Defni Defni
Jurusan Teknologi Informasi Politeknik Negeri Padang

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Implementasi Sistem Pakar Untuk Diagnosis Penyakit Tomat: Pendekatan Backward Chaining Berbasis Web Wijaya, Taruma Leo; Fryonanda, Harfebi; Mardiah, Ainil; Defni, Defni; Ibrahim, Roy
Building of Informatics, Technology and Science (BITS) Vol 6 No 1 (2024): June 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i1.5371

Abstract

This study aims to implement an expert system using a web-based backward chaining method approach to help farmers diagnose and manage tomato plant diseases. This study was conducted because diagnosing plant diseases requires the help of agricultural experts, which causes problems with consultation costs and farmers who have difficulty knowing the type of disease in tomato plants will cause losses for farmers due to crop failure. The methodology used in this study is the prototype method which begins with identifying problems through data collection from literature, interviews with agricultural experts, and field observations. The collected data is then analyzed using the backward chaining method to trace symptoms to the cause of the problem and provide recommendations for handling. This system is implemented in the form of a web application that facilitates access for farmers. The results of the study show that this expert system is able to provide accurate and reliable diagnoses and recommendations with an accuracy level of this study of 85%. Thus, this expert system is expected to improve farmers' knowledge and skills in managing tomato plants, as well as contribute to increasing yields and the quality of agricultural products
Classification of Population Data of Nagari Based on Economic Level Using The K-Nearest Neighbor Method Mardiah, Ainil; Defni, Defni; Lestari, Aster Happy; Junaldi, Junaldi; Ritmi, Titin
International Journal of Advanced Science Computing and Engineering Vol. 6 No. 1 (2024)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/ijasce.6.1.191

Abstract

The process of collecting data and classifying the level of economic status of the residents of Nagari is currently manual, so the efficiency in data collection is less than ideal. As a result, the population of Nagari is not well controlled by government authorities due to the lack of detailed government supervision. Therefore, a classification application system is needed that can overcome these problems. In making a classification application system, it will be analyzed using the K-Nearest Neighbor method for grouping the economic level of the community, where data from each occupant of Nagari is used as criteria. It is hoped that this classification application can facilitate the grouping of the economic class of the population, so that the regent of village can make decisions on assistance from the system.