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All Journal TIN: TERAPAN INFORMATIKA NUSANTARA
Cinantya Paramita
Universitas Dian Nuswantoro, Semarang
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Pengembangan Aplikasi Web Manajemen Tugas Akademik Berbasis Model View Controller untuk Efisiensi Waktu Mahasiswa Danendra Althaf Yuganfa; Reno Dwi Aderelyan; Daniel Aquaries Pratama; Arya Pradipta; Stephanus Abryan Agung Pratama; Cinantya Paramita
TIN: Terapan Informatika Nusantara Vol 6 No 9 (2026): February 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i9.8946

Abstract

The need for an information system capable of managing academic activities and schedules in an integrated manner is increasing in higher education environments. This is due to students often facing difficulties in managing their time efficiently and effectively. This study aims to develop a web-based task management application that is not only functional but also has a proven quality of experience. With features such as task recording, calendar, and real-time notifications. The development method is carried out using the Waterfall approach, starting from gathering requirements to system design that includes three main components, namely: Use Case Diagram, Entity Relationship Diagram, and Activity Diagram. The Implementation stage is supported by the Model View Controller (MVC) architecture to ensure that the development process runs efficiently and organized. Then, at the testing stage, Black Box Testing and User Acceptance Test (UAT) with the Mean Opinion Score (MOS) method are carried out to validate the system. The results of the study show that all functions run according to design, with the highest level of user satisfaction in terms of functionality and performance. The contribution of this study lies in the effectiveness of cloud-based real-time notifications which are proven to be superior in increasing user awareness compared to conventional methods, as well as the availability of time management solutions that are verified to have a high level of user acceptance.
Implementasi MobileNetV2 pada Aplikasi Mobile untuk Penilaian Objektif Kondisi Fisik Ponsel Bekas Azriel Sebastian Pamungkas; Justin Matthew Triono; Emanuel Pinesthi Widi Utomo; Cinantya Paramita
TIN: Terapan Informatika Nusantara Vol 6 No 9 (2026): February 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i9.8947

Abstract

The lack of attention to electronic waste (e-waste), particularly regarding mobile phones, has a serious impact on global environmental issues. One of the main obstacles in the economic circulation of these devices is the subjectivity and technical difficulty in accurately assessing the physical condition of used phones. This research aims to address these challenges through the development of a circular economy platform prototype based on a mobile application that provides objective and automated phone condition assessment services. The system is designed using React Native Expo and integrates the MobileNetV2 Deep Learning model via TensorFlow Lite. Transfer learning methods are applied to a dataset covering various mobile phone brands such as Samsung, Xiaomi, and OPPO to train the model to recognize physical damage on the screen and body. Test results indicate that the system is capable of providing objective assessment with high precision for devices in prime condition (Grade A) at 0.95. However, objectivity for severely damaged phones (Grade D) remains a challenge with a precision of 0.22 due to training data imbalance. Nevertheless, the application prototype successfully presents a transparent real-time scanning feature. This research contributes to providing a technical solution that bridges the trust gap through automated assessment standardization, thereby minimizing manual inspection subjectivity and promoting supply chain efficiency in the electronic circular economy.
Co-Authors Arya Pradipta Azriel Sebastian Pamungkas Danendra Althaf Yuganfa Daniel Aquaries Pratama Emanuel Pinesthi Widi Utomo Justin Matthew Triono Reno Dwi Aderelyan Stephanus Abryan Agung Pratama