Coconut Shell Charcoal Classification Model for Organic Raw Materials Using CNN

Coconut shell charcoal is the basic raw material for biomass briquette products obtained in Sulawesi, Indonesia and has high quality value. Quality briquette products require organic raw materials from Indonesian National Standard coconut shell charcoal. The research aims to design a classification model by sorting and selecting bad, poor, and good types of charcoal according to the fulfillment needs to produce briquette products. An approach based on artificial intelligence technology with deep learning methods through Convolution Neural Network (CNN) architecture. The classification model determines the qualities needed for the sustainability of companies, the industrial world and households. The research produced a classification model to obtain quality organic raw materials with a training accuracy value of 0.92 and validation accuracy of 0.88 so that the model can be used to detect coconut shell charcoal better and more accurately.