Detection of Katokkon Chili Maturity using Convolutional Neural Network with Transfer Learning Model DenseNet169

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Andi Baso Kaswar, Muhammad Ryan Ilham, Renisa Amalia Tahir, Abdul Muis Mappalotteng, Yasser Abdul Djawad, Dyah Darma Andayani

2023 IWAIIP 2023 - Conference Proceeding: International Workshop on Artificial Intelligence and Image Processing Conference paper Cited by 4 Quartile

Abstract

Chili is a plant that originates from America and is included in the Solonaceae and Capsicum genera. One type of chili that is included in the large chili category is Katokkon chili, commonly referred to as Toraja chili, which comes from the Tana Toraja district, South Sulawesi, Indonesia. Research related to the detection of fruit ripeness and quality has also been conducted. However, the research that has been conducted still uses relatively few images, and the accuracy needs to be improved. In addition, no research has discussed the detection of Katokkon chili maturity level using images or images of Katokkon chili fruit taken directly from the tree. Therefore, research was conducted with the title Detection of the Maturity Level of Katokkon Chili using the CNN pretrained DenseNet169 model method. In this study, the level of maturity of chili peppers was classified into three categories: raw chilies, half-ripe chilies, and ripe chilies. Based on the results of several tests that have been carried out, the best accuracy results are obtained in testing using the DenseNet169 method, with an accuracy of 95.03%, a loss value of 16.72%, a recall and specificity value of 95.03% and 97.51% respectively, a precision value of 95.03%, and an accuracy CF of 96.69%. This shows that the DenseNet169 method with a combination (Swish, Swish, and Adamax) can be considered the best choice for classifying or detecting the level of maturity of Toraja chili compared other methods that have been tested. © 2023 IEEE.

Affiliations

State University of Makassar, Department of Computer Engineering, Makassar, Indonesia; State University of Makassar, Department of Informatics and Computer Engineering, Makassar, Indonesia; State University of Makassar, Department of Electronics Engineering, Makassar, Indonesia