cover
Contact Name
Ardi Susanto
Contact Email
jais.ejurnal@gmail.com
Phone
+6281235610550
Journal Mail Official
admin@gws-tech.id
Editorial Address
Jalan Raya Kluwut Timur no. 24, Kluwut, Bulakamba
Location
Kab. brebes,
Jawa tengah
INDONESIA
Journal of Applied Informatics Science
Published by GWS Tech Solution
ISSN : 31107451     EISSN : 31107451     DOI : -
Aim The Journal of Applied Informatics Science is dedicated to advancing the discipline of applied informatics by publishing high-quality, peer-reviewed research that integrates theoretical foundations with practical solutions. The journal seeks to promote scientific excellence, foster technological innovation, and support interdisciplinary collaboration within the global informatics community. Its primary objective is to provide an authoritative platform for researchers, academicians, and industry professionals to disseminate original contributions that address emerging challenges, opportunities, and transformations in intelligent and secure computing. Scope The journal welcomes submissions that explore concepts, models, technologies, and applications across a wide spectrum of applied informatics. Areas of interest include, but are not limited to: Intelligent Systems and Artificial Intelligence: machine learning, deep learning, expert systems, natural language processing, computer vision, robotics, autonomous systems, and intelligent agents. Software Engineering: software development methodologies, agile and DevOps approaches, software testing and quality assurance, software architecture, cloud-native development, and distributed systems. Computing Systems: high-performance computing, embedded and real-time systems, parallel computing, Internet of Things (IoT), sensor networks, edge and fog computing, and cyber-physical system architectures. Cybersecurity and Cryptography: secure communication protocols, network security, intrusion detection and prevention systems, cryptographic techniques, cyber threat modeling, blockchain security, and privacy-preserving technologies. Big Data and Data Analytics: scalable data processing frameworks, data mining, predictive analytics, real-time analytics, data streams, visualization techniques, and analytical dashboards. Business Intelligence and Knowledge Management: decision support systems, enterprise data warehousing, knowledge discovery, digital transformation strategies, and AI-driven business process optimization. The journal accepts original research articles, review papers, technical notes, and case studies that contribute to scientific understanding, technological development, policy insight, or practical implementation of informatics solutions. All submissions undergo a rigorous peer-review process to ensure academic integrity, relevance, and quality. The Journal of Applied Informatics Science encourages interdisciplinary research that connects informatics with domains such as healthcare, education, business, environment, industry, and public services.
Articles 4 Documents
Search results for , issue "Volume 1 Issue 1 (2025)" : 4 Documents clear
Design and Construction of a Web-Based Maintenance Ticket System to Optimize Damage Monitoring in Retail Stores Andrianto, Andrianto; Anggraeni Putri, Sukmawati
Journal of Applied Informatics Science Volume 1 Issue 1 (2025)
Publisher : GWS Tech Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65897/jais.v1.i1.28

Abstract

PT Indomarco Prismatama Tangerang 1 branch faces challenges in managing store infrastructure maintenance tickets because the reporting process is still manual. This causes delays in handling, unstructured documentation, and difficulty in monitoring repair status. This study aims to design a web-based maintenance ticket information system to improve reporting and damage monitoring efficiency. The research methods include observation, interviews, and literature study using a system development approach based on the Waterfall model. The system is developed using PHP and MySQL and designed using ERD and logical data structure modeling. Testing is performed using black-box testing and User Acceptance Testing to evaluate system functionality and user acceptance. The results show that all system functions operate properly and the system is accepted with a high level of user satisfaction. The implementation improves maintenance process effectiveness and supports smoother store operational activities.
A Web-Based Chatbot-Integrated Application for Skin Disease Detection Using ResNet50 Architecture Naovi Magfiroh; Sasmito, Ginanjar Wiro; Ilmadina, Hepatika Zidny
Journal of Applied Informatics Science Volume 1 Issue 1 (2025)
Publisher : GWS Tech Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65897/jais.v1.i1.31

Abstract

The skin is a vital human organ located on the outermost part of the body and is vulnerable to various external stimuli and diseases. The high prevalence of skin diseases in Indonesia indicates a lack of public awareness regarding skin health. This study aims to develop a web-based application capable of detecting 10 types of skin diseases quickly and accurately using the ResNet50 architecture and computer vision technology. The research stages include the creation of a Haar Cascade Classifier, developing an image classification model, model evaluation, chatbot development, system design, implementation, and application testing. The results show that the model achieved an accuracy of 90.10% on the training data and 89.06% on the validation data. The integrated chatbot also provided additional information with a response accuracy of 87.50%. System testing demonstrated good performance based on black-box testing and scored 77.625 on the System Usability Scale (SUS), which falls into the "Good" category. This application can detect early skin disease without requiring direct consultation with a doctor.
Drug Data Management Application at Telu Tegal Pharmacy Using Website-Based K-Means Algorithm Rafidatus Salsabilah Qosimah; Ginanjar Wiro Sasmito; Dyah Apriliani
Journal of Applied Informatics Science Volume 1 Issue 1 (2025)
Publisher : GWS Tech Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65897/jais.v1.i1.34

Abstract

The rapid development of information technology provides great opportunities in increasing the efficiency and accuracy of data management, including in the pharmaceutical sector. Apotek Telu as one of the health service providers requires a system that is able to manage drug sales data effectively and provide useful insights in decision making. This study aims to build a website-based application that not only handles drug data management and sales transactions, but is also equipped with a disease trend analysis feature using the K-Means Clustering algorithm. This method is used to group drug purchase data based on patient purchase patterns, so that it can identify disease trends that often occur in a certain period. This application is built using the Laravel framework for the backend and Blade as the frontend templating system. The test results show that the application is able to manage data efficiently and display the results of disease trend analysis in the form of informative graphic visualizations, so that it can help pharmacies in planning stock and providing more targeted services.
Web-Based Electronic Medical Record System with Patient Activity Recommendation Using K-Nearest Neighbor Algorithm Rama Oktabara; Ginanjar Wiro Sasmito; Dega Surono Wibowo
Journal of Applied Informatics Science Volume 1 Issue 1 (2025)
Publisher : GWS Tech Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65897/jais.v1.i1.36

Abstract

In the digital era, the use of information technology in the health sector continues to grow, one of which is through the implementation of Electronic Medical Records (EMR). This study develops a web-based EMR system equipped with an automatic patient activity recommendation feature using the K-Nearest Neighbor (KNN) algorithm. Data from 550 patients from Dr. Viandini Clinic, Halo doc, and the internet were used with attributes of disease, age, blood pressure, and activity recommendations. The development process includes data collection, labeling, preprocessing, training and evaluation of the KNN model using the Accuracy@1 and Accuracy@5 metrics. The system is implemented with Laravel Filament and Python-Flask for the recommendation API. The test results show that the system is able to provide relevant recommendations with Accuracy@1 of 90.83% and Accuracy@5 of 95.31%. The application of KNN to this system supports automation, efficiency, and improvement of service quality in clinics and is the basis for the development of more personalized and data-driven digital health services.

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