Segmentasi Kematangan Buah Kopi Berdasarkan Kemiripan Warna dengan Algoritma K-Means: Coffee Fruit Ripeness Segmentation Based on Color Similarity Using the K-Means Algorithm

Nurhalijah Berutu; Sriani Sriani

doi:10.57152/malcom.v6i4.3334

Authors

Nurhalijah Berutu Universitas Islam Negeri Sumatera Utara
Sriani Sriani Universitas Islam Negeri Sumatera Utara

DOI:

https://doi.org/10.57152/malcom.v6i4.3334

Keywords:

Buah Kopi, Kematangan, Kemiripan Warna, K-Means, Segmentasi

Abstract

Penilaian kematangan buah kopi secara manual bersifat subjektif karena pencahayaan yang tidak merata, buah yang tertutup daun, dan banyaknya buah pada satu pohon, sehingga pohon yang masih didominasi buah mentah dapat ikut dipanen. Penelitian ini menerapkan K-Means pada nilai RGB piksel untuk menyegmentasi buah kopi Arabika menjadi kategori mentah, setengah matang, dan matang, lalu mengagregasi empat sisi setiap pohon menjadi keputusan panen. Kontribusinya adalah keputusan tingkat pohon yang menggabungkan tiga klaster dengan agregasi empat sisi, disertai analisis kestabilan keputusan tersebut. Data berupa 32 citra dari delapan pohon. Citra dipotong secara manual, diubah ukurannya menjadi 1600 × 1600 piksel, dan dikelompokkan dengan K = 3 di MATLAB. Pohon dinyatakan layak panen jika rata-rata persentase setengah matang dan matang mencapai 60%. Lima pohon layak panen (empat setengah matang, satu matang) dan tiga pohon belum layak. Simpangan baku rata-rata antarsisi 10,14 poin persentase, tiga pohon berada dalam 1,6 poin dari ambang, dan penghilangan satu sisi mengubah keputusan tiga pohon. Validasi dilakukan secara visual tanpa data acuan berlabel, sehingga akurasi segmentasi belum terukur.

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