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All Journal International Journal Software Engineering and Computer Science (IJSECS)
Muhammad Abdul Aziz Abyan
Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika
Computer Science & IT

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Design and Development of a Web-based Online Store Application for Yudistira Jaya Stationery Shop Muhammad Abdul Aziz Abyan; Untung Surapati
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3887

Abstract

The accelerated progress of information technology has fundamentally reshaped the landscape of the trade sector, with notable impacts on micro, small, and medium enterprises (MSMEs). This research aims to design and develop a web-based online sales platform tailored for ATK Yudistira Jaya, a stationery and photocopy service provider, to optimize operational efficiency and broaden market accessibility. The development process employs the Waterfall methodology, a systematic approach that ensures structured progression through distinct phases of system creation. The technological foundation of the platform is built using the Laravel framework for backend operations, paired with MySQL as the database management system to handle data storage and retrieval effectively. Findings from the system evaluation indicate that the developed platform adequately addresses the functional requirements of both administrators and end-users. Key features integrated into the system include a comprehensive product catalog for easy browsing, a streamlined order placement mechanism, secure payment integration through a trusted gateway, and robust order management tools to track and process transactions. The successful implementation of this digital solution is anticipated to empower MSMEs like ATK Yudistira Jaya by equipping them with the necessary tools to navigate the challenges of a digital marketplace, ultimately enhancing their competitive edge through strategic adoption of technology.
Image Quality Improvement for Sign Language Gestures Through Gaussian Filter and Contrast Stretching Techniques Dadang Iskandar Mulyana; Muhammad Abdul Aziz Abyan
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.
Image Quality Improvement for Sign Language Gestures Through Gaussian Filter and Contrast Stretching Techniques Dadang Iskandar Mulyana; Muhammad Abdul Aziz Abyan
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

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` Untung Surapati