Sistem Pakar Untuk Mendeteksi Penyakit Mata Menerapkan Metode Case Based Reasoning

Abstract

The problem that is often faced by the general public is the difficulty of knowing the occurrence of eye disease in humans because it is caused by different symptoms, so if the eye is disturbed and we ignore it, it could be an early symptom of eye disease that can be fatal. Given that experts and practice hours are limited, so that patients cannot consult experts anytime and anywhere, an expert system is needed. The existence of an expert system can solve problems that occur because the expert system uses an appropriate method. In the expert system, the method used to diagnose an eye disease is the Case Based Reasoning (CBR) method, which is a reasoning process for a previous similar case. In the experiment, it is proven by looking for the level or value of the new case data approach with the old case data data for reference in making decisions on new cases. Therefore, the authors build an expert system application to diagnose disease. In this system the inference used is Case Based Reasoning because the process is carried out to recognize the disease and its symptoms and early characteristics of the disease. The development of this web-based system uses the PHP and Mysql programming languages ​​as the database. This expert system can represent an expert in the field of eye disease to find out eye diseases based on existing characteristics and symptoms and can provide solutions if there are diseases suffered by patients

Case Based Reasoning Untuk Diagnosa Penyakit Gigi Berbasis Web

“…Metode pemecahan masalah yang disebut Case Based Reasoning (CBR) adalah penggunaan pengalaman dari kasus-kasus sebelumnya untuk memecahkan masalah yang baru muncul [8]. Konsep dasar CBR ialah bahwa dalam menghadapi suatu masalah baru, sistem mencari kasus serupa yang pernah terjadi sebelumnya, kemudian menggunakan solusi yang diterapkan pada kasus-kasus tersebut untuk menyelesaikan masalah baru [9,10].…”

Analisa Perbandingan Metode Teorema Bayes Dan Case Based Reasoning Diagnosa Penyakit Pada Tanaman Tomat

“…Kualitas basis data kasus memiliki dampak signifikan pada kinerja CBR, dan jenis serta volume data yang disimpan perlu diperhatikan. Selama pengambilan kasus sebelumnya, tingkat kesamaan antara kasus baru dan yang ada akan dihitung menggunakan fungsi kesamaan untuk menentukan kesamaan atau perbedaan [23]. Nilai kesamaan dihitung dengan rumus berikut: (7) Keterangan: S menunjukkan similarity (tingkat kesamaan) dengan skala 1 (identik) dan 0 (berlainan) W mengindikasikan Weight (bobot yang diberikan.…”