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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 217 Documents
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Decision-making model for cadet selection using the AHP TOPSIS method Tsany, Tazky; Manurung, Jonson; Prabukusumo, M. Azhar
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.v14i3.486

Abstract

Cadet selection in defense institutions requires a comprehensive assessment process because it must cover the academic, psychological, health, physical, and ideological integrity aspects of prospective participants. This multidimensional complexity poses challenges in producing decisions that are objective, consistent, and free from assessor bias. Therefore, a quantitative approach-based evaluation model is needed that can integrate all assessment components in a measurable manner. This study developed a cadet selection decision-making model using a combination of the Analytical Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. AHP is used to determine the weight of importance of the seven main criteria: Academic Potential Test, Academic Interview, Psychological Test, Ideological Mental Test, Ideological Mental Interview, Health Test, and Physical Test, while TOPSIS is used to determine the ranking of candidates based on their proximity to the ideal profile of a cadet. The results of the study show that the integration of AHP–TOPSIS is able to provide evaluation results that are more objective, transparent, and accountable than conventional assessments. In addition to formulating a selection model, this study also discusses alternative methods in multi-criteria decision making as material for developing a selection system in the future. Overall, this model is expected to become a scientific basis for defense institutions in improving the quality and accuracy of the cadet selection process.
Mixed integer linear programming for cadet dormitory placement at Indonesia Defense University Pradhana Putra, I Made Aditya; Manurung, Jonson; Saragih, Hondor
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.v14i3.487

Abstract

Cadet dormitory placement at Indonesian Defense University was currently performed manually by administrative staff, resulting in potential inefficiencies in room assignments regarding walking distance, study program cohesion, and cadet preferences. This research developed a Mixed Integer Linear Programming (MILP) optimization model to automate and improve the dormitory assignment process for military education institutions. The general framework addresses 1,550 cadets distributed across four cohorts and 13 study programs in   dormitory buildings with standardized configurations (3 floors, 25 rooms per floor, 2 cadets per room). The MILP model incorporated three objectives: minimizing total walking distance to academic facilities, maximizing study program cohesion by concentrating programs within specific floors, and maximizing cadet floor preference satisfaction. The model was formulated with configurable weight parameters (w₁, w₂, w₃) enabling administrators to balance competing objectives according to institutional priorities. A validation case study with 38 male cadets from two study programs demonstrated computational feasibility, with the CBC solver achieving optimal solutions in 0.34 seconds (strict constraint approach) and 0.11 seconds (maximum occupancy approach) on standard desktop hardware, both with 0.00% MIP gap confirming proven optimality. The validation study compared two policy approaches: strict constraint enforcement achieving 95% room occupancy with 20 rooms, and maximum space utilization achieving 100% occupancy with 19 rooms. This research contributed the first application of MILP optimization to military education dormitory management in Indonesia, providing a scalable framework with empirical validation for computational tractability and a replicable methodology for resource allocation optimization in defense institutions.
Mapping monthly consumer purchasing patterns at the UNHAN RI Cooperative using time series analysis and LSTM Sigalingging, Miranda Bintang Maharani; Prabukusumo, M. Azhar Prabukusumo; Manurung, Jonson
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.v14i3.488

Abstract

This study investigated the monthly purchasing patterns of consumers at Koperasi Unhan RI and developed forecasting models to support data-driven inventory and procurement planning. Historical cooperative sales data from 2020–2024 were analyzed using time series decomposition, autocorrelation analysis, ARIMA modeling, and a Long Short-Term Memory (LSTM) neural network. The analysis revealed a clear upward trend and strong annual seasonality, with consistent demand peaks occurring in December. The ARIMA model achieved significantly lower prediction errors than the LSTM model and successfully captured both trend and seasonal components. A 12-month forecast for 2025 was then generated to support operational decision-making. The forecasting results provide practical managerial insights for cooperative management, particularly in optimizing inventory levels, scheduling procurement, and anticipating seasonal demand fluctuations. The novelty of this study lies in the comparative application of classical time-series and deep learning approaches within a cooperative context using limited historical data, demonstrating that ARIMA remains a robust and interpretable solution for small to medium-sized cooperative environments. This research concludes that time series analysis combined with ARIMA forecasting effectively mapped consumer purchasing patterns and produced actionable demand predictions for the subsequent year.
Automated news monitoring and sentiment analysis system using web scraping and large language models Naibaho, Zerusealtin David; Saragih, Hondor
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.v14i3.492

Abstract

Organizations increasingly require efficient systems to monitor and analyze vast online news data for timely and informed decision making. Manual monitoring is inadequate due to information overload and the time sensitive nature of digital content. This study presents the design, development, and evaluation of an automated web based news monitoring and sentiment analysis system integrating web scraping and artificial intelligence. The system was implemented using the Django web framework with a PostgreSQL database, Playwright browser automation for dynamic content extraction, and Google’s Gemini API for contextual sentiment classification. Three main functions were developed: automated data collection based on keywords and date ranges, AI driven sentiment analysis producing positive, negative, or neutral labels with contextual understanding, and automated reporting with interactive visualizations exportable to XLSX and CSV formats. Functional black box testing confirmed 100% success across 28 test cases, verifying reliability in authentication, data acquisition, sentiment analysis, and visualization. Performance evaluation showed that the system could collect 50–200 articles within 2–4 minutes and process sentiment analysis at 1–2 seconds per article. The proposed system effectively transforms manual workflows into fully automated operations, enabling systematic media monitoring, sentiment tracking, and data driven decision support.
AI-based cyber patrol system for media sentiment analysis on online news regarding the Indonesian Air Force Setyawan, Muhammad Iqbal; Mardamsyah, Adam; Anindito, Anindito; Budiman, Dwi Cahyo
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.v14i3.497

Abstract

This study presents the development of an adaptive cyber patrol system designed to assist the Indonesian Air Force in monitoring the rapidly changing dynamics of public information. The system aims to detect issues that may influence strategic perception and operational readiness by automatically tracking online news sources across Indonesia. The integrated framework automates the collection, Analysis, and reporting process ranging from identifying viral phrases and performing sentiment Analysis to generating tactical reports for Download. Artificial intelligence techniques are employed to expand keyword coverage, ensure the timeliness of information, and assess the relevance and coherence of collected content. Evaluation results indicate that the system operates reliably and produces well-structured outputs. Overall, this research offers a modular integration of AI, information Analysis, and automated reporting that can be further developed toward predictive and multi-tenant analytics in the future.
A location-based application for public facility damage reporting in Manado City Palilingan, Kenneth; Joshua, Salaki Reynaldo; Lengkong, Salvius
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.v14i3.502

Abstract

This study presents the design and development of a Location Based Service (LBS)-based public facility damage reporting application for Manado City to address limitations in conventional public reporting mechanisms. The novelty of this research lies in the integration of real-time spatial reporting with the Rapid Application Development (RAD) method, enabling iterative and user-centered prototype development tailored to local government public service workflows. The RAD approach was implemented through iterative stages of requirement analysis, system design, prototyping, and evaluation involving user participation. The developed prototype enables users to submit damage reports with automatic GPS-based location detection, photographic evidence, and report status tracking. Functional evaluation using black box testing showed that all core user-side features operated successfully according to the defined requirements. Scenario-based testing involving six respondents indicated that report submission, location detection, and information display functions executed correctly under normal operating conditions. The results demonstrate that the proposed prototype improves the accuracy of reported locations and simplifies the public reporting process. Overall, this study highlights the potential of integrating LBS technology with the RAD approach to support responsive digital public service management and strengthen community participation in urban infrastructure monitoring within the local context of Manado City.
Minimize shipping costs from multi-warehouse to multi-outlet with VAM and MODI Riandari, Fristi; Zain, Ruri Hartika
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.v14i3.506

Abstract

Distribution costs are a dominant component in logistics operations, especially in multi-warehouse to multi-outlet delivery schemes involving variations in supply capacity, demand, and route costs. This study aims to minimize shipping costs by modeling the problem as a Transportation Problem (TP), generating an initial solution using Vogel's Approximation Method (VAM), and ensuring an optimal solution using the Modified Distribution Method (MODI). The case study was conducted in one planning period with input data in the form of a matrix of shipping costs per unit, supply capacity per warehouse, and demand per outlet (balanced condition). The results show that the baseline distribution cost is 4,898 (thousand IDR), while the initial VAM solution reduces the cost to 3,777 (thousand IDR). After optimality testing and improvements using MODI, the minimum cost is 3,605 (thousand IDR), with an additional improvement of 172 (thousand IDR) from the VAM solution. Compared to the baseline, the optimal solution provides savings of 1,293 (thousand IDR) or 26.40%, without violating the supply-demand constraint. These findings confirm that the VAM-MODI flow is effective as a fast, audit-friendly, and applicable end-to-end procedure for the preparation of minimum cost delivery plans in logistics companies.

Page 22 of 22 | Total Record : 217

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