Bil Qisthi, Imam
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Classification of nutmeg ripeness using artificial intelligence Bil Qisthi, Imam; Siswono, Hartono
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i2.pp2441-2450

Abstract

Nutmeg seeds can produce a lot of oil if they have optimal maturity. In other words, they have little moisture content. Based on observations made at one of the refineries in Sukabumi, farmers do not pay attention to the maturity level of nutmeg seeds after drying which can cause a decrease in the quality of nutmeg seeds and the quality of the oil produced. This study aims to make it easier for nutmeg farmers to classify the maturity of nutmeg seeds. This study used the convolutional neural network (CNN) method to help with classification problems and several image processing methods. This program will be run through an Android application. When the application containing this CNN model is run, the camera system will turn on, and the program will classify in real-time nutmeg objects into 1 of 3 class labels namely LowQuality, MidQuality, or HighQuality class labels classifying. The results will be displayed on the application screen, the results are displayed in the form of class names and scores. The results of CNN model training accuracy are 97.92%.