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All Journal Knowbase : International Journal of Knowledge in Database Jurnal Teknologi dan Komunikasi Pemerintahan
Titis Sari Putri
Institut Pemerintahan Dalam Negeri
Computer Science & IT Social Sciences

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Journal : Knowbase : International Journal of Knowledge in Database

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Application of Case Based Reasoning Using The K-Nearest Neighbor Algorithm in an Expert System for Diagnosing Pests and Diseases of Sugarcane Plants Andi Maulidinnawati Abdul Kadir Parewe; Mursalim Mursalim; Titis Sari Putri; Hermawati Hermawati
Knowbase : International Journal of Knowledge in Database Vol 2, No 2 (2022): December 2022
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v2i2.5959

Abstract

Sugarcane pests and diseases are still diagnosed manually, which can lead to errors such as data loss or inaccurate data. The goal of this research is to develop an expert system for identifying plant pests and diseases that affect sugarcane yield and quality. This data was obtained through literature study, observation, and interviews. The Case Based Reasoning method is used to find cases by comparing previous cases with recent cases using similarity calculations with the K-Nearest Neighbor algorithm to find the best solution from the identified cases. The results of this study indicate that the expert system for diagnosing sugarcane pests and diseases is easy to use, the appearance is easy to reach, and the diagnostic process does not take a long time. Based on testing the accuracy of the system to diagnose according to the expert's mind, it got an accuracy of 96% from 50 cases tested with the system and got a percentage result of 87.33% from 10 respondents including very feasible criteria.
Co-Authors Andi Maulidinnawati Abdul Kadir Parewe Hermawati Hermawati Mursalim Mursalim Wenty Zahrati