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Menampilkan 1–3 dari 3 artikel
Design and Development of LeleQue : A Web-Based Financial Management Application for Catfish Farming MSME
Jonser Steven
; Arya Dimas Wicaksana
; Helena Dewi Hapsari
; Wien Kuntari
International Journal of Computer Technology and Science
Vol 2
, No 1
(2024)
The rapid development of information technology has significantly impacted the business world, including Micro, Small, and Medium Enterprises (MSMEs). However, business actors, particularly in the catfish farming sector, often face challenges in accessing broader markets and improving operational efficiency. This study aims to develop LeleQue, a web-based information system designed to efficiently support the management of catfish farming businesses. By implementing the SDLC (Software Developmen...
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Functional Testing of the JivaJoy Online Product Stock Management and Ordering System Software Using Black Box Testing
Jasmine Aulia Mumtaz
; Kinaya Khairunnisa Komariansyah
; Helena Dewi Hapsari
; Bima Julian Mahardhika
; Luthfi Dika Chandra
; Muhammad Rafi' Rusafni
; Wicaksono, Aditya
; Mindara, Gema Parasti
International Journal of Computer Technology and Science
Vol 2
, No 1
(2024)
This study focuses on black-box testing of JivaJoy software, an online product stock management and ordering system. The primary goal of this research is to evaluate the functionality and performance of the system's key features, including profile management, CRUD operations for admin and customer accounts, product stock management, shopping cart, order management, and AI counseling. Black-box testing was applied to assess whether these features meet expected operational standards and user requi...
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Enhancing Low-Resolution Facial Images for Forensic Identification Using ESRGAN
Helena Dewi Hapsari
; Arya Dimas Wicaksana
; Hafiz Fadli Faylasuf
; Asa Yuaziva
; Rivanka Marsha Adzani
; Endang Purnama Giri
; Gema Parasti Mindara
International Journal of Multilingual Education and Applied Linguistics
Vol 1
, No 4
(2024)
This research is motivated by the challenges in facial identification for forensic investigations due to poor image quality, especially from low-resolution CCTV recordings. Images with noise, low lighting, and suboptimal angles often hinder accurate facial recognition. This study aims to examine the effectiveness of the Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) method in enhancing the quality of forensic facial images. The methodology consists of three main stages: data p...
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