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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics 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 INTERNATIONAL JOURNAL OF MECHANICAL COMPUTATIONAL AND MANUFACTURING RESEARCH LEBAH Indonesia Accounting Research Journal Journal of Computer Science and Research International Journal of Enterprise Modelling Journal of Defense Technology and Engineering
Hengki Tamando Sihotang
Universitas Putra Abadi Langkat
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Reconfigurable Metasurface Panels for Active Electromagnetic Shielding of Protective Domes Hengki Tamando Sihotang; Budi Arif Dermawan; Rasenda Rasenda; Galih Prakoso Rizky A
Cebong Journal Vol. 4 No. 3 (2025): July: Green dan Blue Economy
Publisher : IHSA Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cebong.v4i3.420

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 Fristi Riandari; Hengki Tamando Sihotang
International Journal of Basic and Applied Science Vol. 14 No. 2 (2025): Optimization and Computer Science
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 Bambang Saras Yulistiawan; Rifka Widyastuti; Rr Octanty Mulianingtyas; Galih Prakoso Rizky A; Hengki Tamando Sihotang
International Journal of Basic and Applied Science Vol. 14 No. 2 (2025): Optimization and Computer Science
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.
Klinik penulisan artikel ilmiah: Strategi peningkatan kompetensi publikasi masyarakat akademik menuju jurnal terakreditasi Sinta Hengki Tamando Sihotang; Galih Prakoso Rizky A
Lebah Vol. 19 No. 3 (2026): January: Pengabdian
Publisher : IHSA Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/lebah.v19i3.520

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan meningkatkan kompetensi penulisan dan publikasi ilmiah masyarakat akademik menuju jurnal terakreditasi SINTA melalui model Klinik Penulisan Artikel Ilmiah. Latar belakang kegiatan ini adalah rendahnya kemampuan publikasi dosen, guru, dan peneliti muda di daerah akibat keterbatasan kompetensi teknis dan minimnya pendampingan publikasi berkelanjutan. Metode yang digunakan adalah clinic-based training berbasis daring yang mengombinasikan webinar penulisan artikel ilmiah, praktik penulisan berbasis naskah nyata, serta pendampingan teknis submission melalui sistem Open Journal System (OJS). Evaluasi dilakukan menggunakan pre-test, post-test, dan pemantauan luaran publikasi. Hasil kegiatan menunjukkan peningkatan kompetensi peserta secara signifikan, ditandai dengan seluruh peserta (100%) memperoleh skor post-test di atas batas kompetensi minimal dan berhasil melakukan submit artikel ke jurnal ilmiah nasional. Sebagian naskah telah berstatus published dan accepted, sementara lainnya masih dalam tahap review. Kegiatan ini efektif meningkatkan kapasitas publikasi ilmiah dan berpotensi direplikasi sebagai model pengabdian berbasis literasi akademik yang berkelanjutan
Digital propaganda content detection using a transformer-based model on social media platforms Jonson Manurung; Hengki Tamando Sihotang; R. Fanry Siahaan
Journal of Defense Technology and Engineering Vol. 2 No. 1 (2026): July, Journal of Defense Technology and Engineering
Publisher : Fakultas Teknik dan Teknologi Pertahanan, Universitas Pertahanan Republik Indonesia

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Abstract

Digital propaganda on social media has emerged as a critical challenge to democratic stability and national security. Although transformer-based language models have demonstrated promising performance in text classification, their effectiveness for propaganda detection is often constrained by subtle rhetorical manipulation and severe class imbalance, leading to biased predictions toward majority classes. This study addresses these limitations by proposing a fine-tuned RoBERTa-base model integrated with a class-weighted cross-entropy loss to improve the recognition of minority propaganda instances. The model was trained and evaluated on the SemEval-2020 Task 11 sentence-level corpus containing 14,857 annotated sentences, partitioned into 11,886 training samples and 2,971 test samples using stratified sampling. RoBERTa was selected because its robust pre-training strategy and dynamic masking enable more effective contextual representation learning, while class-weighted loss mitigates the adverse effects of the 22.80% to 77.20% class imbalance by assigning weights of 2.19 and 0.65 to the propaganda and non-propaganda classes, respectively. Under identical fine-tuning settings, the proposed model was compared with BERT-base and DistilBERT-base to ensure a fair architectural evaluation. Experimental results demonstrate that RoBERTa achieved the best performance, attaining 93.47% accuracy and a macro-F1 score of 91.82%, outperforming BERT by 1.28 percentage points and DistilBERT by 2.89 percentage points in macro-F1. These findings demonstrate that combining RoBERTa with class-weighted learning provides a robust and practical approach for propaganda detection, supporting the development of automated content moderation and misinformation monitoring systems for social media platforms. Future work will investigate multilingual propaganda detection and fine-grained propaganda technique classification.
Toward an integrated AI-Driven governance architecture for smart cities and digital economy systems Bambang Saras Yulistiawan; Henry Eko Hapsanto; Satriyo Wibowo; Hengki Tamando Sihotang
Indonesia Accounting Research Journal Vol. 13 No. 3 (2026): March: IT Governance, Finance, Accounting, Management
Publisher : Institute of Accounting Research and Novation (IARN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/iacrj.v13i3.665

Abstract

The rapid growth of smart city technologies and digital economy systems has significantly increased the complexity of urban governance, particularly in integrating heterogeneous data sources, supporting intelligent decision-making, and ensuring effective coordination across systems. However, existing approaches often remain fragmented, with limited integration between data infrastructures, artificial intelligence (AI), and governance mechanisms. This study addresses this gap by proposing and evaluating an AI-driven governance architecture designed to integrate smart city systems and digital economy ecosystems into a unified, data-driven framework. This research adopts the Design Science Research (DSR) methodology, encompassing problem identification, objective definition, architecture design, demonstration, evaluation, and communication. The proposed architecture is structured into five interconnected layers: data acquisition, data management, AI intelligence, governance, and service delivery. A demonstration scenario integrating smart mobility and digital economy systems illustrates the operational capabilities of the architecture. The evaluation is conducted using a multi-framework approach, incorporating COBIT, ISO 37120, TOGAF, NIST AI Risk Management Framework, ITIL, and GDPR, combined with expert-based assessment. The results indicate that the proposed architecture achieves a high level of effectiveness, with an overall evaluation score of 4.39, demonstrating strong alignment with governance, architectural, and service requirements. This study contributes by introducing an integrated AI-driven governance model that bridges smart city systems and digital economy ecosystems, enabling adaptive, predictive, and data-driven urban governance. The findings provide both theoretical insights and practical guidance for developing next-generation governance architectures in complex digital environments.
Optimization of logistics distribution costs using the NWCR, MODI, and stepping stone methods Fristi Riandari; Hengki Tamando Sihotang; Hikmah Adwin Adam; Afrisawati Afrisawati
Jurnal Mantik Vol. 10 No. 1 (2026): May : Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v10i1.7177

Abstract

Logistics distribution is a crucial component of the supply chain that impacts a company's operational efficiency. Inaccuracy in allocating goods distribution can increase transportation costs and reduce the effectiveness of distribution services. Therefore, an optimization method capable of producing a distribution pattern with minimum costs is needed. This study aims to analyze the optimization of logistics distribution costs using the North West Corner Rule (NWCR), Modified Distribution Method (MODI), and Stepping Stone methods in determining optimal distribution solutions. The study uses a quantitative approach with a transportation model. The research data include distribution costs, supply capacity, and demand from several warehouses to the distribution area. The initial solution was obtained using the NWCR method, then its optimality was tested using the MODI and Stepping Stone methods. The analysis was carried out by comparing the total distribution costs generated by each method. The results showed that the NWCR method produced an initial solution with a total distribution cost of Rp154,000,000. After optimization using the MODI and Stepping Stone methods, the total distribution cost was successfully reduced to Rp128,500,000, or a savings of 16.56%. The MODI and Stepping Stone methods yield the same optimal solution, but the MODI method has a more efficient iteration process. The combination of the NWCR, MODI, and Stepping Stone methods has been proven to improve the efficiency of a company's logistics distribution costs. This approach can be used as an alternative decision-making tool for optimizing goods distribution and effectively managing the supply chain
Decision Support System for Determining Cyber Risk Mitigation Priorities in Higher Education Using the Fuzzy TOPSIS Method Fristi Riandari; Hengki Tamando Sihotang
Jurnal Teknik Informatika C.I.T Medicom Vol 18 No 2 (2026): May: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

The increasing frequency and sophistication of cyber threats have made higher education institutions attractive targets for cyberattacks, posing significant risks to information assets, academic operations, and institutional reputation. Universities rely heavily on digital technologies, including academic information systems, e-learning platforms, cloud services, and research databases, making effective cybersecurity risk management essential. However, limited cybersecurity resources often prevent institutions from addressing all potential threats simultaneously, highlighting the need for a systematic approach to prioritizing cyber risk mitigation efforts. This study aims to develop a Decision Support System (DSS) for determining cyber risk mitigation priorities in higher education institutions using the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) method. Six evaluation criteria were considered, namely probability of occurrence, financial impact, operational impact, reputation damage, data sensitivity, and recovery complexity. Expert assessments were expressed using linguistic variables and converted into Triangular Fuzzy Numbers (TFNs) to accommodate uncertainty in the decision-making process. The Fuzzy TOPSIS method was then applied to evaluate and rank cyber risks according to their mitigation priorities. The results demonstrated that the proposed DSS successfully generated a prioritized ranking of cyber risks, with ransomware and data breach risks receiving the highest mitigation priorities due to their substantial impacts on university operations, financial resources, and information security. The findings suggest that the developed DSS effectively supports cybersecurity decision-making by handling uncertainty in expert assessments and providing systematic recommendations for cyber risk mitigation. Consequently, the proposed framework can assist higher education institutions in allocating cybersecurity resources more efficiently and enhancing their overall cybersecurity resilience.
Machine Learning Integration in DEA Models: Current Developments and Future Challenges Hengki Tamando Sihotang; Fristi Riandari; Rasenda Rasenda; Wildan Alrasyid
Jurnal Teknik Informatika C.I.T Medicom Vol 18 No 2 (2026): May: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

The increasing availability of large and complex datasets has created new opportunities for enhancing Data Envelopment Analysis (DEA) through the integration of Machine Learning (ML) techniques. This study reviews current developments in the integration of ML and DEA models and identifies key challenges, trends, and future research opportunities. A systematic literature review was conducted by examining recent studies that combine DEA with various machine learning algorithms across multiple application domains, including healthcare, banking and finance, manufacturing, supply chain management, energy, agriculture, and higher education. The findings indicate that Artificial Neural Networks (ANN), Support Vector Machines (SVM), Random Forests, Gradient Boosting methods, and Deep Learning models are among the most frequently employed techniques in DEA-ML frameworks. Despite these advantages, several challenges remain, including data quality issues, model interpretability, computational complexity, limited generalizability, and the lack of standardized integration frameworks. The review concludes that the integration of ML and DEA offers substantial potential for advancing efficiency analysis and organizational performance evaluation. Future research should focus on developing explainable artificial intelligence (XAI) solutions, real-time efficiency analytics, federated learning approaches, and standardized hybrid DEA-ML frameworks to improve transparency, scalability, and practical applicability across diverse operational environments.
Implementasi sistem pengusir tikus sawah berbasis ultrasonik dan iot untuk mengurangi kehilangan hasil panen dan peningkatan ketahanan produksi padi Nurul Afifah Arifuddin; Galih Prakoso Rizky A; Hengki Tamando Sihotang; Fitri Andhika; Praffi Ramadhani; Dara Ramadhani Aresti
Lebah Vol. 20 No. 1 (2026): July: Pengabdian
Publisher : IHSA Institute

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Abstract

Pengabdian kepada Masyarakat (PkM) ini bertujuan menerapkan Sistem Pengusir Tikus Sawah Berbasis Ultrasonik-Internet of Things (IoT) sebagai alternatif pengendalian hama non-kimia sekaligus meningkatkan pengetahuan, keterampilan, dan keberdayaan kelompok tani di Desa Kutamukti, Kecamatan Kutawaluya, Kabupaten Karawang. Kegiatan dilaksanakan pada Poktan Ranca Ekek dan Poktan Mukti Jaya I menggunakan pendekatan partisipatif berbasis kebutuhan mitra melalui tahapan sosialisasi, pelatihan dan workshop, penerapan teknologi, pendampingan dan evaluasi, serta penguatan keberlanjutan program. Teknologi mengintegrasikan ultrasonik 20–65 kHz, suara predator alami, mikrokontroler ESP32/setara berbasis IoT, panel surya, dan baterai. Evaluasi dilakukan menggunakan pre-test dan post-test terhadap 25 responden dengan delapan indikator keberdayaan dan skor maksimum 40. Hasil menunjukkan peningkatan rata-rata skor keberdayaan dari 19,12 ± 1,36 (47,80%) menjadi 35,36 ± 1,44 (88,40%), atau meningkat sebesar 16,24 poin dan 40,60 poin persentase. N-gain deskriptif berdasarkan skor rata-rata kelompok mencapai 0,778. Hasil tersebut menunjukkan adanya peningkatan pengetahuan, pemahaman, kesiapan penggunaan teknologi, dan keterlibatan mitra
Co-Authors A, Galih Prakoso Rizky Achiriani, Tri Wahyuningtiyas Afrisawati Afrisawati Agustina Simangunsong Aisyah Alesha Alrasyid, Wildan Anthoni Anggrawan Anthony Anggrawan Bambang Saras Yulistiawan Bambang Saras Yulistiawan Bosker Sinaga Budi Arif Dermawan Calvin Berkat Iman Hulu Chandra, Suherman Dadang Pyanto Dahayu Annisa Nathania Dara Ramadhani Aresti Delano, Aldrich Desi Vinsensia Dini Anggraini Dwiki Rivaldo Naidu Efendi, Syahril Elpridawati Purba Endang Mistaorina Laia Erwin Panggabean Ezra Natasya.S Fadiel Rahmad Hidayat Firmansyah Firmansyah Fitri Andhika Fransisco alexander Simbolon Fristi Riandari Fristi Riandari Fristi Riandari Fristi Riandari Galih Prakoso Rizky A Galih Prakoso Rizky A Galih Prakoso Rizky A Galih Prakoso Rizky A Galih Prakoso Rizky A Galih Prakoso Rizky A. Guntur Syahputra Harapan Lumbantoruan Harapan Lumbantoruan Harpingka Fitria Br. Sibarani Harpingka Fitriai Br. Sibaran Hasugian , Paska Marto Henry Eko Hapsanto Herlina Zebua Herman Mawengkang Hikmah Adwin Adam Hondor Saragih Husain Husain Hutahaean, Harvei Desmon I Made Aditya Pradhana Putra Jacob, Halburt Jane Irma Sari Jelita Sari Simanungkalit Jijon Raphita Sagala Joan De Mathew Jonhariono Sihotang Jonhariono Sihotang Jonson Manurung Jonson Manurung Jonson Manurung Judijanto, Loso Kharisma Wiati Gusti Kouvelis Geovany Ortizan Laia, Endang Mistaorina Lemos, Sgarbossa Carlo Manurung, Jonson Maria Santauli Siboro Martinus Ndruru Melda Agustina Nababan Michaud, Patrisius Mochamad Wahyudi Muhammad Rafli Muhammad Zarlis Murni Marbun Normi Verawati Marbun Nurul Afifah Arifuddin Panjaitan, Firta Sari Patricius Michaud Felix Patrisia Teresa Marsoit Pilisman Buulolo Praffi Ramadhani Pujiastuti, Lise R. Fanry Siahaan R. Mahdalena Simanjorang Rasenda Rasenda Rasenda Rasenda Rifka Widyastuti Rifka Widyastuti Ririn Pebrina Br. Marpaung Rizky, Galih Prakoso Rohit Gautama Roma Sinta Simbolon Rosulastri Purba RR Octanty Mulianingtyas Rr Octanty Mulianingtyas Santiwati Sihotang Santoso, Heroe Satriyo Wibowo Sethu Ramen 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 Vinsensia, Desi Wildan Alrasyid Wildan Alrasyid Wildan Alrasyid Yudistira Alif Raditya