RANCANG BANGUN APLIKASI PREDIKSI JENIS DAN TINGKAT KEMATANGAN BUAH PISANG MENGGUNAKAN METODE WATERFALL DAN MOBILENET V3 BERBASIS ANDROID

Muhammad Hykal Nurhakim, . (2025) RANCANG BANGUN APLIKASI PREDIKSI JENIS DAN TINGKAT KEMATANGAN BUAH PISANG MENGGUNAKAN METODE WATERFALL DAN MOBILENET V3 BERBASIS ANDROID. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

Bananas are one of the horticultural commodities with the highest consumption and production rates in Indonesia, thus requiring supporting technology to accurately identify their type and ripeness. This study aims to develop an Android application named BanaScan, which can predict the type and ripeness of bananas using the Convolutional Neural Network (CNN) algorithm with the MobileNet V3 Large architecture. The model was developed using a transfer learning approach and integrated into the Android application through TensorFlow Lite. The development process was carried out using the Waterfall method and applied the MVVM architecture on the software side. The evaluation results showed that the model achieved an accuracy of 88% in predicting the type of banana and 96% in predicting the ripeness level. Meanwhile, the User Acceptance Testing (UAT) with 20 respondents resulted in a user satisfaction rate of 92.6%. This application is expected to be a practical and efficient solution for both industry players and consumers to quickly assess the quality of bananas through Android devices.

Item Type: Thesis (Skripsi)
Additional Information: [No.Panggil: 2110511024] [Pembimbing 1: Ridwan Raafi'udin] [Pembimbing 2: Catur Nugrahaeni Puspita Dewi] [Penguji 1: Jayanta] [Penguji 2: Muhammad Adrezo]
Uncontrolled Keywords: Banana, Android, Convolutional Neural Network (CNN), MobileNet V3 Large, User Acceptance Testing (UAT).
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User: MUHAMMAD HYKAL NURHAKIM
Date Deposited: 07 Aug 2025 01:29
Last Modified: 07 Aug 2025 01:29
URI: http://repository.upnvj.ac.id/id/eprint/37361

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