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All Journal International Journal Software Engineering and Computer Science (IJSECS) Jurnal Manajemen Sistem Informasi
Abyan, Muhammad Abdul Aziz
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management

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Rancang Bangun Aplikasi Toko Online Berbasis Website ATK Yudistira Jaya Abyan, Muhammad Abdul Aziz; Surapati, Untung
Jurnal Manajemen Sistem Informasi (JMASIF) Vol. 4 No. 1 (2025): April 2025
Publisher : Divisi Riset, Lembaga Mitra Solusi Teknologi Informasi (L-MSTI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59431/jmasif.v4i1.479

Abstract

The rapid development of information technology has brought significant changes to the trading sector, including micro, small, and medium enterprises (MSMEs). This study aims to design and develop a website-based online store application for ATK Yudistira Jaya to enhance operational efficiency and expand market reach. The development method used in this system is the Waterfall model, with the Laravel framework for the backend and MySQL as the database. The test results indicate that the application meets the needs of both admins and customers, with key features such as a product catalog, ordering system, payment integration, and order management. The implementation of this application is expected to assist MSMEs in leveraging digital technology to improve their competitiveness.
Image Quality Improvement for Sign Language Gestures Through Gaussian Filter and Contrast Stretching Techniques Mulyana, Dadang Iskandar; Abyan, Muhammad Abdul Aziz
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i3.5254

Abstract

Deaf people use sign language as their primary means of communication. Images of sign language gestures are usually low quality because visual impairments like noise and low contrast prevent an automatic recognition system from working well. This research tries to enhance the quality of images with sign language gestures using two preprocessing methods, namely Gaussian Filter and Contrast Stretching. The first one eliminates noise while keeping important details in the image, and the second increases pixel intensity distribution to make hand gestures more apparent and outlined. An experiment was done on a dataset that includes 54,049 static hand gesture images taken from videos that contain certain sign languages divided into 28 classes for hijaiyah letters. A quantitative evaluation indicated substantial enhancements in processed image quality. The preprocessing method resulted in an average PSNR of 20.13 dB, SSIM equal to 0.8875, and MSE equal to 976.39 for all samples tested confirming that this combination method improves sharpness, structural integrity, and contrast when compared with original unprocessed images significantly. This study recommends using Gaussian Filter along with Contrast Stretching as a practical option for improving the quality of sign language images which can eventually help automated recognition systems that need clear visual input to correctly classify gestures.
Co-Authors Dadang Iskandar Mulyana` Surapati, Untung