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All Journal OKTAL : Jurnal Ilmu Komputer dan Sains
Alvin Diaz Setiadi
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Astronomy Chemistry Computer Science & IT Electrical & Electronics Engineering Social Sciences

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Pendekatan Decision Tree Untuk Klasifikasi Penyakit Pada Tanaman Kopi Altaf Ghani Subekti; Alvin Diaz Setiadi; Muhammad Agung Zikri; Ryandanu Wisnu Pradipta
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 3 No 10 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

Coffee plants are an important commodity in the agricultural sector but are vulnerable to various diseases that can affect productivity and crop quality. To quickly and accurately identify and classify diseases in coffee plants, a technology-based approach is needed to assist farmers in decision-making. This study aims to evaluate the use of the Decision Tree algorithm as a classification method in detecting diseases in coffee plants. Through a Systematic Literature Review (SLR), we collected data from five relevant journals and analyzed the effectiveness of Decision Tree in the disease classification process. The results show that the Decision Tree approach can achieve high accuracy in identifying coffee plant diseases and is easy to implement in the field. This research is expected to provide further insights for the development of decision support systems to help coffee farmers improve plant health and productivity.
Co-Authors Altaf Ghani Subekti Muhammad Agung Zikri Ryandanu Wisnu Pradipta