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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Proceedings of Annual International Conference Syiah Kuala University - Life Sciences & Engineering Chapter Bulletin of Electrical Engineering and Informatics Jurnal Infinity Journal of Telematics and Informatics SAMUDERA Scientific Journal of Informatics CESS (Journal of Computer Engineering, System and Science) Register: Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Teknologi Informasi dan Komunikasi InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Pilar Nusa Mandiri Abdimas Talenta : Jurnal Pengabdian Kepada Masyarakat Jurnal Inotera MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JISTech (Journal of Islamic Science and Technology) Building of Informatics, Technology and Science Jurnal Mantik MES: Journal of Mathematics Education and Science Jurnal Varian International Journal of Advances in Data and Information Systems Computer Science and Information Technologies Journal of Innovation Information Technology and Application (JINITA) Randwick International of Social Science Journal Journal of Research in Mathematics Trends and Technology Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Journal for Lesson and Learning Studies International Journal of Humanities Education and Social Sciences Jurnal MathEducation Nusantara International Journal of Community Service Implementation Jurnal Infinity
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A Data-Driven MINLP Approach for Enhancing Sustainability in Blockchain-Enabled e-Supply Chains Badawi, Afif; Efendi, Syahril; Tulus, Tulus; Mawengkang, Herman
Journal of Applied Data Sciences Vol 6, No 4: December 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i4.889

Abstract

Modern e-supply chains are characterized by increasing complexity and a critical need for enhanced sustainability, transparency, and traceability. Blockchain technology emerges as a significant enabler, offering decentralized, immutable ledgers and smart contracts that can support more secure, verifiable, and environmentally responsible operations through trustworthy data. Despite blockchain's potential, a notable gap exists in the availability of quantitative, data-driven optimization models that rigorously assess the operational and sustainability impacts of its integration into e-supply chains, particularly for complex, non-linear system interactions. This study aims to address this gap by presenting an in-depth analysis of a specific Mixed-Integer Non-Linear Programming (MINLP) optimization model. The goal is to clarify its structure, evaluate its application for an e-supply chain incorporating blockchain features (like transaction costs and conceptual smart contract enforcement for compliance) and sustainability objectives (such as carbon emission reduction), and derive practical insights. The methodology involves a detailed exposition of the MINLP model, followed by its application to a defined e-supply chain scenario. The analytical approach includes computational experiments focusing on a base case analysis to demonstrate model functionality. The broader evaluative framework for this study encompasses benchmarking the model’s performance against a conventional system and conducting sensitivity analyses on key parameters to understand performance trade-offs. The initial base case analysis demonstrates the model's capability to optimize supplier selection and operational plans while adhering to sustainability constraints, such as maintaining carbon emissions at or below 300 kg CO₂ per period, and accounting for blockchain-specific costs like a per-supplier usage fee of 500. The structure of the model and preliminary insights suggest its potential to achieve improved environmental impact compared to conventional systems, balanced against associated blockchain implementation costs. This research provides a detailed examination of a complex MINLP structure, offering a data-driven analytical approach for assessing blockchain's role in sustainable e-supply chains. It furnishes a foundational framework and insights that can guide managerial decisions and strategic planning for industries transitioning towards greener, more transparent, and digitally advanced supply chain operations.
A Data-Driven Mixed Integer Nonlinear Programming Model for Cost-Optimal Scheduling of Perishable Production and Workforce Putri, Mimmy Sari Syah; Mawengkang, Herman; Suwilo, Saib; Tulus, Tulus
Journal of Applied Data Sciences Vol 6, No 4: December 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i4.1019

Abstract

This study presents a data-driven, Mixed Integer Nonlinear Programming (MINLP) framework for optimizing the multi-period production scheduling of perishable products with integrated workforce planning. Its primary novelty is the holistic integration of a continuous exponential decay function for product deterioration with dynamic workforce planning, creating a unified model that optimizes production, inventory, and labor simultaneously. This approach addresses key challenges in perishable inventory systems by treating labor as a controllable resource rather than a fixed constraint. Mathematically, the model includes nonlinear inventory balance equations with decay terms and resource-dependent capacity constraints. The objective is to minimize total operational cost, comprising production, holding, and spoilage costs. Computational experiments, based on a realistic case study, demonstrate that the proposed model reduces total system cost by 6.2% and spoilage costs by 43.2% compared to a standard heuristic benchmark. The resulting production and labor schedules align closely with demand fluctuations, supporting both economic and operational efficiency. This unified framework advances the mathematical modeling of sustainable production planning and offers a practical tool for real-world industries such as food processing and pharmaceuticals.
Mathematical Modeling of the Vehicle Routing Problem with Relaxed Time Windows and Delay Penalties Fitrie, Rosa; Suwilo, Saib; Mawengkang, Herman
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 3 (2025): Article Research July 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i3.14977

Abstract

The Vehicle Routing Problem with Relaxed Time Windows (VRP-RTW) is an extension of the classic Vehicle Routing Problem (VRP) that incorporates flexibility in service time windows. In VRP-RTW, vehicles are allowed to arrive later than the specified time window. However, a violation will be imposed for exceeding the specified time limit. in the form of fines or similar penalties. This research aims to design a mathematical model for VRP-RTW to minimize total travel costs and delay penalties, while ensuring that all customers are served within the capacity limits of the available vehicles. This research uses literature review methods and mathematical formulation approaches to describe the logistics distribution problem. The developed model considers several constraints, such as vehicle capacity, route balance, and service time limitations. The results of this research are expected to contribute to more efficient and flexible logistics distribution decision-making and serve as a basis for the development of vehicle route optimization models that can be applied in real-world scenarios.
Education on community empowerment in prevention of Covid-19 to the community Laut Dendang village, Percut Sei Tuan district Deli Serdang regency Mardiningsih; Suwilo, Saib; Mawengkang, Herman; Sutarman; Marpongahtun
ABDIMAS TALENTA: Jurnal Pengabdian Kepada Masyarakat Vol. 5 No. 2 (2020): ABDIMAS TALENTA : Jurnal Pengabdian Kepada Masyarakat
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (167.727 KB) | DOI: 10.32734/abdimastalenta.v5i2.5069

Abstract

Community Service Activities carried out by the Service Team are intended to achieve the output target of reducing the spread of covid-19 in the people of Laut Dendang Village. The community service team conducts outreach regarding improving the quality of health and education in this village, in this case the Village Head, Hamlet Head, and PKK women become participants in this outreach, so that further all participants can socialize the issue of the importance of preventing Covid-19 and how to do it. prevention. It is hoped that the improvement of the quality of health in this village can be a lesson for the village community to understand and implement all knowledge or rules in reducing or stopping the spread of this deadly virus. This service is aimed at Community Service for the 2020 USU Lecturer Service Scheme is to solve problems together with the community through observation, problem identification, problem formulation, preparation of alternative solutions and evaluation of their implementation.
Teaching Digital Archives Management Using Google Sites, Google Drive, and Gmail Herawati, Elvina; Suwilo, Saib; Mawengkang, Herman; Syahmrani, Aghni
ABDIMAS TALENTA: Jurnal Pengabdian Kepada Masyarakat Vol. 8 No. 2 (2023): ABDIMAS TALENTA: Jurnal Pengabdian Kepada Masyarakat
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/abdimastalenta.v8i2.10444

Abstract

Study plans, study modules, practice questions and exams from teachers, results of student exercises and exams, photos and videos of teaching activities, and other teaching files for each subject are teaching data that can be used to obtain quality education. However, some of the data is not documented by Partners in a systematic and comprehensive manner. If the data is physically collected, it will require a repository for the data, so it will take time to organize the warehouse, search for files, and provide files to teachers or students who need the files. To keep teaching data collected without using physical storage warehouses, digital archiving can be used. Google Sites, Google Drive, and Gmail can be used to build digital archives. The USU Mathematics Master’s Program team plans to build a site through Google Sites to archive digital files and to display digital archives that are stored on Google Drive and which can be submitted via Gmail online. In addition, the Team also provides training for Partners to build and develop sites on Google Sites and perform digital archive management on Google Drive and integrate Google Sites and Google Drive with Gmail.
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.
Evaluating the Impact of Model Complexity on the Accuracy of ID3 and Modified ID3: A Case Study of the Max_Depth Parameter Asrianda, Asrianda; Mawengkang, Herman; Sihombing, Poltak; K. M. Nasution , Mahyuddin
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.4864

Abstract

The complexity of decision tree structures has a direct impact on the generalization capability of classification algorithms. This study investigates and evaluates the performance of the classical ID3 algorithm and its modified version in the context of tree depth. The primary objective is to identify the optimal accuracy point and assess the algorithms' robustness against overfitting. Experiments were conducted across tree depths ranging from 1 to 20, with accuracy used as the main evaluation metric. The results indicate that both algorithms achieved peak performance at depth 3, followed by a notable decline. While the classical ID3 algorithm exhibited a gradual decrease in accuracy, the modified ID3 showed a sharp drop and performance stagnation between depths 11 and 20. These findings suggest that the modified ID3 algorithm enhances sensitivity in selecting informative attributes but also increases the risk of overfitting in the absence of structural regularization mechanisms. Therefore, the study recommends the implementation of regularization strategies such as pruning and cross-validation to mitigate performance degradation caused by model complexity. This research not only contributes to the theoretical understanding of how tree depth influences classification performance but also offers practical insights for developing adaptive, stable, and accurate decision tree-based classification systems.
Development of distance formulation for high-dimensional data visualization in multidimensional scaling Marto Hasugian, Paska; Mawengkang, Herman; Sihombing, Poltak; Efendi, Syahril
Bulletin of Electrical Engineering and Informatics Vol 14, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i2.8738

Abstract

This research aims to produce a new method called pasca-multidimensional scaling (pasca-MDS) by modifying the multidimensional scaling (MDS) method, the developed model comes as a solution to overcome the problem of data complexity by reducing its description dimension without losing important information. This model, offers an innovative approach in dealing with these problems. Pasca-MDS not only focuses on reducing the dimensionality of data, but also retains the essence of relevant information from each data point. As such, it allows for easier and more efficient analysis without compromising the accuracy of the information conveyed. The main advantage of pasca-MDS lies in its ability to produce simpler visual representations while maintaining the original structure of complex data. This provides clarity and ease in understanding the patterns or relationships hidden within. By using adjustment techniques after the MDS process, this model can provide more optimized results. This process allows the adjustment of data points to achieve a better representation in a lower dimensional space, resulting in a more intuitive and easy-to-understand interpretation. The developed distance formula has the ability to minimize stress compared to other distance formulas in MDS space, with the aim of improving the accuracy of high-dimensional data visualization.
Evaluating ERD Models and RAID-Based Storage for Query Performance Optimization in Relational Databases Juanda Hakim Lubis; Sri Handayani; Herman Mawengkang; Yuliska
Journal of Innovation Information Technology and Application (JINITA) Vol 7 No 1 (2025): JINITA, June 2025
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v7i1.2707

Abstract

The amount of data stored in magnetic disks (e.g., floppy disks) increases by 100% each year for each department in a company, necessitating efforts to maintain an optimal database system. Designing a database is the initial step in creating a system with optimal performance. However, database design alone is not sufficient to enhance performance. One approach to improving data transaction speed is by optimizing query processing. This research evaluates different relational database models using varying amounts of data. Query costs are analyzed using the Cost-Based Optimizer method and access time measurements. The results of this study provide insights for database administrators in designing relational database models effectively and selecting appropriate query structures to optimize database performance. The findings indicate that: (1) database design can be optimized by separating entities based on specialized usage, and (2) factors such as record count, attribute size, query type, use of unique or primary keys, order-by clauses, index sequences, and SQL function usage significantly impact query cost and overall performance.
Co-Authors , Rahmad Sembiring Abi Rafdi Afdhaluzzikri, Afdhaluzzikri Afnaria, Afnaria Ahmad Zaki Mubarak, Ahmad Zaki Al Khowarizmi Anggi Anatasia Kinanti Anugreni, Fera Arjon Turnip Asrianda Asrianda Azmi, Zulfian - Badawi, Afif Buaton, Relita Budhiarti, Erna Christefa, Dea Christian Sinaga, Christian Dadang Priyanto Dedi Siswo Defri Muhammad Chan Deny Jollyta Efendi, Syahril Elly Rosmaini Ermawati Ermawati Erna B N Erna Budhiarti Nababan Fatma Sari Hutagalung Firmansyah Firmansyah Firmansyah Firmansyah Fitrie, Rosa Hadistio, Ryan Rinaldi Handayani, Sri Hartama, Dedy Hasugian , Paska Marto Hengki Tamando Sihotang Hengki Tamando Sihotang Heni Pujiastuti Herawati, Elvina Heri Gustami Husain Husain Husain Husain Ignazio Ahmad Pasadana Iin Parlina Indah Purnama Sari Juanda Hakim Lubis Juanda Hakim Lubis K. M. Nasution , Mahyuddin Lestari, Valencya lili Tanti Lismardiana Lismardiana Lusi Herlina Siagian M Safii M Zarlis Mahyuddin K. M Nasution Mardiningsih Mardiningsih, Mardiningsih Marpongahtun Marwan Ramli Maya Silvi Lydia Mochamad Wahyudi Muhammad Arif Satria Nasution Muhammad Zarlis Muhammad Zarlis Muhammad Zarlis Muhammad Zarlis, Muhammad Muliawan Firdaus Napitupulu, Fajrul Malik Aminullah Nuraini Nuraini Oktaviana Bangun Opim Salim Sitompul Ovirianti, Nurul Huda Pasaribu, Suhendri Poltak Sihombing Prandana, Randy Pujiastuti, Lise Putri, Mimmy Sari Syah Rahman, Silvi Anggraini Resti, Lady Ichwana Roma Rezeki Ryan Rinaldi Hadistio Saib Suwilo Saib Suwilo Santoso, Ahmad Imam Sarif, Muhammad Irfan Sawaluddin Nasution Sawaluddin Sawaluddin, Sawaluddin Sri Handayani Sugiyarmasto Sugiyarmasto Sutarman Sutarman Sutarman Sutarman Sutarman Syahmrani, Aghni Syahputra, Muhammad Romi Syahril Effendi Tanjung, Ilyas Tulus Tulus Tulus Tulus Vinsensia, Desi Weber, Gerhard Wilhelm Wiryanto Wiryanto Wisnu Irsandi Pratama Yuliska Zakarias Situmorang Zarkasyi, Muhammad Imam Zarlis, M Zarlis, M Zoelkarnain Rinanda Tembusai Zulfian Azmi