Journal Global Technology Computer

Analisis Peran Sistem Enterprise Resource Planning dalam Mendukung Manajemen Produksi dan Penjualan Usaha Mikro Kecil Menengah

2026-04-22T11:11:25+07:00

Micro, Small, and Medium Enterprises (MSMEs) of Kopi Muria Zayna still face challenges in managing production and sales activities that are conducted manually and are not yet integrated. This condition results in weak control over raw material inventory, suboptimal production planning, and inaccurate sales recording and reporting that require considerable time. This study aims to analyze the role of an Enterprise Resource Planning (ERP) system in supporting production and sales management at Kopi Muria Zayna MSME. The research employs a qualitative approach with a descriptive case study method through several stages, including analysis of the existing system (As-Is), identification of system requirements, and design of the proposed ERP-based system (To-Be). Data were collected through observation, interviews, and documentation, while system analysis was conducted using the PIECES framework. The results indicate that an ERP system conceptually has the potential to improve production process efficiency, enhance integrated management of raw material and finished goods inventory, and support more accurate and structured sales recording and reporting. Furthermore, ERP can assist MSME owners in making more precise and timely data-driven decisions. Therefore, the ERP system plays a strategic role in supporting operational effectiveness and the long-term business sustainability of Kopi Muria Zayna MSME.

Klasifikasi Kualitas Biji Kopi Secara Otomatis Berbasis Citra Visual Menggunakan Convolutional Neural Network (CNN)

2026-04-22T11:11:45+07:00

Coffee bean quality is a crucial factor that determines the commercial value and overall quality of coffee products. In practice, coffee bean quality assessment is still largely performed manually through visual inspection, which may lead to subjectivity and inconsistent results. Therefore, this study aims to apply a Convolutional Neural Network (CNN) method to automatically classify coffee bean quality based on visual images. This study employs a quantitative approach using a computational experimental method. The dataset consists of 90 coffee bean images categorized into three quality classes, namely good, medium, and poor, with 30 images in each class. All images undergo preprocessing stages, including image resizing to 150 × 150 pixels, pixel value normalization, and data augmentation. The CNN model is developed using the TensorFlow and Keras frameworks on the Google Colab platform and trained using the Adam optimizer and categorical crossentropy loss function with an optimal number of 20 epochs. The results show that the CNN model is able to learn basic visual patterns of coffee beans progressively, as indicated by an increase in accuracy and a decrease in loss values during the training process. However, evaluation using a confusion matrix reveals that the model still faces difficulties in distinguishing between quality classes with similar visual characteristics, particularly between the good, medium, and poor categories. Nevertheless, this study demonstrates that CNN has strong potential as an initial approach for developing an automated system to support objective and consistent coffee bean quality classification.

Penerapan Teknologi Full Stack dalam Pengembangan Sistem Formulir Digital Rumah Sakit Menggunakan Metode Waterfall Development

2026-04-22T11:11:54+07:00

The healthcare sector currently faces significant challenges in patient data management, where manual medical recording often leads to inefficiency, the risk of data loss, and slow information access by medical personnel. The main problem faced by many hospitals is the suboptimal integration between patient data collection and centralized database systems, which hinders continuous care delivery. Therefore, this study aims to design and develop an integrated digital form system in a hospital environment to facilitate accurate, fast, and secure medical data recording. The proposed solution is the application of full-stack technology using the CodeIgniter framework, PHP programming language, and DBeaver for database management. This research employs the Waterfall Development method, which aligns with collaborative team workflows. The development process is divided into iterative stages, starting from task assignments based on interface mockups from the Project Manager, dynamic data processing, to code collaboration via GitHub. Every system update goes through a Pull Request mechanism and is comprehensively tested by the Quality Assurance (PDI) team to ensure functionality and prevent errors. The achieved results indicate that the full-stack approach combined with the Waterfall method successfully produces a responsive digital form prototype, minimizes bugs through rigorous code reviews, and accelerates software adaptation. The contribution of this research is providing a scalable architectural model for health information systems, which can serve as a reference for medical institutions in executing digital transformation in healthcare services.

A Correlation Based Modeling of Industry on Campus Implementation on Ethics, Professionalism, and Digital Competency

2026-04-29T11:12:12+07:00

In this research, the use of the industry on campus (IoC) approach at Baling Community College and its impact on the students’ ethicality, professionalism, and digital capability is considered. Early findings revealed that the students possessed relatively average levels of ethicality, professionalism, and skillful usage of technological aids, making it necessary to introduce an intervention measure. For this reason, the comprehensive module of IoC approach, which involves ethical considerations, professionalism, and digital skills, was devised through the means of reflective learning, mentoring, and case studies carried out in the real industrial environment. The findings have shown substantial improvement regarding all three areas with digital competence displaying the most considerable growth. Based on the results, the combination of experiential learning in the form of participation in case studies under the guidance of industrial mentors, together with active use of the digital tools, increases students' abilities to apply ethical and professional aspects of performance. Nonetheless, the problems were recognized, such as the lack of time, inconsistencies in mentoring, and difficulties in evaluation.

UXplore@poly: A Mobile Learning Application Developed Using the ADDIE Model to Enhance Student Performance in User Experience Fundamentals

2026-05-05T13:31:16+07:00

UXplore@poly is a mobile learning application developed to enhance students’ understanding of the DFK30023 User Experience Fundamentals course. As a newly introduced course in the Polytechnic Diploma in Information Technology programme, students face challenges in accessing structured and syllabus-aligned learning materials, which affects their understanding and engagement. This study aims to evaluate the effectiveness of UXplore@poly in improving students’ learning experience and academic performance. A quantitative research approach was employed involving 39–42 students, using needs analysis and post-analysis surveys as well as pre-assessment and post-assessment evaluations. The application was developed based on the ADDIE instructional design model and integrates various learning components into a centralized and accessible mobile learning platform. The findings from the needs analysis indicate a strong demand for a structured and accessible learning solution. Following the implementation of UXplore@poly, the results show significant improvements in students’ learning experience, with high levels of engagement, usability, and satisfaction reported. In addition, students’ academic performance improved by approximately 30% to 40% based on pre- and post-assessment results. Furthermore, expert evaluation results indicate consistently high ratings across all criteria, confirming the quality, usability, and effectiveness of the application. The convergence of student feedback, performance improvement, and expert validation demonstrates a strong triangulation of evidence. These findings indicate that UXplore@poly effectively enhances students’ understanding, supports self-directed learning, and improves academic outcomes. This study concludes that UXplore@poly is a robust, user-centered mobile learning solution with strong potential for scalability and wider implementation in higher education.