Penentuan Keakuratan Kelompok Data Gambar pada Proses Segmentasi Menggunakan Algoritma Random Forest

Salma N. Aini, Dian Puspita Hapsari, Aeri Rachman

Abstract


Abstrak. Sebagian besar metode segmentasi tradisional didasarkan pada intensitas dan hubungan spasial piksel, atau model terbatas yang ditemukan melalui pengoptimalan. Meskipun demikian, manusia menggunakan lebih banyak pengetahuan saat melakukan segmentasi manual. Oleh karena itu, dalam beberapa tahun terakhir, metode pembelajaran mesin yang dapat dilatih telah muncul sebagai alat yang ampuh untuk menyertakan sebagian dari pengetahuan tersebut dalam proses segmentasi dan meningkatkan akurasi wilayah berlabel. Pada paper ini dilakukan analisis untuk melihat seberapa akurat segmentasi gambar dengan menggunakan algoritma random forest. Dalam makalah ini akan diulas tentang hasil perbandingan kinerja algoritma random forest dengan algoritma J48, Naïve bayes, dan Logistic regression. Hasil perbandingan dari beberapa algoritma tersebut Random Forest memiliki keakuratan tertinggi 97.7%.


Keywords


kecerdasan buatan, segmenting, random forest.

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DOI: https://doi.org/10.31284/p.snestik.2023.4156

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