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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) IJoICT (International Journal on Information and Communication Technology)
Satrio, Cahyo Tri
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Computer Science & IT Education

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The Re-development of Proxsis Workspace with Responsive Design and Multiplatform approaches using Flutter Framework Puspitasari, Shinta Yulia; Ra'uf, Iqbal Abdul; Nurtantyana, Rio; Satrio, Cahyo Tri
International Journal on Information and Communication Technology (IJoICT) Vol. 10 No. 1 (2024): Vol. 10 No.1 June 2024
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/ijoict.v10i1.919

Abstract

Most of previous studies implemented the responsive design approach for the web-based application platform only since it had several difficulties to apply in the mobile-based application platform. In addition, the mobile application required different codebases since there were several platforms like Android and iOS. However, this study tried to redevelopment the Proxsis Workspace website to mobile application with responsive design and multiplatform approaches using Flutter Framework, in order to explore the potentials and counter the difficulties these two approaches for mobile development. In addition, we provide the detailed improvement, and the software testing results of our redevelopment app. Eight participants were participated in this study to measure the improvement of the redevelopment application. The results showed that the redevelopment version of the Proxsis Workspace could implement the responsive design and multiplatform approaches well. Furthermore, the software testing found that the redevelopment version passed the responsive design and multiplatform testing. In addition, there was significant different and enhancement of the usability score from 52.50 with marginal category to 72.81 with acceptable category. Hence, the authors suggest implementing the responsive design and multiplatform with Flutter Framework to enhance and make efficient with single code base only.
Pengembangan Sistem Deteksi Jatuh Ringan Berbasis Pose Estimation Pada Video CCTV Untuk Edge Device Imam Yabunaiya Ramadhani; Bedy Purnama; Mulyantini, Agustien; Satrio, Cahyo Tri
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol. 12 No. 2 (2026): Volume 12 No 2
Publisher : Program Studi Informatika

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Abstract

Deteksi jatuh merupakan komponen penting dalam sistem pemantauan kesehatan, khususnya bagi lansia dan individu berisiko tinggi. Sebagian besar metode berbasis deep learning membutuhkan sumber daya komputasi yang besar sehingga kurang sesuai untuk perangkat edge. Penelitian ini mengusulkan sistem deteksi jatuh berbasis video yang menggabungkan human pose estimation dan klasifikasi lightweight dalam pipeline terintegrasi yang mencakup preprocessing video, pose estimation, temporal smoothing, ekstraksi fitur kinematik, temporal pooling, dan klasifikasi. Eksperimen dilakukan menggunakan gabungan UR Fall Detection, Le2i, dan Multicam Dataset sebanyak 472 video, dan diuji pada Raspberry Pi 5. Hasil menunjukkan bahwa kombinasi OpenPose Body25 dan Random Forest memperoleh accuracy tertinggi sebesar 89,58% dan F1-score sebesar 92,96%, sedangkan BlazePose Lite dan TinyML memberikan keseimbangan terbaik antara performa klasifikasi dan efisiensi komputasi dengan accuracy sebesar 85,42% dan F1-score sebesar 91,36%.
Co-Authors Agustien Mulyantini Bedy Purnama Imam Yabunaiya Ramadhani Nurtantyana, Rio Ra'uf, Iqbal Abdul Shinta Yulia Puspitasari