Implementasi Metode Case Based Reasoning Untuk Mendeteksi Kerusakan Televisi

 (*)Sursih Wulandari Mail (Universitas Labuhan Batu, Rantauprapat, Indonesia)
 Marnis Nasution (Universitas Labuhan Batu, Rantauprapat, Indonesia)
 Mustafa Haris Munandar (Universitas Labuhan Batu, Rantauprapat, Indonesia)

(*) Corresponding Author



The process of deteriorating television should indeed be done by an expert who is a television expert himself, but because television is a tool that is no longer common for people to know him, many people also have television in their respective homes. Even for television repairs, it is quite expensive, so some people who have televisions can do television maintenance at home. The lack of knowledge possessed by the community can lead to wrong handling of television maintenance / maintenance and this has a fatal impact. Hopefully the existence of this system can help the community in diagnosing the damage to their televisions. In that case they need not bother to call for repairmen or bring in a television repair shop. Here the authors provide solutions to solve the problems that often arise on television. In this study, it discusses how to care for television officers. The research objective is to analyze a desktop-based expert system program that contains the knowledge of an expert / doctor whose truth is believed to have the ability to be able to diagnose the disease from the symptoms of damage that has been damaged by television damage quickly and precisely. The stages of research carried out in this study include literature study, data collection, system design, system creation, system testing. Case Based Reasoning is a method used to build a knowledge-based system. The source of system knowledge is obtained by collecting the handling of cases by an expert / expert. Therefore, many problems in television damage are usually due to the negligence of the television owner himself. The first step in solving a problem is by first identifying the scope of the problem to be resolved, this also applies to any Artificial Intelligence (AI) programming. The results obtained in the study for the diagnosis of conjunctivitis were the value of old cases and new cases which obtained a high weight value, namely 1 from the third case


Diagnosis; Case Based Reasoning; Damage; Expert System; Television

Full Text:


Article Metrics

Abstract view : 159 times
PDF - 35 times


M. Arifin, S. Slamin, and W. E. Y. Retnani, “Penerapan Metode Certainty Factor Untuk Sistem Pakar Diagnosis Hama Dan Penyakit Pada Tanaman Tembakau,” Berk. Sainstek, vol. 5, no. 1, p. 21, 2017.

T. E. Putri, D. Andreswari, and R. Efendi, “Implementasi Metode CBR (Case Based Reasoning) dalam Pemilihan Pestisida terhadap Hama Padi Sawah Menggunakan Algoritma K-Nearest Neighbor (KNN) (Studi Kasus Kabupaten Seluma),” J. Rekursif, 2016.

M. Syahrizal and H. Haryati, “Perancangan Aplikasi Sistem Pakar Deteksi Kerusakan Mesin Alat Berat (Beko) Dengan Menerapkan Metode Teorema Bayes,” J. MEDIA Inform. BUDIDARMA, 2018.

C. Cubfritua, F. A. Sianturi, and A. Gea, “Sistem Pakar Untuk Mendiagnosa Pertumbuhan Gigi Balita Dengan Menggunakan Metode Dempster Shaper,” J. ARMADA Inform., 2018.

Minarni and A. Fadhillah, “Expert System in Detecting Rice Plant Diseases,” J. Dyn., vol. 2, no. 1, pp. 11–15, 2017.

B. Sinaga, P. M. Hasugian, and A. M. Manurung, “Sistem Pakar Mendiagnosa Kerusakan Smartphone,” vol. 3, no. 1, pp. 333–339, 2018.

S. Murni and F. Riandari, “Penerapan Metode Teorema Bayes Pada Sistem Pakar Untuk Mendiagnosa Penyakit Lambung,” J. Teknol. dan Ilmu Komput. Prima, 2018.

P. Ananta Dama Putra, I. K. Adi Purnawan, and D. Purnami Singgih Putri, “Sistem Pakar Diagnosa Penyakit Mata dengan Fuzzy Logic dan Naïve Bayes,” J. Ilm. Merpati (Menara Penelit. Akad. Teknol. Informasi), 2018.

F. A. Sianturi, “Implementasi Metode Certainty Factor Untuk Diagnosa Kerusakan Komputer,” MEANS (Media Inf. Anal. dan Sist., vol. 4, no. 2, pp. 176–184, 2019.

T. Syahputra and J. Halim, “Sistem Pakar Untuk Mendiagnosa Penyakit Menular Seksual ( HIV / AIDS ) Dengan Menggunakan Metode Case Based Reasoning ( CBR ),” J. Sains dan Komput., 2019.

S. Salamun, “Penerapan Algoritma Nearest Neighbor dan CBR pada Expert System Penyimpangan Perilaku Seksual,” J. Online Inform., 2018.

A. Annisa, T. Tursina, and H. S. Pratiwi, “Diagnosis Kerusakan Komputer Menggunakan Metode Similarity Jaccard Coefficient,” vol. 5, no. 2, pp. 104–108, 2017.


M. Syahrizal, R. Irwanti, and M. Sayuthi, “Sistem Pakar Diagnosa Penyakit Zika Dengan Menerapkan Metode Case Base Reasoning,” J. Ris. Komput., vol. 5, no. 3, pp. 240–246, 2018.

R. Avrizal, “Sistem Pakar Mendiagnosa Penyakit Flu Babi Menerapkan Metode Hybrid Case Based,” J. Ris. Komput., vol. 6, no. 2, pp. 204–210, 2019.

Bila bermanfaat silahkan share artikel ini

Berikan Komentar Anda terhadap artikel Implementasi Metode Case Based Reasoning Untuk Mendeteksi Kerusakan Televisi


  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

STMIK Budi Darma
Sekretariat : Jln. Sisingamangaraja No. 338 Telp 061-7875998
email :

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.