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All Journal International Journal of Electrical and Computer Engineering Register: Jurnal Ilmiah Teknologi Sistem Informasi Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Mantik Penusa JIPN (Journal of Informatics Pelita Nusantara) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer ComTech: Computer, Mathematics and Engineering Applications Jurnal Mantik Jurnal Sains dan Teknologi TRIDARMA: Pengabdian Kepada Masyarakat (PkM) Jurnal Teknik Informatika C.I.T. Medicom Journal of Intelligent Decision Support System (IDSS) INFOKUM Journal of Computer Networks, Architecture and High Performance Computing International Journal of Basic and Applied Science Jurnal Media Informatika Journal Basic Science and Technology Jurnal Mandiri IT CEBONG Journal Journal of Computer Science and Research International Journal of Enterprise Modelling
Hengki Tamando Sihotang
Universitas Putra Abadi Langkat
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Decision Support System to Determine Applicant Housing Credits With SAW Method on the House Complex of J. City Residence by Capital Property Laia, Endang Mistaorina; Sihotang, Hengki Tamando
Journal of Computer Networks, Architecture and High Performance Computing Vol. 2 No. 2 (2020): Computer Networks, Architecture and High Performance Computing
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnapc.v2i2.402

Abstract

J. City Residence provides subsidized housing loans facilities for people who earn below the average. The number of credit applicants with different criteria requires carefulness of the Credit Analyst in making decisions. This problem can be solved by building a Decision Support System (DSS) in determining the provision of subsidized mortgage loans using the Simple Additive Weighting (SAW) method. The criteria used are house condition (cost attribute), income (cost attribute), employment (benefit attribute), credit history (benefit attribute) and marital status (benefit attribute). The process is to normalize the credit applicant value matrix, then multiply the results of the normalization by the weight value. If the result of the calculation is above the credit line is not feasible, then the applicant is declared eligible to receive credit. Application can be used to help to determine the eligibility of consumers in obtaining subsidized housing loans with the SAW method in J. City Residence by Capital Property Housing.
New Method for Identification and Response to Infectious Disease Patterns Based on Comprehensive Health Service Data Desi Vinsensia; Siskawati Amri; Jonhariono Sihotang; Hengki Tamando Sihotang
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 3 (2024)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i3.4000

Abstract

Infectious diseases continue to pose a major threat to global public health and require early detection and effective response strategies. Despite advances in information technology and data analysis, the full potential of health data in identifying disease patterns and trends remains underutilised. This study aims to propose a comprehensive new mathematical model (new method) that utilises health data to identify infectious disease patterns and trends by exploring the potential of data-driven care approaches in addressing public health challenges associated with infectious diseases. The research methods used are exploratory data collection and analytical model development. The research results obtained mathematical models and algorithms that consider data of period, time, patterns, and trends of dangerous diseases, statistical analysis, and recommendations. Data visualisation and in-depth analysis were conducted in the research to improve the ability to respond to infectious disease threats and provide better decision-making solutions in improving outbreak response, as well as improving preparedness in addressing public health challenges. This research contributes to health practitioners and decision-makers.
Vulnerability Analysis and Mitigation Strategies of DDoS Attacks on Cloud Infrastructure Sihotang, Hengki Tamando; Alrasyid, Wildan; Delano, Aldrich; Jacob, Halburt; Rizky, Galih Prakoso
Journal Basic Science and Technology Vol 14 No 2 (2025): June: Basic Science and Technology
Publisher : Institute of Computer Science (IOCS)

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Abstract

As cloud computing becomes increasingly central to modern digital operations, it has also become a primary target for Distributed Denial of Service (DDoS) attacks. This research investigates the major vulnerabilities within cloud infrastructure that are commonly exploited by DDoS attackers and evaluates the effectiveness of various mitigation strategies. The study employs a mixed-methods approach, combining vulnerability assessment, simulated attack scenarios, and comparative performance analysis of traditional and advanced defense mechanisms, including rate limiting, Intrusion Detection Systems (IDS), Software-Defined Networking (SDN), and machine learning-based anomaly detection. The findings reveal that key weaknesses in cloud systems such as shared resource models, unsecured APIs, and auto-scaling configurations can be leveraged to disrupt services or cause economic damage. The comparative evaluation highlights the limitations of conventional tools in handling sophisticated or large-scale attacks, while also showcasing the superior adaptability of SDN and AI-driven techniques under dynamic threat conditions. This research contributes to the field of cloud security by offering a comprehensive understanding of DDoS threat vectors, identifying effective defense combinations, and providing practical recommendations for strengthening the security posture of cloud systems. The study emphasizes the importance of proactive, layered, and intelligent defense frameworks to enhance the resilience of cloud-based infrastructures against evolving DDoS threats.
Reconfigurable Metasurface Panels for Active Electromagnetic Shielding of Protective Domes Sihotang, Hengki Tamando; Dermawan, Budi Arif; Rasenda, Rasenda; Rizky A, Galih Prakoso
Cebong Journal Vol. 4 No. 3 (2025): July: Green dan Blue Economy
Publisher : IHSA Institute

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Abstract

The increasing complexity of electromagnetic (EM) environments in defense and communication systems necessitates shielding solutions that are both adaptive and efficient. Conventional static shielding domes, while effective in blocking electromagnetic interference (EMI), are inherently limited by their fixed frequency response, high structural weight, and lack of real-time adaptability. This research investigates the design and performance of reconfigurable metasurface panels for active electromagnetic shielding of protective domes, with the aim of enhancing shielding effectiveness, tunability, and structural efficiency. The study explores the integration of reconfigurable metasurfaces into dome architectures, enabling dynamic control of electromagnetic wave propagation through electronically tunable elements. Performance metrics including shielding effectiveness (in dB), tunable frequency ranges, angular stability, and real-time adaptability were evaluated and benchmarked against conventional static shielding designs. Results indicate that reconfigurable metasurface domes achieve superior shielding performance across wide frequency bands while offering significant weight reduction and improved adaptability. These characteristics make them well-suited for critical applications such as military radomes, satellite communication shelters, aerospace systems, and secure civilian infrastructures. However, challenges remain regarding large-scale fabrication, integration complexity, power requirements for active tuning, and environmental durability. Despite these limitations, the findings highlight the transformative potential of reconfigurable metasurfaces as the foundation of next-generation adaptive shielding technologies. This research demonstrates that reconfigurable shielding domes not only address the shortcomings of static designs but also pave the way for resilient, flexible, and future-proof electromagnetic protection systems.
Distribution cost optimization: Comparison of NWC, MODI, and Stepping Stone methods in transportation problems Riandari, Fristi; Sihotang, Hengki Tamando
International Journal of Basic and Applied Science Vol. 14 No. 2 (2025): Sep (In Progress)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijobas.v14i2.688

Abstract

Solving transportation problems is essential in minimizing distribution costs in logistics and supply chains. Three classical methods North West Corner (NWC), Modified Distribution Method (MODI), and Stepping Stone are frequently used, but few studies offer a comprehensive comparison. This study fills this gap by evaluating their performance using simulated data representing real-world distribution scenarios. This study applies a structured comparative framework to analyze NWC (a cost-agnostic initial allocation technique), MODI (a dual-variable-based optimization approach), and Stepping Stone (a closed-loop path evaluation method). Each method was tested on a simulated cost matrix using Python. Evaluation metrics included total distribution cost, number of iterations, and computation time. The NWC method yielded a feasible but suboptimal solution with a cost of 540 units. Optimization using MODI reduced the cost to 425, while Stepping Stone further minimized it to 410 after three iterations. MODI showed greater computational efficiency, while Stepping Stone offered visual traceability of cost reductions. This study contributes methodologically by combining heuristic and iterative optimization techniques in one analytical framework. Practically, it provides decision-makers with insights into selecting appropriate solution methods based on trade-offs between simplicity, efficiency, and cost minimization.
A System dynamics quantitative model for enhancing e-government maturity in the indonesian education sector Yulistiawan, Bambang Saras; Widyastuti, Rifka; Mulianingtyas, Rr Octanty; A, Galih Prakoso Rizky; Sihotang, Hengki Tamando
International Journal of Basic and Applied Science Vol. 14 No. 2 (2025): Sep (In Progress)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijobas.v14i2.693

Abstract

This study develops a deterministic mathematical model integrated with system dynamics to measure key success factors driving e-government maturity in Indonesia’s education sector. Addressing the gap in previous research, which mainly relied on descriptive methods, the model quantitatively examines causal relationships among leadership commitment, budget support, digital infrastructure, human capital, service quality, and feedback mechanisms. The methodology involves three stages: (1) constructing a causal loop diagram based on theoretical and empirical insights, (2) converting these relationships into a linear system of equations normalized on a [0–1] scale, and (3) performing simulations and sensitivity analyses to evaluate policy scenarios. Simulation results indicate that even relatively high leadership commitment (K=0.75) only produces moderate maturity levels (M≈0.409). The greatest improvement occurs when feedback loops are reinforced and service quality investments are prioritized. Sensitivity analysis reveals the model is particularly responsive to changes in feedback effectiveness and service quality weighting, identifying these as critical leverage points for accelerating transformation. Under optimal conditions, maturity can increase from 0.41 to 0.48, reflecting a 7% gain over the baseline. The study contributes a replicable quantitative framework for evidence-based policymaking, while noting limitations in parameter assumptions and empirical calibration for future refinement.
New Method for Identification and Response to Infectious Disease Patterns Based on Comprehensive Health Service Data Vinsensia, Desi; Amri, Siskawati; Sihotang, Jonhariono; Sihotang, Hengki Tamando
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 3 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i3.4000

Abstract

Infectious diseases continue to pose a major threat to global public health and require early detection and effective response strategies. Despite advances in information technology and data analysis, the full potential of health data in identifying disease patterns and trends remains underutilised. This study aims to propose a comprehensive new mathematical model (new method) that utilises health data to identify infectious disease patterns and trends by exploring the potential of data-driven care approaches in addressing public health challenges associated with infectious diseases. The research methods used are exploratory data collection and analytical model development. The research results obtained mathematical models and algorithms that consider data of period, time, patterns, and trends of dangerous diseases, statistical analysis, and recommendations. Data visualisation and in-depth analysis were conducted in the research to improve the ability to respond to infectious disease threats and provide better decision-making solutions in improving outbreak response, as well as improving preparedness in addressing public health challenges. This research contributes to health practitioners and decision-makers.
Developing an Enhanced Algorithms to Solve Mixed Integer Non-Linear Programming Problems Based on a Feasible Neighborhood Search Strategy Wahyudi, Mochamad; Firmansyah, Firmansyah; Sihotang, Hengki Tamando; Pujiastuti, Lise; Mawengkang, Herman
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 9 No 2 (2023): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v9i2.3706

Abstract

Engineering optimization problems often involve nonlinear objective functions, which can capture complex relationships and dependencies between variables. This study focuses on a unique nonlinear mathematics programming problem characterized by a subset of variables that can only take discrete values and are linearly separable from the continuous variables. The combination of integer variables and non-linearities makes this problem much more complex than traditional nonlinear programming problems with only continuous variables. Furthermore, the presence of integer variables can result in a combinatorial explosion of potential solutions, significantly enlarging the search space and making it challenging to explore effectively. This issue becomes especially challenging for larger problems, leading to long computation times or even infeasibility. To address these challenges, we propose a method that employs the "active constraint" approach in conjunction with the release of nonbasic variables from their boundaries. This technique compels suitable non-integer fundamental variables to migrate to their neighboring integer positions. Additionally, we have researched selection criteria for choosing a nonbasic variable to use in the integerizing technique. Through implementation and testing on various problems, these techniques have proven to be successful.
A Unified Theoretical-Practical Framework for Explainable Machine Learning in Critical Public Sector Applications Sihotang, Hengki Tamando; Simbolon, Romasinta
Jurnal Teknik Informatika C.I.T Medicom Vol 16 No 4 (2024): September: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

The rapid adoption of machine learning (ML) in the public sector has increased the need for transparent, accountable, and trustworthy algorithmic decision-making, particularly in high-stakes domains such as social welfare, healthcare, security, and public administration. However, existing approaches to explainable machine learning (XML) remain fragmented, focusing primarily on technical explanation techniques without integrating the institutional, ethical, and user-centered requirements of government environments. This research aims to develop a unified theoretical practical framework that operationalizes explainability across the entire ML lifecycle for critical public-sector applications. This study adopts a qualitative, multi-stage research design that combines theoretical synthesis, framework construction, and empirical validation through expert assessment and case-based evaluation.The results demonstrate that explainability is a multidimensional construct that extends beyond algorithmic transparency to include contextual risk assessment, adaptive explanation delivery, and governance mechanisms such as auditability, human oversight, and documentation standards. The proposed framework integrates four interconnected layers context analysis, model design and transparency, explanation delivery, and oversight and governance providing a structured pathway for implementing explainable ML systems that meet public-sector standards of fairness, legitimacy, and accountability. Expert feedback and case evaluations confirm that the framework enhances interpretability, reduces misinterpretation risks, and supports more informed decision-making among stakeholders. This research contributes to the advancement of responsible AI in government by offering a comprehensive model that bridges technical methods with policy and practice, paving the way for more transparent and trustworthy ML adoption in public-sector services.
Developing the Adaptive Digital IT Governance Framework for Next-Generation IT Governance Yulistiawan, Bambang Saras; Widyastuti , Rifka; Mulianingtyas , RR Octanty; A, Galih Prakoso Rizky; Sihotang, Hengki Tamando
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 25 No. 1 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v25i1.5628

Abstract

The increasing complexity of digital transformation requires an adaptive, measurable, and contextaware IT governance model. However, existing frameworks such as COBIT, ITIL, TOGAF, and ISO/IEC 38500 tend to be partial and prescriptive, failing to address strategic, operational, and innovative needs holistically. This study proposes the Adaptive Digital IT Governance Framework, anovel governance model synthesized from eleven leading IT frameworks and structured into three integrated domains: Govern, Manage, and Adapt. Employing a Design Science Research methodology, the model was developed through a systematic framework analysis, conceptual domain formulation, iterative implementation mapping, and the design of a maturity assessment instrument. The results demonstrate that the Adaptive Digital IT Governance Framework offers a modular, scalable, and value-driven governance solution suited for diverse organizational contexts. Theoretical contributions include extending the IT governance paradigm by integrating strategic alignment, agile governance, and digital sustainability. Practically, the framework provides actionable guidance for designing, assessing, and enhancing digital governance systems across sectors. Unlike previous cross-framework synthesis efforts, the Adaptive Digital IT Governance Framework explicitly introduces the Adapt domain, operationalizing governance agility, innovation capability, and sustainability measurement. This makes the Adaptive Digital IT Governance Framework the first modular, maturity-oriented framework that simultaneously integrates strategy, operations, and adaptability, positioning it as a next-generationmodel to support organizational resilience and sustainable digital transformation.
Co-Authors Achiriani, Tri Wahyuningtiyas Agustina Simangunsong Aisyah Alesha Aisyah Alesha Alrasyid, Wildan Amri, Siskawati Anthoni Anggrawan Anthony Anggrawan Bambang Saras Yulistiawan Bosker Sinaga Budi Arif Dermawan Calvin Berkat Iman Hulu Chandra, Suherman Dadang Pyanto Delano, Aldrich Desi Vinsensia Dini Anggraini Dwiki Rivaldo Naidu Efendi, Syahril Elpridawati Purba Endang Mistaorina Laia Erwin Panggabean Fadiel Rahmad Hidayat Firmansyah Firmansyah Fransisco alexander Simbolon Fristi Riandari Guntur Syahputra Harapan Lumbantoruan Harapan Lumbantoruan Harpingka Fitria Br. Sibarani Harpingka Fitriai Br. Sibaran Hasugian , Paska Marto Herlina Zebua Herman Mawengkang Husain Husain Hutahaean, Harvei Desmon Jacob, Halburt Jane Irma Sari Jelita Sari Simanungkalit Jijon Raphita Sagala Joan De Mathew Jonhariono Sihotang Jonhariono Sihotang Judijanto, Loso Kouvelis Geovany Ortizan Laia, Endang Mistaorina Lemos, Sgarbossa Carlo Maria Santauli Siboro Martinus Ndruru Melda Agustina Nababan Michaud, Patrisius Mochamad Wahyudi Muhammad Rafli Muhammad Zarlis Mulianingtyas , RR Octanty Mulianingtyas, RR Octanty Murni Marbun Normi Verawati Marbun Panjaitan, Firta Sari Patricius Michaud Felix Patrisia Teresa Marsoit Pilisman Buulolo Pujiastuti, Lise R. Mahdalena Simanjorang Rasenda, Rasenda Rifka Widyastuti, Rifka Ririn Pebrina Br. Marpaung Rizky A, Galih Prakoso Rizky, Galih Prakoso Rohit Gautama Roma Sinta Simbolon Rosulastri Purba Santiwati Sihotang Santoso, Heroe Sethu Ramen Sihotang , Jonhariono Sihotang, Jonhariono Sim, Lee Choi Simbolon, Agata Putri Handayani Simbolon, Roma Sinta Simbolon, Romasinta Siringoringo, Rimmar Siskawati Amri Sitio, Arjon Samuel Song , Jiang Lou Sri Devi Sulindawaty, Sulindawaty Tarisa Tarigan Teresa, Patrys Vina Winda Sari Vinsensia, Desi Widyastuti , Rifka