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Implementation of HACCP and GMP in the coffee processing industry with a website-based information system Ilham Ramadhani
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 9 No. 1 (2026): Jurnal Teknologi dan Open Source, June 2026
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v9i1.5323

Abstract

Digital transformation is essential in improving operational efficiency and food safety compliance in the food processing industry. Argopuro Walida still manages warehouse and production activities manually, resulting in data inaccuracies, limited traceability, and delayed reporting. This research aims to develop a web-based Warehouse Management and Production Information System integrated with Good Manufacturing Practices (GMP) and Hazard Analysis Critical Control Point (HACCP) standards using the Rapid Application Development (RAD) method. The system was developed through requirements planning, design workshop, development, and testing phases. It supports production recording, real-time stock monitoring, transaction management, and structured GMP–HACCP documentation with role-based access control. Black Box Testing confirmed that all functional modules operated properly. The results show that the system improves data accuracy, operational efficiency, real-time monitoring, and food safety documentation, supporting better warehouse and production management in coffee processing industries.
Comparison of KNN and Logistic Regression Algorithms in Classifying Food Product Healthiness Based on Nutritional Information Iidris Fikri; Ahmad Homaidi; Syarif Aminul Khoiri
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 9 No. 1 (2026): Jurnal Teknologi dan Open Source, June 2026
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v9i1.5626

Abstract

This research was conducted to analyze and compare the effectiveness of the K-Nearest Neighbor (KNN) and Logistic Regression algorithms in identifying the health category of food products using nutritional information. The dataset employed in this study was collected from Kaggle in CSV format and consisted of several nutritional attributes, including energy, fat, protein, sugar, and sodium content. The research methodology followed a data mining process that included preprocessing, data normalization, model training, and performance evaluation through a confusion matrix. Furthermore, a web-based classification application was created using the PHP programming language to assist in testing and simulating the product classification process. The experimental results indicated that the K-Nearest Neighbor algorithm achieved an accuracy value of 84.25%, with a precision of 0.82 and a recall of 0.78. Meanwhile, Logistic Regression produced an accuracy of 82.88%, a precision of 0.81, and a recall of 0.83. Based on these findings, the K-Nearest Neighbor method demonstrated slightly better performance in classifying the healthiness of food products.
The Impact of Agile Methodology Implementation on Software Quality in Information System Development A Case Study of Industry X Muhammad Galih Ramaputra; Hendri Purnomo; Seli Puri Andini
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 9 No. 1 (2026): Jurnal Teknologi dan Open Source, June 2026
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v9i1.5627

Abstract

The rapid demand for high-quality software requires organizations to adopt adaptive and efficient development methodologies. This study examines the impact of Agile methodology adoption on software quality within information system development in Industry X. Utilizing a quantitative explanatory design, data were collected via questionnaires from 100 software development team members and analyzed using simple linear regression. Descriptive analysis indicates that both Agile implementation (mean = 4.14) and software quality (mean = 4.09) fall into the high category. Hypothesis testing confirms that Agile methodology has a positive and significant effect on software quality (β = 0.68, t-count = 11.33, p < 0.001), contributing 52% to its variance (R² = 0.52). While team collaboration and functional suitability emerged as the strongest contributors, customer engagement and performance efficiency received the lowest scores. These findings imply that robust Agile practices substantially elevate system quality. To maximize outcomes, organizations must strategically intensify user participation throughout the development cycles and reinforce rigorous performance testing.
Prediction Model of Batam University Management Information System Based on Regression and Machine Learning Fendi Hidayat; Eisyaniah Desvazulinda; Syakinah Warrahmah
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 9 No. 1 (2026): Jurnal Teknologi dan Open Source, June 2026
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v9i1.5648

Abstract

The implementation of Management Information Systems (MIS) in higher education is strongly influenced by the use of information technology (IT) and the digital competence of its users. This study aims to analyze the influence of IT use and digital competence on MIS at Batam University, as well as to develop the best prediction model by comparing conventional statistical methods and machine learning algorithms. Research data were collected through a Likert-scale-based questionnaire from respondents selected using a purposive sampling technique. Data analysis was performed using a combination of Multiple Linear Regression, Random Forest Regressor, and Gradient Boosting Regressor. The results of statistical tests indicate that the use of IT and digital competence simultaneously have a positive and significant effect on MIS with a coefficient of determination ($R^2$) of 87.40%. On the other hand, the results of the machine learning model evaluation show that Random Forest Regressor provides the best performance with the lowest MAE and RMSE values, and the highest prediction accuracy ($R^2$ Score) reaching 0.905072. This study concludes that the integration of statistical and machine learning approaches can produce an accurate and adaptive MIS prediction model to support data-driven decision making at Batam University
Design and Development of a Web-Based Customer Queue Information System on a Local Area Network Using PHP (Case Study: PT BPD Jambi Sharia Branch) Andreo Yudertha; Zulhadi Abdillah; Khalilah Silky; Zainul Muttakin4; AZN padila
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 9 No. 1 (2026): Jurnal Teknologi dan Open Source, June 2026
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v9i1.5730

Abstract

Optimal customer service is a key factor in improving banking service quality. At PT BPD Jambi Sharia Branch, queue management is still conducted manually using paper-based queue numbers, which is inefficient and prone to errors. This study aims to design and develop a web-based customer queue information system operating on a local area network (LAN). The system was developed using the Waterfall method, including requirement analysis, system design, implementation, and testing. The technologies used are PHP and MySQL as the database. The system is designed without a login mechanism because it is intended for use in a controlled internal environment. The results show that the system improves service efficiency, simplifies queue management, and reduces errors in queue calling. Therefore, this system supports the digitalization of customer service in the banking environment. Furthermore, the system is expected to enhance operational accuracy, accelerate service time, and provide a more organized queue experience for customers at the branch and improve overall system performance.

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