Journal of Enhanced Studies in Informatics and Computer Applications

Implementation of Extreme Programming (XP) in the Development of Dental Clinic Information Systems

2025-02-28T13:41:33+00:00

Along with the development of information technology, dental clinics are required to improve efficiency and quality of service through an integrated information system. This study aims to develop a web-based Dental Clinic Information System using Laravel with the Extreme Programming (XP) method as its development approach. This system is designed to manage electronic medical records, examination schedules, drug stock, and patient bills efficiently, according to the Regulation of the Minister of Health of Indonesia Number 24 of 2022 concerning electronic medical records. This research method involves four stages in XP: planning, design, coding, and testing. At the design stage, Use Case and Activity Diagram modeling are created to ensure the system meets user needs. The system implementation uses Laravel Filament to build an integrated admin dashboard. Testing is carried out using Black-Box Testing to ensure all features function properly. The results of the study show that the developed system can improve the operational efficiency of dental clinics, reduce manual recording errors, and speed up the administration process. With the XP approach, system development becomes more flexible and adaptive to changes in user needs. It is hoped that this system can be applied in small to medium-scale dental clinics to improve the quality of health services.

Design and Implementation of a Construction Budgeting Application for Residential Projects on Android Platform Using the Waterfall Method

2025-02-28T13:41:38+00:00

Building a home is one of the most important and basic human needs. However, uncertainty around construction schedules and cost details often pose significant obstacles for individuals and families. The process can be overwhelming, especially for those with less experience in building homes. This is where information technology can play a vital role in streamlining the home-building process. By harnessing the power of technology, the building process can be simplified, providing greater transparency and convenience to users. To address these challenges, the Halo Rumah app was developed. The app helps users choose the right design and materials for their home construction. The app has an intuitive interface that allows users to explore a variety of home designs tailored to different preferences and choose materials that suit their needs and budget. Additionally, the app offers a range of advanced tools that help users estimate and calculate the costs of building a home, giving them a clear picture of their financial needs before starting the building process. By integrating these features, the Halo Rumah app ensures that users can make informed decisions, reduce uncertainty, and plan their dream home more effectively. Based on black box testing of 5 features tested on the Halo Rumah application, the research results show that the 5 features in the application can function according to the expected results.

MediStock: Medical Stock Website Development Using Design Thinking

2025-02-28T13:41:44+00:00

Pharmacies play a vital role in public health by ensuring the availability of essential medications. However, inefficient inventory management systems, particularly in Malang, lead to operational inefficiencies, stock discrepancies, and regulatory compliance challenges. This study aims to develop a web-based inventory management system, MediStock, using the Design Thinking methodology to address these issues effectively. The research employs a human-centered approach, focusing on user needs and experiences through the stages of empathize, define, ideate, prototype, and testing. The system integrates real-time stock monitoring, predictive analytics, and compliance with electronic medical records, enhancing operational efficiency and regulatory adherence. Results indicate that MediStock significantly improves inventory management by minimizing stock discrepancies, optimizing procurement processes, and ensuring real-time visibility of medicine stocks. The heuristic evaluation revealed high usability and adaptability among different user groups, confirming the system's effectiveness and the user-centered design. These findings highlight the potential of Design Thinking to bridge the gap between complex technological solutions and user needs in healthcare inventory management. This study contributes to the field by providing an innovative, user-friendly inventory management solution that enhances operational efficiency and regulatory compliance. Future research should explore the scalability of the system and its integration with broader healthcare management systems to maximize its impact on the healthcare sector.

Prediction of Unemployment Rates in East Java Region Using Multiple Linear Regression Method

2025-02-28T13:41:49+00:00

Unemployment is a major problem for developing countries, including Indonesia. The average unemployment rate in East Java is 5.202 percent from 2004 to 2023, according to data from Badan Pusat Statistik (BPS). These figures show that unemployment is still a major problem for local governments, despite changes. The purpose of this study is to create an application that can predict the number of unemployed in the future. The method used is multiple linear regression where this method was chosen because it can show how the year and labor force participation rate, which are two independent variables, correlate with the unemployment rate as the dependent variable. The data used comes from BPS and covers 19 years. This prediction model is integrated into a web-based platform to make the research results easier to access and use. This platform will display data and analysis results interactively, so that it can be used by local governments, academics, and other individuals looking for information about unemployment. The results of the study show that the regression model created is quite accurate. Based on the results of testing that has been carried out on the existing features, the system has displayed the appropriate output.

Comparing Discriminant Analysis Function for Early Prediction of Smartphone Addiction

2025-02-28T13:41:51+00:00

The pervasive use of smartphones in daily life has led to significant benefits, but excessive use has caused alarming behavioral and health issues, particularly among adolescents. Addressing smartphone addiction requires early detection to enable timely interventions. This study investigates the application of machine learning, specifically Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA), for the early prediction of smartphone addiction. The research used a dataset containing 394 instances categorized into "addicted" and "non-addicted" classes. Dataset is derived from questionnaire responses. After preprocessing steps, including feature selection and ordinal encoding, the data was split using 10-fold cross-validation to ensure robust evaluation. The models were assessed using metrics such as accuracy, precision, recall, and F-measure. Results indicate that LDA significantly outperforms QDA across all metrics, achieving an accuracy of 94.16%, a precision of 94.2%, a recall of 94.2%, and an F-measure of 94.2%. Additionally, the Receiver Operating Characteristic (ROC) curve analysis showed an Area Under the Curve (AUC) of 0.9875 for LDA, indicating its high reliability and stability in classifying smartphone addiction. QDA, while effective, has a slightly lower performance due to the linear separability of the dataset. This study concludes that LDA is a robust and effective method for early prediction of smartphone addiction, offering valuable insights for health monitoring systems. The findings provide a foundation for future applications of discriminant analysis in addressing behavioral health issues.