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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): November : International Journal of Multilingual Education and Applied Linguist
Publisher : Asosiasi Periset Bahasa Sastra Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/ijmeal.v1i4.156

Abstract

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 preparation of low-resolution facial images, applying the ESRGAN model to enhance image resolution, and evaluating the results using metrics such as PSNR and SSIM. The findings reveal that ESRGAN significantly improves the visual details of facial images, thereby supporting better facial identification processes. These results have important implications for leveraging deep learning technology to facilitate image analysis in forensic contexts. However, challenges such as extreme noise presence require further development of methods to achieve more optimal outcomes.
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 (2025): International Journal of Computer Technology and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijcts.v2i1.126

Abstract

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 requirements without considering the internal code structure. The test results indicate that most features function as expected. However, some issues were identified related to input validation, particularly with email format, phone number length, file uploads, and product stock management. Additionally, the order management and AI counseling features showed deficiencies in error handling and input validation. Based on these findings, the study recommends improvements in input validation, product stock management, shopping cart functionality, and AI counseling systems to enhance the reliability and performance of the JivaJoy platform. These enhancements are essential to deliver more efficient, secure, and optimal services, ensuring better user experiences and customer satisfaction.
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 (2025): International Journal of Computer Technology and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijcts.v2i1.131

Abstract

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 Development Life Cycle) method, this research outlines the system development process, from needs analysis to system evaluation The LeleQue application is equipped with key features such as financial bookkeeping, inventory management, debt tracking, financial reports, and discussion forums. The findings indicate that LeleQue provides an integrated platform to meet the operational management needs of catfish farming businesses. Additionally, the application facilitates collaboration among farmers through its community forum. This study contributes to supporting MSME digitalization, particularly in the catfish farming sector, to enhance efficiency, productivity, and business competitiveness.
Implementasi Metode Waterfall dalam Pembuatan Website Katering Diet FitMeal Anatasya Wenita Putri; Helena Dewi Hapsari; Rivanka Marsha Adzani; Nabil Malik Al Hapid; Aditya Wicaksono; Mindara, Gema Parasti
Jurnal Teknologi dan Manajemen Industri Terapan Vol. 4 No. 3 (2025): Jurnal Teknologi dan Manajemen Industri Terapan (in press)
Publisher : Yayasan Inovasi Kemajuan Intelektual

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55826/jtmit.v4i3.725

Abstract

Perkembangan gaya hidup sehat mendorong masyarakat untuk memilih makanan yang tidak hanya praktis, tetapi juga bernutrisi dan sesuai dengan kebutuhan diet. Namun, sistem pemesanan catering tradisional masih memiliki sejumlah keterbatasan, seperti proses yang tidak efisien dan minimnya personalisasi menu. Penelitian ini bertujuan untuk merancang website FitMeal sebagai platform digital pemesanan catering sehat dan program diet menggunakan metode pengembangan perangkat lunak Waterfall. Proses pengembangan meliputi tahap analisis kebutuhan, desain sistem, implementasi, pengujian, hingga pemeliharaan. Website dikembangkan menggunakan framework Laravel dengan pendekatan Model-View-Controller (MVC). Untuk menjamin kualitas sistem, dilakukan pengujian menggunakan metode Black Box Testing dengan teknik Equivalence Partitioning. Sebanyak 13 fitur utama, baik dari sisi pengguna maupun admin, diuji menggunakan berbagai skenario input valid dan tidak valid. Hasil pengujian menunjukkan bahwa seluruh fitur, termasuk registrasi, pemilihan paket diet harian/bulanan, informasi gizi per menu, Top Menu, dan sistem pembayaran terintegrasi, berhasil dijalankan tanpa kesalahan fungsional. Website FitMeal diharapkan dapat menjadi solusi digital yang efektif dan user-friendly dalam mendukung masyarakat menjalani gaya hidup sehat melalui akses pemesanan makanan berbasis teknologi yang personal dan andal.