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All Journal JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Journal Medical Informatics Technology
Puspitaningtyas, Mery Oktaviyanti
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Computer Science & IT Dentistry Education Engineering Medicine & Pharmacology Public Health

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Optimizing Image Quality for Dog Skin Disease Diagnosis: Bacterial, Fungal, and Hypersensitivity Cases with MATLAB Puspitaningtyas, Mery Oktaviyanti; Na`am, Jufriadif
Journal Medical Informatics Technology Volume 3 No. 3, September 2025
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/medinftech.v3i3.54

Abstract

Skin diseases in dogs, such as hypersensitive dermatitis, fungal infections, and bacterial dermatoses, present diverse clinical signs that complicate diagnosis in veterinary practice. This study employs MATLAB as an image-processing tool to enhance diagnostic accuracy through a structured pipeline. A dataset of 500 canine skin images obtained from Kaggle was processed using enlargement, histogram equalization, Gaussian filtering, and Sobel convolution. These methods improved image quality by enhancing contrast, reducing noise, and clarifying lesion boundaries. The experimental results demonstrate that the processed images allow veterinarians to more easily detect key diagnostic features, including changes in lesion texture, color, and shape. Enhanced visual clarity supports faster identification of disease patterns and reduces diagnostic ambiguity in clinical settings. This study highlights the potential of MATLAB-based image processing as an effective decision-support tool for veterinary dermatology, enabling quicker and more reliable treatment planning. Future work may integrate deep learning classification to further automate disease recognition.
SMART CONTRACT-DRIVEN QUEUE MANAGEMENT FOR EFFICIENT ONLINE TICKET PURCHASING ON BLOCKCHAIN Puspitaningtyas, Mery Oktaviyanti; Ilmi, Happid Ridwan; Wardani, Yulita Ayu; Saputra, Irwansyah
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 4 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i4.7367

Abstract

This study investigates how smart contract-driven queue management can be utilized to increase online ticket purchasing efficiency via blockchain technology. The system is designed to manage ticket purchase queues transparently and securely, using smart contracts written in the Solidity programming language and the Ionic UI framework. In addition, the system is connected with MetaMask as a transaction wallet, allowing users to purchase tickets directly and securely. Ganache serves as a testing environment for replenishing wallet balances without involving real transactions. The First In First Out (FIFO) approach is used to manage the transaction queue, with the first purchased ticket being processed first by the administrator. The administrator accepts each transaction, which is then confirmed by MetaMask. When the transaction is confirmed, the system automatically updates the ticket status. The implementation results show that this system effectively optimizes ticket transaction management transparently and securely. This work also makes a significant contribution to the application of blockchain technology for better management of online ticket purchasing systems, as well as minimizing the possibility of transaction errors and fraud.
Co-Authors Ilmi, Happid Ridwan Jufriadif Na`am, Jufriadif Saputra, Irwansyah Wardani, Yulita Ayu