Implementasi Metode Case Based Reasoning Untuk Mendeteksi Kerusakan Televisi

Abstract

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

Pemodelan Warna Pada Dataset Baru Citra Bunga Lantana Camara Menggunakan Algoritma Yolov5

“…Variabel ini didasarkan pada hasil prediksi dan observasi aktual: true positive (TP), true negative (TN), false positive (FP), dan false negative (FN) [ (3) d) Mean Average Precision (mAP): Rata-rata dari average precision (AP) untuk semua kelas objek. mAP yang tinggi menunjukkan model yang baik dalam deteksi dan lokalisasi objek pada gambar [34]:…”

Aplikasi Deteksi Pelanggaran Merokok di Tempat Larangan Merokok

“…Dari penelitian tersebut didapatkan hasil bahwa sistem dapat mendeteksi rokok dengan tingkat akurasi deteksi tertinggi pada jarak 1meter dengan persentase 99,03% dan pada jarak 5 meter sistem sama sekali tidak dapat mendeteksi objek rokok. (Harun et al, 2023). Hal ini seperti hasil pada penelitian ini bahwa jarak 1 meter memiliki akurasi tertinggi.…”

Sistem Pakar Dalam Mendeteksi Kerusakan Televisi

“…Permasalahan tersebut dikarenakan faktor ketidaktahuan pengguna dalam penanganan televisi yang rusak (Wulandari et al, 2021). Dari permasalahan tersebut maka dibutuhkan suatu sistem pakar yang dapat mendeteksi kerusakan televisi berdasarkan tanda-tanda kerusakan yang ada.…”