Febriana, Trissa Noor Aulia
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Klasifikasi Tingkat Kematangan Buah Pisang Raja Menggunakan Metode CNN Berbasis Android Febriana, Trissa Noor Aulia; Lusiana, Veronica
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 1 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i1.37790

Abstract

Raja banana (Musa paradisiaca L.) is a banana cultivar commonly enjoyed in Indonesia. In addition to being consumed as a fresh fruit, Pisang Raja is often processed into various banana-based foods, such as banana chips, fried bananas, banana fritters, and other banana products. For farmers, post-harvest sorting of Pisang Raja requires a significant amount of time and effort. Therefore, a system is needed to assist farmers and the community in general to determine the ripeness level of Pisang Raja fruit more efficiently and clearly. The classification process of Pisang Raja fruit ripeness levels is carried out through precision calculations in a system, using a dataset consisting of 300 images covering 3 types of Pisang Raja ripeness levels. The classification process for the ripeness levels of Pisang Raja fruit utilizes the Convolutional Neural Network (CNN) method with the TensorFlow module for training and testing data. Based on experimental results, the accuracy in classifying the ripeness levels of Pisang Raja fruit reaches a value of 95%."