The Indonesian Journal of Computer Science
Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)

Diagnosis Penyakit Tanaman Kopi Robusta Menggunakan Metode Dempster Shafer Berbasis Sistem Pakar

Acihmah Sidauruk (Unknown)
Panggih Suseno (Unknown)
Budy Satria (Unknown)
Mulia Sulistiyono (Unknown)



Article Info

Publish Date
25 Jul 2024

Abstract

Robusta coffee is a coffee variety that has unique characteristics, a strong taste and a different level of bitterness from Arabica coffee because Robusta coffee contains lower sugar and 2.2% more caffeine than Arabica coffee so that Robusta coffee production is quite helpful for the economy. several coffee producing countries in the world. The quality and productivity of coffee plants can decrease due to several factors such as pests and disease. However, the limitations of experts regarding coffee plant diseases are a factor and obstacle. The aim of this research is to create an expert-based intelligent system to identify pests and diseases in robusta coffee plants. The method that will be applied is Dempster Shafer. Data on disease names amounted to 13 and data on symptoms amounted to 27. The final result was that Robusta coffee plants were tested for expertise on the system with an average accuracy of diagnosis results of 94% from 13 test cases on pests and diseases of coffee plants, so it can be concluded that the system Experts can diagnose coffee plant pests and diseases very well using the Dempster Shafer method

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Journal Info

Abbrev

ijcs

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering Engineering

Description

The Indonesian Journal of Computer Science (IJCS) is a bimonthly peer-reviewed journal published by AI Society and STMIK Indonesia. IJCS editions will be published at the end of February, April, June, August, October and December. The scope of IJCS includes general computer science, information ...