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INDONESIA
Jurnal Mandiri IT
Published by Institute of Computer Science
ISSN : 23018984     EISSN : 28091884     DOI : https://doi.org/10.35335/mandiri
Core Subject : Science, Education,
Computer Science & IT Library & Information Science Mathematics
The Jurnal Mandiri IT is intended as a publication media to publish articles reporting the results of Computer Science and related research.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 233 Documents
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Website-Based laboratory management system of UNHAN RI Chemical Laboratory Sufi Naylil Karomah; Sembada Denrineksa Bimorogo; Tedi Kurniadi; Miranda B.M Sigalingging; M. Fadhil Diadra; M. Sulthan Nasyira; Daffa Mahdy Brata; Azzam Amar Ma’ruf
Jurnal Mandiri IT Vol. 14 No. 3 (2026): Jan: Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i3.503

Abstract

Effective laboratory management plays a crucial role in supporting academic and research activities in higher education; however, many university laboratories still rely on manual recording systems that lead to data inconsistencies, weak inventory control, and limited monitoring of material and equipment usage. These challenges are particularly critical in chemistry laboratories with high-intensity utilization and strict governance requirements, such as those in defense-oriented institutions. This study aims to develop and implement a web-based Laboratory Management System, namely LABUNICA, to improve the efficiency, accuracy, and accountability of laboratory operations in the Chemical Laboratory of Universitas Pertahanan Republik Indonesia. The system was developed using the Rapid Application Development (RAD) method, emphasizing iterative prototyping, direct user involvement, and continuous refinement based on operational feedback. System analysis and design were conducted through interviews, observations, and UML-based modeling, followed by front-end and back-end development and black-box testing. The results indicate that LABUNICA successfully streamlines laboratory workflows, reduces redundancy in usage recording, enhances real-time inventory monitoring, and supports role-based access control for users and administrators. The implementation of LABUNICA improves documentation accuracy, system usability, and operational transparency compared to previous manual practices. This study contributes to the laboratory information system literature by demonstrating the effectiveness of a user-centered, web-based management system tailored to the operational characteristics of a defense university chemistry laboratory, with practical implications for digital laboratory governance in higher education institutions.
Handwritten text segmentation using deep learning method Zulkarnaen Hatala; Ahmad Thariq; Josseano Parera; Muhammad Hatala
Jurnal Mandiri IT Vol. 14 No. 4 (2026): April: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i4.509

Abstract

The rapid development of artificial intelligence and deep learning technologies has increased the risk of digital task fabrication in academic environments, encouraging educators to reintroduce handwritten assignments as an authentic evaluation method. In handwritten document analysis systems, background segmentation is a critical preprocessing step that separates text from complex document backgrounds. This study proposes the use of the U-Net deep learning architecture for background segmentation of handwritten document images. Two datasets were employed: the public cBAD dataset and a custom dataset consisting of Indonesian handwritten student assignments. Both datasets were processed using an identical pipeline and evaluated using 5-fold cross-validation. Model performance was measured using the Dice Similarity Coefficient and Intersection over Union (IoU). Experimental results show that the proposed U-Net model achieved an average Dice coefficient (F1-Score) of 0.74 on the cBAD dataset and 0.83 on the student assignment dataset. These results indicate that the model performs consistently and demonstrates stable generalization across cross-validation folds. Therefore, the proposed approach is suitable as an initial segmentation stage in handwritten document recognition systems.
Design of a chatbot-based and web schedule management information system to optimize information distribution in the student cadet corps regiment of the Indonesian Defense University Amelia Kartika; Muhammad Rafi Arnof; Sayyid Hasan Harahap; Rizky Ramadhan Nasution; Henoch Kurniawan; Eryan Ahmad Firdaus
Jurnal Mandiri IT Vol. 14 No. 4 (2026): April: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i4.520

Abstract

The educational environment of the Student Cadet Corps Regiment at the Indonesian Defense University (Unhan RI) requires strict discipline and precise time management; however, the distribution of dynamic schedule information remains inefficient, delayed, and prone to human error due to conventional methods and restricted mobile device usage. This study aims to design and develop an integrated Schedule Management Information System that improves the efficiency, accuracy, and speed of information distribution. The research adopts a system development approach using the Waterfall method, integrating a Web-based Dashboard for schedule management and a Telegram Chatbot for real-time notification, supported by Role-Based Access Control (RBAC) to ensure data integrity and access security. The system was evaluated through Black Box Testing, usability testing using the System Usability Scale (SUS), and performance comparison between conventional and proposed methods involving 25 cadets and 4 staff. The results show that the proposed system significantly reduces schedule distribution time from 30–60 minutes to less than 5 seconds (>95% improvement), increases data accuracy to above 98%, and achieves a SUS score of 82, indicating high usability. These findings imply that the integration of web-based systems and chatbot technology can effectively enhance operational efficiency, support time discipline, and serve as a scalable model for information management in discipline-based institutions with strict operational constraints.
Prioritizing micro, small, and medium enterprises assistance areas in West Java using analytical hierarchy process Renita Lestari; Baenil Huda; Elfina Novalia; April Lia Hananto
Jurnal Mandiri IT Vol. 14 No. 4 (2026): April: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i4.527

Abstract

This study aims to develop a Decision Support System (DSS) to prioritize areas for receiving assistance for Micro, Small, and Medium Enterprises (MSMEs) in West Java Province using the Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods. The AHP method is used to determine the importance weight of each criterion based on its priority level, while the SAW method is used to carry out the normalization process, calculate preference values, and rank alternative areas. The criteria used include the number of MSMEs, workforce, financial stability ratio, legality ratio, BPP ratio, digital ratio, and innovation ratio. The results of the study indicate that the system built is able to produce an objective and consistent ranking of priority areas for MSME assistance, as evidenced by the agreement between the results of manual calculations using Microsoft Excel and the results of calculations in the system. Thus, this system is expected to assist relevant parties in making decisions regarding the distribution of MSME assistance in a more targeted and structured manner and rank 27 administrative regions in West Java Province. The results show that the highest-ranked region achieved a preference value of 0.8573, indicating its highest priority for MSME assistance, while the lowest-ranked region obtained a value of 0.5129. These results demonstrate the system’s capability to generate consistent and objective rankings. In addition, this study contributes by applying a combined AHP–SAW approach at a regional (macro) level, which is still limited in previous studies, thereby providing a more comprehensive framework for data-driven policy decision-making.
Inventory control system using threshold method for automotive industry Arya Fadillah; Bayu Priyatna; Fitria Nurapriani; Tukino Tukino
Jurnal Mandiri IT Vol. 14 No. 4 (2026): April: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i4.528

Abstract

Inventory control is a critical aspect in manufacturing companies to ensure the availability of materials and support smooth production processes. Ineffective inventory management can lead to stock shortages or overstock conditions, which may disrupt operational activities. This study aims to develop a web-based inventory control system using the Reorder Point (ROP) method to optimize stock management in a manufacturing environment. The system is designed to monitor stock levels, calculate Average Daily Usage (ADU), safety stock, and reorder points automatically. When stock reaches a predefined threshold, the system provides notifications to assist decision-making in replenishment processes. The development method used in this study is the Waterfall model, including analysis, design, implementation, and testing stages. The system is implemented using the CodeIgniter framework and MySQL database. Testing results show that the system can accurately calculate ROP values and effectively provide early warnings for low stock conditions. Therefore, the proposed system can improve efficiency, reduce the risk of stock shortages, and support better inventory management in manufacturing companies. The system achieved an accuracy rate of 100% in calculating ROP values based on Black Box testing results, and successfully generated real-time notifications for all critical stock conditions. The novelty of this study lies in the integration of threshold-based logic with automated notification features in a web-based system, which provides a more responsive and practical solution compared to previous inventory control approaches that rely on manual monitoring.
The role of social media in improving digital literacy among the Sei Mencirim Village Community, Sunggal District Dasa Syawal Syahputra
Jurnal Mandiri IT Vol. 15 No. 1 (2026): Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v15i1.529

Abstract

Social media is a technological advancement that has become inseparable from modern society. Various benefits have been experienced by the public following the emergence of social media in their daily lives. However, the question remains whether social media has played a positive role in society, particularly in rural communities. This article aims to explore more deeply the role of social media in improving digital literacy among the community in Sei Mencirim Village, Sunggal District. This study employs a qualitative method, with data collected through observations and interviews with residents of Sei Mencirim Village, Sunggal District. The results of this study indicate that social media has contributed to enhancing digital literacy among the community in Sei Mencirim Village, Sunggal District. This is reflected in the community’s good understanding of digital literacy as well as their awareness of not indiscriminately sharing information obtained from social media. However, the amount of content related to digital literacy available across various social media platforms remains limited. Therefore, the government needs to encourage content creators to more actively and extensively produce such content.
Machine learning-based sports preference classification using demographic and behavioral factors Hendra Apriawan; Suhendro Yusuf Irianto
Jurnal Mandiri IT Vol. 15 No. 1 (2026): Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v15i1.530

Abstract

Sports preference is influenced by demographic and behavioral factors, making data-driven classification important for supporting personalized physical activity programs and public health decision-making. However, previous studies have mostly relied on descriptive analysis and have rarely integrated demographic and behavioral variables into a predictive machine learning framework. This study aims to classify community sports preferences using the Naive Bayes algorithm and compare its performance with the Decision Tree model. A quantitative data mining approach was applied using questionnaire data collected from 286 respondents selected from a population of 1,000 individuals using the Slovin formula with a 5% margin of error. The dataset included demographic attributes, such as age, gender, location, occupation, and socioeconomic status, as well as behavioral attributes, including exercise frequency, exercise place, motivation, barriers, and activity preference. Data preprocessing involved data cleaning, attribute transformation, binary label construction, and data leakage removal. Model evaluation was conducted using 10-fold stratified cross-validation with accuracy, precision, recall, F1-score, and Cohen’s kappa. The results show that Naive Bayes outperformed Decision Tree, achieving 63.63% accuracy, 57.84% precision, 56.14% recall, 56.97% F1-score, and 0.132 kappa. These findings indicate that Naive Bayes provides moderate but better predictive performance and can serve as an initial baseline for data-driven sports recommendation systems, although further model development is needed to improve reliability.
Analysis of user satisfaction with the seabank app using support vector machines (SVM) Eko Yulianto; Nanang Nuryadi; Taufik Asra
Jurnal Mandiri IT Vol. 15 No. 1 (2026): Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v15i1.531

Abstract

The development of financial technology (fintech) in Indonesia has driven the rapid growth of digital banks, one of which is SeaBank. User satisfaction with the SeaBank app is a crucial indicator for maintaining customer loyalty amid intense competition. This study aims to analyze user satisfaction with the SeaBank app based on reviews on the Google Play Store using the Support Vector Machine (SVM) method. Review data was classified into positive sentiment (satisfied) and negative sentiment (dissatisfied). The research stages included data collection, rating-based labeling, text preprocessing (including normalization of banking colloquial language), feature extraction using TF-IDF, handling imbalanced data with SMOTE, and classification using an RBF Kernel SVM. The results show that the application of SMOTE successfully addressed class imbalance, and SVM hyperparameter optimization yielded an accuracy of 89.14% with an F1-Score of 88.75%. The analysis findings indicate that the majority of users are satisfied with the convenience of free transactions, but there are significant complaints regarding OTP delays and errors in the login system.
Comparative evaluation of local storage and MinIO object storage for django applications in docker-based environments Hendra Saputra; Faldi Faldi; Wawan Joko Pranoto
Jurnal Mandiri IT Vol. 15 No. 1 (2026): Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v15i1.543

Abstract

Media file management, such as documents and images, was an important aspect of Django-based web application development. Local storage was commonly used to store media files; however, it had limitations in terms of deployment portability, data management, and service continuity in containerized environments. Object storage emerged as an alternative approach by separating file storage from the application layer. This study compared the use of local storage and MinIO object storage in a Django application deployed using Docker containers. A comparative experimental method was employed by implementing both storage approaches on the same application under identical deployment conditions. The evaluation focused on file upload functionality, file accessibility, data persistence after container restart and redeployment, and deployment portability. The results indicated that both approaches successfully stored and provided access to media files. However, MinIO demonstrated advantages in data persistence, storage management, and deployment portability because media files were maintained independently from the application container. In contrast, local storage offered simpler implementation but required additional management during application migration or infrastructure changes. The findings suggested that MinIO object storage was more suitable for Django applications requiring flexible deployment and scalable file management in container-based environments.
Development of a customs-integrated warehouse management system for inbound and outbound goods monitoring Tri Handayani; Mustazzihim Suhaidi
Jurnal Mandiri IT Vol. 15 No. 1 (2026): Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v15i1.545

Abstract

The growth of international trade and customs-related logistics activities has increased the complexity of warehouse operations, particularly in managing inventory, inbound and outbound transactions, and customs document administration. This study aimed to develop a Customs-Integrated Warehouse Management System (CI-WMS) for monitoring inbound and outbound goods in customs-regulated warehouse environments in Dumai. The system was developed using the System Development Life Cycle (SDLC) based on the Waterfall model, which consists of requirements analysis, system design, implementation, and testing stages. The proposed system integrates product management, importer management, customer management, warehouse management, inbound and outbound transaction processing, customs document administration, and reporting functions within a centralized web-based platform. Functional testing was conducted to evaluate the performance of each system module based on predefined requirements. The testing results demonstrated that all modules operated successfully and produced valid outputs. The developed CI-WMS improves inventory visibility, supports inbound and outbound monitoring, enhances goods traceability, and facilitates customs document management within a single integrated system. The proposed system contributes to improving operational efficiency and supporting customs compliance in warehouse operations.

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