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All Journal International Journal of Electrical and Computer Engineering Journal of the Indonesian Mathematical Society Sinkron : Jurnal dan Penelitian Teknik Informatika Building of Informatics, Technology and Science MES: Journal of Mathematics Education and Science Journal of Research in Mathematics Trends and Technology Journal of Applied Data Sciences
Saib Suwilo
Department of Mathematics, University of Sumatera Utara
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Mathematics

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Integer Linear Programming Model for Multicast Routing to Minimize Link Cost at Wavelengths Fitria, Rizka; Suwilo, Saib; Rosmaini, Elly
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12591

Abstract

Routing is a technique or process carried out in a packet or information delivery system from a source to a destination or a place that requests the information needed from a source. Routing is done in solving a problem and is well-known is unicast routing. Unicast routing can transmit information from a source to a single destination. However, this is ineffective for an infinite number of requests to be served because the unicast routing system only funnels one destination to one source. So that another route is needed that can handle this, this route is called a multicast route. Multicast routing that can serve multiple destinations with only one source so that a collection of destinations to get the same request in the same time and data. This research will discuss multicast routing to minimize link costs at wavelengths using a hierarchical structure. To help provide reduction or savings on the link by offering an integer linear programming model formulation to minimize link costs at wavelengths. An update from previous studies is to use a hierarchical structure with wavelength conversion taking into account the links that are traversed and the requests that will be served by the source to the destination. Using wavelength conversion so that there are no wavelength continuity problems, so that when sending information you get more path choices and you can save on sending information using a link that will be passed from the source to the intermediate node until it reaches the destination node, with this it will find a path more efficiently so that the goal of minimizing link cost at wavelengths on multicast routing is achieved
A Class of Primitive Two-Colored Digraph with Large Competition Index Rezeki, Ema Sri; Suwilo, Saib; Mardiningsih, Mardiningsih
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12744

Abstract

The competition index of a primitive two-colored digraph D^2, denoted k(D^((2))), is the smallest positive integer h+l such that for each pair of vertices u and v there is vertex w with the property that there is a (h,l)-walk from v to w. For two-colored digraph on n vertices it is known that k(D^((2) ))≤(3n^3+2n^2-2n)/2. In this work, we discuss a class of primitive two-colored digraph consisting of two cycles whose scrambling index closes to (3n^3+2n^2-2n)/2
Enhancing Vehicle Routing Efficiency through Branch and Bound and Heuristic Methods Mubarak, Ahmad Zaki; Mawengkang, Herman; Suwilo, Saib
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.13759

Abstract

The Vehicle Routing Problem (VRP) is a critical challenge in logistics, impacting delivery efficiency and costs. Traditional VRP solutions often fail to address real-world dynamics such as fluctuating traffic conditions and varying customer demands. This research proposes a novel VRP model integrating real-time data to enhance route optimization. By combining the precision of the Branch and Bound (B&B) approach with the flexibility of heuristics like Genetic Algorithms and Simulated Annealing, the hybrid method dynamically adjusts routes based on live traffic and demand updates. The objective is to reduce operational costs and improve logistical performance. The hybrid model’s effectiveness is validated through comparative analysis with traditional VRP solutions, demonstrating significant improvements in cost reduction, fuel consumption, vehicle wear and tear, and customer satisfaction due to timely deliveries. These advancements highlight the potential of real-time data integration and advanced optimization techniques in providing robust solutions for modern logistics challenges. Future research should focus on incorporating more advanced data sources and testing the model in various real-world scenarios to further enhance its practicality and performance, ensuring businesses remain competitive in a dynamic market. This study underscores the importance of continuous innovation in VRP solutions to achieve sustainable, efficient, and customer-centric logistics operations.
Optimization Model for Relief Distribution After Flood Disaster Pujiana, Perli; Suwilo, Saib; Mardiningsih
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.13769

Abstract

Logistics planning is critical and a key component in meeting initial emergency needs in the aftermath of a disaster. The rapid and efficient distribution of logistical aid becomes critically important. In such situations, the construction of temporary depots in strategic locations and the determination of optimal distribution routes play an important role in ensuring that logistics aid can be distributed to the affected areas evenly. In this study, the Multi Depot Vehicle Routing Problem (MDVRP) is used which aims to minimize the total cost of distributing logistics aid which includes shipping costs, vehicle usage costs, temporary depot construction costs, and vehicle travel costs from distribution centers to temporary depots, while still meeting constraints such as logistics aid demand, vehicle capacity, area visits, maximum mileage, and depot construction. This model uses two types of vehicles where vehicle  is tasked with carrying logistics aid from the distribution center to the temporary depot and vehicle  is tasked with delivering logistics aid directly to the point of demand.
Strategic plant maintenance planning in agriculture by integrating lean principles and optimization Simarmata, Gayus; Suwilo, Saib; Sitompul, Opim Salim; Sutarman, Sutarman
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp6279-6286

Abstract

Operational planning within agricultural production systems plays a pivotal role in facilitating farmers' decision-making processes. This study introduces a novel mathematical model aimed at optimizing plant maintenance planning through the efficient allocation of labor, optimal utilization of machinery, and strategic scheduling. Utilizing mixed integer non-linear programming (MINLP), the model integrates lean principles to minimize waste and improve operational efficiency. The primary contributions of this study include the development of a comprehensive maintenance planning model, the application of advanced mathematical techniques in agriculture, and the enhancement of resource allocation strategies. The results demonstrate significant improvements in maintenance task scheduling, reduced downtime, and enhanced productivity, ultimately contributing to sustainable farming practices and food security. This model serves as a strategic decision-support tool for farmers, enabling data-driven planning and resource utilization to achieve both short-term efficiency and long-term agricultural viability.
The role of Louvain-coloring clustering in the detection of fraud transactions Mardiansyah, Heru; Suwilo, Saib; Nababan, Erna Budhiarti; Efendi, Syahril
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp608-616

Abstract

Clustering is a technique in data mining capable of grouping very large amounts of data to gain new knowledge based on unsupervised learning. Clustering is capable of grouping various types of data and fields. The process that requires this technique is in the business sector, especially banking. In the transaction business process in banking, fraud is often encountered in transactions. This raises interest in clustering data fraud in transactions. An algorithm is needed in the cluster, namely Louvain’s algorithm. Louvain’s algorithm is capable of clustering in large numbers, which represent them in a graph. So, the Louvain algorithm is optimized with colored graphs to facilitate research continuity in labeling. In this study, 33,491 non-fraud data were grouped, and 241 fraud transaction data were carried out. However, Louvain’s algorithm shows that clustering increases the amount of data fraud of 90% by accurate.
Combination Multilayer Fuzzy Inference System with K-means for Classification of Dental Diseases Prandana, Randy; Mawengkang, Herman; Suwilo, Saib
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5737

Abstract

This study was conducted to solve the problem of classifying dental diseases such as pulpitis, gingivitis, periodontitis and advanced periodontitis. The method in this study uses a combination of algorithms with a multilayer system where in the first layer a fuzzy inference will be carried out whether a patient is suffering from pulpitis. Early symptoms of pulpitis are characterized by pain with varying levels. Meanwhile, in the second layer a fuzzy inference process will also be carried out to identify other types of dental diseases, but in this second layer the centroid value calculation process is carried out using the K-means algorithm for all input variables. Then the inference process will run to determine the type of disease suffered by the patient following the fuzzy set of other types of diseases. This study is expected to contribute to helping the initial screening process for dental diseases so that it is easier for dentists to carry out further examinations. The results of this study have been proven to be able to help doctors in conducting initial screening to determine dental disease. In this study, the multilayer system is intended to differentiate the results of dental disease classification because pulpitis does not have a relationship between input variables and other types of dental disease. Meanwhile, the use of the fuzzy inference system method in this study showed good results because the FIS method can map the level of pain suffered by a patient with mild, moderate and severe levels into a numeric value that can be classified where the level of pain is a feeling that cannot be calculated, by using the fuzzy method, the linguistic value can be defined into a conclusion. Grouping input values by finding the means value in the second layer and combined with the fuzzy method has been proven to provide good results for determining the type of dental disease.
A Multi-Objective Decomposition Model for Integrated Urban Transit Line Planning and Passenger Routing Hasibuan, Shubuhan Syukri; Suwilo, Saib; Mardiningsih, Mardiningsih
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 2 (2025): Research Articles April 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i2.14803

Abstract

: Urban public transport networks must balance traveler convenience with tight budgetary and capacity constraints. This study develops a comprehensive multi-objective integer programming framework that unifies line selection, frequency setting, and passenger routing to minimize door-to-door travel time and operating cost while respecting vehicle capacities and limiting transfers. The model is solved using a Dantzig–Wolfe decomposition approach with linear-programming relaxation, which enables tractable solutions on realistically scaled networks. To reflect real-world commuting behavior, three increasingly sophisticated formulations are proposed: a Basic Line Planning Model, a Direct Connection Capacity Model, and a Change-and-Go Model that embeds walking and waiting penalties. On a six-edge, four-node network with 6,000 passenger trips, the Change-and-Go Model emerges as the most effective, reducing average travel time by 47%, halving transfers, and increasing cost by only 11% compared to the incumbent plan. Sensitivity analysis reveals that the model remains robust under varying demand levels and cost–time priorities. The proposed framework thus offers a scalable and passenger-friendly decision-support tool that significantly improves public transport efficiency with moderate investment, making it especially valuable for urban transit agencies seeking to modernize their services.
Analysis of Rainfall Transition Probability Using Markov Chain Method Pasaribu, Suhendri; Suwilo, Saib; Mawengkang, Herman
Journal of Research in Mathematics Trends and Technology Vol. 7 No. 2 (2025): Journal of Research in Mathematics Trends and Technology (JoRMTT)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jormtt.v7i2.21719

Abstract

This research applies the Markov Chain model to examine daily rainfall data in Medan City. Markov chain is one of the methods used for forecasting in various fields, such as economics, industry, and climate. This research uses secondary data of daily rainfall intensity from the BMKG Station of the Center for Meteorology, Climatology and Geophysics Region I. The purpose of this research is to determine the transition probability (probability of transition). This study aims to determine the chance of transition (displacement) of daily rainfall intensity, There are four conditions of rainfall intensity that are categorized, namely no rain, light rain, moderate rain, and heavy rain. The Markov Chain method used is the Champman- Kolmogorov Equation and the steady state equation. The fixed probability of not raining is 59.16%, the fixed probability of light rain is 17.67%, the fixed probability of moderate rain is 16.28%, and the fixed probability of heavy rain is 6.86%.
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.
Co-Authors Aghni Syahmarani Aghni Syahmarani Ahmad Zaki Mubarak, Ahmad Zaki Christy, Claudia Efendi, Syahril Elly Rosmaini Erna Budhiarti Nababan Feren, Feren Gayus Simarmata, Gayus Harahap, Desti Alannora Hasibuan, Shubuhan Syukri Herman Mawengkang Mardiansyah, Heru Mardiningsih Mardiningsih , Mardiningsih Mardiningsih Mardiningsih Muhammad Zarlis, Muhammad Nasution, Putri Khairiah Opim Salim Sitompul Pasaribu, Suhendri Prandana, Randy Pujiana, Perli Pulungan, Annisa Fadhillah Putri, Mimmy Sari Syah Rezeki, Ema Sri Riansyah, Muhammad Rizka Fitria, Rizka Rumahorbo, Yuli Sukiman, T. Sukma Achriadi Sutarman Sutarman Tarigan, Aam Jon Mintase Tarigan, Ruffiana Tulus Tulus Yanti, Maulida