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All Journal METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi
Jeremia Sebayang
Universitas Methodist Indonesia
Computer Science & IT Economics, Econometrics & Finance

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KLASIFIKASI PENYAKIT BAWANG MERAH MELALUI CITRA DAUN DENGAN METODE K-MEANS Darwis Robinson Manalu; Jeremia Sebayang; Harlen Gilbert Manullang
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 7 No. 1 (2023): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol7No1.pp150-157

Abstract

Shallot production is threatened by a number of diseases resulting in quite large losses and causing a decrease in shallot quality. One of the main diseases that attack shallots is purple spot disease and another common disease on shallots is lanas. Therefore it is necessary to classify the diseases of shallots in order to know the type of disease that attacks shallots. Shallot disease can be seen from the shape of the leaves and the texture of the leaves is the most appropriate feature used in the identification of shallot disease. However, the various forms of shallots are not easy for humans to detect, especially for ordinary farming communities. Therefore, technology can help detect shallot disease through leaf texture with the K-Means method using matlab. Based on the results of the identification test with test data as many as 20 images managed to get an accuracy value of 80%, where this accuracy value can be said to be good
Co-Authors Darwis Robinson Manalu Harlen Gilbert Manullang