Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal JoDENS: Journal of Digital Ecosystem for Natural Sustainability
Tang, Steven
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Perancangan Aplikasi Belens : Pemindai Minuman untuk Penilaian Kualitas dan Komposisi Berbasis Gambar Edison; Whenjaya, Calvin; Tang, Steven; Lia Febrianti, Eka
Journal of Digital Ecosystem for Natural Sustainability Vol 5 No 1 (2025): Juli 2025
Publisher : Fakultas Komputer - Universitas Universal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63643/jodens.v5i1.281

Abstract

Jurnal ini menyajikan desain aplikasi Belens, aplikasi mobile berbasis Android untuk analisis minuman melalui teknologi pemrosesan gambar dan kecerdasan buatan. Penelitian ini memiliki beberapa fokus antara lain persyaratan perangkat lunak, desain arsitektur sistem, dan desain permukaan pengguna. Metodologi Desain Menggunakan Software Development Life Cycle (SDLC) dengan pendekatan waterfall yang menekankan persyaratan sistem dan analisis desain yang sistematis. Hasil desain meliputi persyaratan fungsional seperti pemindaian gambar dan analisis minuman, kebutuhan non-fungsional seperti kemampuan keselamatan dan respons, dan visualisasi sistem melalui diagram aplikasi, diagram aktivitas dan diagram kelas. Dokumen ini juga menyediakan desain antarmuka pengguna dan aliran interaksi yang memprioritaskan keramahan pengguna. Desain aplikasi Belens diharapkan membentuk dasar untuk pengembangan sistem minuman, dengan pengguna yang menerima informasi konfigurasi visual dan efisien dan kualitas minuman.
Implementasi Regresi Linear Berganda dalam Prediksi Waktu Tiba Bus Transjakarta Menuju Destinasi Akhir Duandi; Triyanti, Vivie; Tang, Steven
Journal of Digital Ecosystem for Natural Sustainability Vol 4 No 2 (2024): Desember 2024
Publisher : Fakultas Komputer - Universitas Universal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63643/jodens.v4i2.258

Abstract

Transjakarta, the primary public transportation system in Jakarta, plays a strategic role in meeting the growing mobility needs of urban residents. This study aims to implement multiple linear regression to predict bus arrival times at final destinations using simulated transaction data that includes tap-in and tap-out information, bus routes, travel times, as well as additional variables such as traffic conditions, route distances, and operational hours. The analysis results indicate that the predictive model developed has high accuracy, with traffic conditions and route distances identified as significant factors. The implementation of this model has the potential to assist Transjakarta operators in improving route management efficiency, reducing passenger wait times, and providing more accurate arrival time estimates through supporting applications. This research also lays the foundation for developing data-driven prediction systems for public transportation management.
Co-Authors Duandi Edison Febrianti, Eka Lia Triyanti, Vivie Whenjaya, Calvin