Klasifikasi Tanaman Rempah Jenis Rimpang dengan Menggunakan Metode Random Forest pada Android

Abstract

Indonesia is one of the tropical countries rich in spices, commonly found in daily life, one of which is rhizomes. Rhizomes are a type of spice plant with stems that grow horizontally underground and produce new shoots at their nodes. This research aims to develop a mobile application capable of providing information about the classification of rhizome-type spice plants. The study used image processing techniques with the random forest method to classify rhizome types. The dataset consists of 1,000 images representing 10 types of rhizomes, with 700 images used as training data and 300 images as test data. The results of the study show that the random forest algorithm can deliver good performance in classifying rhizome types, achieving an accuracy of 80% based on 30 test images. The testing process was conducted twice by users.