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Obedh Eliezer Sidauruk
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Computer Science & IT Library & Information Science

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leman, D Deteksi Penyakit Pada Daun Pisang dengan Penggunakan Algoritma Local Binary Pattern Dan K-Nearest Neighbor Dedi Leman; Obedh Eliezer Sidauruk
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 3 No. 2 (2024): Mei 2024
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v3i2.134

Abstract

Bananas are a type of fruit that has high production and is liked by many people. Mango productivity fluctuates from year to year. This is due to fluctuations in harvest area, plants that have not produced optimally, climate disturbances and attacks by various pests and diseases which are factors inhibiting banana growth and production in Indonesia. This identification will take a relatively long time and produce various diseases on banana leaves because humans have visual limitations in identifying, the level of fatigue and differences in opinion about diseases on banana leaves. The process of recognizing leaf patterns can be done by recognizing the characteristics of leaf structures such as leaf shape and texture. The method used in this research is Local Binary Pattern, an algorithm that can be used to classify based on images. In this study, 4 types of banana leaf diseases were used. Based on the results of the accuracy test, an accuracy value of 90.5% was obtained for the disease detection process on banana leaves for 10 pieces of data.
Co-Authors Leman, Dedi