of Case-Based Reasoning for an expert system for diagnosing bone diseases. It takes data in the form of types of bone disease, and the symptoms of each type of bone disease. After that, the calculation is carried out using the CBR method, where the symptoms selected by the patient will be considered as new cases, then a match is made between the symptoms of the new cases and the symptoms of the old cases that have been stored in the database, if the symptoms of the new case are the same as the symptoms of the old case, then it is given a value of 1, if it is not the same, then it is given a value of 0, then a calculation is made between the match value and the weight value of each symptom, the result of the calculation is the value of the level of similarity between the new case and the old case, the old case that has the highest similarity value will be taken to be used in solving the problems experienced by the patient. In making the expert system, the CBR method uses the PHP programming language for website creation and MySQL for database management. The system built is web-based, this research was conducted through literature reviews and direct interviews. The result is the disease suffered by the patient and the treatment solution.

References

A. Herlina., V. A. Setiawan., R. T. Prasetio. 2018. ”Penerapan Inferensi Backward Chaining Pada Sistem Pakar Diagnosa Awal Penyakit Tulang” Jurnal Informatika. Vol 5. No 1. pp. 50-60

Kemenkes RI. 2020. ”Infodatin Osteoprosis 2020” Available At: [https://pusdatin.kemkes.go.id/resources/downl oad/pusdatin/infodatin/Infodatin-Osteoporosis- 2020] diakses 3 Mei 2021

M. Salmin. 2018. ”Case Based Reasoning untuk diagnosa penyakit Infeksi Saluran Pernapasan Akut” JIKO (Jurnal Informatika dan Komputer) Ternate. Vol 2. No 1.

M. Papuangan., M. Salmin. 2020. ”Penggunaan Algoritma Nearest Neighbor Pada Sistem Penalaran Berbasis Kasus Untuk Diagnosis Penyakit ISPA” Serambi Engineering. Vol 5. No 1. pp. 883-892

S. K. Pal., S. C. K. Shiu. 2004. ”Fondation of Soft Case-Based Reasoning. John Willey and Sons, Inc. New Jersey.

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Published
2022-12-30
Issue
Vol. 1 No. 1: DESEMBER 2022 - MEI (2023)
Section
Artikel
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How to Cite

EXPERT SYSTEM FOR DIAGNOSIS OF BONE DISEASE USING CASE-BASED REASONING METHOD. (2022). Jurnal Jaringan Dan Teknologi Informasi, 1(1). https://doi.org/10.33387/jati.v1i1.36

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