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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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Support Vector Machine Using A Classification Algorithm Ovirianti, Nurul Huda; Zarlis, Muhammad; Mawengkang, Herman
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11597

Abstract

Support vector machine is a part of machine learning approach based on statistical learning theory. Due to the higher accuracy of values, Support vector machines have become a focus for frequent machine learning users. This paper will introduce the basic theory of the Support vector machine, the basic idea of classification and the classification algorithm for the support vector machine that will be used. Solving the problem will use an algorithm, and prove the effectiveness of the algorithm on the data that has been used. In this study, the support vector machine has obtained very good accuracy results in its completion. The SVM classification uses kernel RBF with optimum parameters Cost = 5 and gamma = 2 is 88%.
Data-Driven Decision Making In Large Scale Production Planning Christefa, Dea; Mawengkang, Herman; Zarlis, Muhammad
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11600

Abstract

Production planning is a very important part for a company in making the right decisions before carrying out production activities in order to obtain maximum profit with a minimum level of production costs. Production planning is defined as a process in producing goods and services within a certain period by considering resources such as labor, materials, machinery and etc. In this research, a production planning model is produced based on several variables and parameters that can assist in making production decisions
Artificial Neural Network Backpropagation Method to Predict Tuberculosis Cases Lestari, Valencya; Mawengkang, Herman; Situmorang, Zakarias
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i1.11998

Abstract

Artificial neural networks are information processing systems that have certain performance characteristics in common with biological neural networks. Backpropagation is a method in artificial neural networks that uses supervised learning. Backpropagation has a weakness in reaching the convergence level. The convergence rate is the difference from the mean square error value. The mean square error is the difference between the target value and the actual value. One way to increase the convergence rate is to provide input values. in this study using the nguyen widrow backpropagation method. The network will predict Tuberculosis cases. Data sourced from the North Sumatra Provincial Health Office from 2019 to 2021. architectural testing with a learning rate ranging from -0.5 to 0.5 and momentum ranging from 0 to 1 obtained a learning rate of 0.5, the epoch process stops at the 172nd iteration with an achievement gradient of 0.0001598 and the R value for training data is 0.99841 which means it is very good because it is close to 1 with an accuracy rate of 81.82%.  
Non-Holonomic Robot Navigation Path Planning Using Fuzzy - Steepest Ascent Hill Climb Gustami, Heri; Mawengkang, Herman; Budhiarti, Erna
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i1.12052

Abstract

Robot navigation is determination position as well as direction movement in a trip . Planning track is matter most important in the world of mobile robots. in short , determination track will produce dynasty that can traversed (feasible) with availability information that has there is that is map robotic environment . modelling environment map is step first for determine path planning. on the contrary for environment that doesn't known , modeling will done with the information obtained from the sensors on the robot . on the environment actually , noise and limitations accuracy from the sensor leads to the most basic problem in modeling, that is accuracy , and speed , where influence system navigation live in real-time. For resolve matter the needed the existence of a Fuzzy Description Environment which consists of over the fuzzy model of information obtained in the environment around robots. of these models will Becomes base reference path planner that is used reference to path planning. From the map environment modeling will processed by Steepest Ascent Hill Climb so produce track going to point end . From the results program simulation is obtained waypoints with _ distance shortest that is 363.2724 units distance
Direct Search Techniques for Mixed Stochastic Nonlinear Programming Model Tanjung, Ilyas; Mawengkang, Herman; Sawaluddin, Sawaluddin
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.v8i3.12542

Abstract

Stochastic programming is a methodology utilized for the purpose of achieving optimal planning and decision-making outcomes when faced with uncertain data. The subject of investigation pertains to a stochastic optimization problem wherein the results of stochastic data are not disclosed during runtime, and the optimization of the decision does not necessitate foresight into forthcoming outcomes. This establishes a strong correlation with the imperative need for immediate optimization in uncertain data settings, enabling effective decision-making in the present moment. The present study introduces a novel methodology for achieving global optimization of the model for nonlinear mixed-stochastic programming problem. The present study centers on stochastic problems that are two-staged and entail non-linearities in both the objective function and constraints. The first stage variables are discrete in nature, whereas the second stage variables are a combination of continuous and mixed types. Scenario-based representations are utilized for formulating problems. The fundamental approach to address the non-linear mixed-stochastic programming problem involves converting the model into a deterministic non-linear mixed-count program that is equivalent in form. The feasibility of this proposition stems from the discrete distribution assumption of uncertainty, which can be represented by a limited set of scenarios. The magnitude of the model size will increase significantly due to the quantity of scenarios and time horizons involved. The utilization of filtered probability space in conjunction with data mining techniques will be employed for the purpose of scenario generation. The methodology employed for addressing nonlinear mixed-integer programming problems of significant scale involves elevating the value of a non-basic variable beyond its boundaries in order to compel a basis variable to attain a cumulative value. Subsequently, the problem is simplified by maintaining a constant count variable and modifying it incrementally in discrete intervals to achieve an optimal solution at a global level.
Mathematical Model for Vehicle Routing and Scheduling with Forward and Reverse Logistics Resti, Lady Ichwana; Mawengkang, Herman; 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.v8i3.12599

Abstract

Companies usually use cross-docking to reduce logistics costs. The product delivery process from suppliers to retailers and vice versa is facilitated by crossdocking facilities. One of important problem in crossdocking is vehicle routes. In this work we discuss about cross-docking problem for vehicle routes which is brought into the form of an integration model. We also present the strategy to handle the forward and reverse logistics. From this strategy we have a NP-hard mathematical model as the result.
Mathematical Modelling In Logistics Transportation Problems with The Direct Search Rahman, Silvi Anggraini; Mawengkang, Herman; Sutarman, Sutarman
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.v8i3.12601

Abstract

Migration of rural communities to cities increases logistics activities in urban areas to meet customer needs because there is a close relationship between economic expansion and usage. Daily fluctuating demand for logistics, uncertain driving times and insufficient parking spaces are some of the factors that link the crisis in urban logistics in urban areas, which directly affects operational costs, the environment and its success or failure. The related steps of modeling optimization have a major impact in making complex transportation and logistics systems competitive with each other. This paper proposes a model optimization to solve transportation problems mathematically. The integer programming model would be suitable for the problems that have been described. the author uses direct search to complete the model.
Simplifying Complexity: Scenario Reduction Techniques in Stochastic Programming Sinaga, Christian; Tulus, Tulus; Mawengkang, Herman
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.v8i3.12753

Abstract

Stochastic programming problems arise as mathematical models for optimizing problems under stochastic uncertainty. Computational approaches for solving these models often involve approximating the underlying probability distribution with a probability measure that has finite support. To mitigate the computational complexity associated with increasing the number of scenarios, it may be necessary to reduce their quantity. The scenario is selected as the first element of supp , and the separable structure is used to determine the second element of supp while keeping the first element fixed. The process is repeated to establish the remaining indices, and each subsequent scenario is reduced accordingly. This iterative process continues until scenario is reduced
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.
Measurement by applying internet financial reporting on the level of information presentation in the competitive FinTech peer-to-peer lending industry Al-Khowarizmi, Al-Khowarizmi; Efendi, Syahril; Nasution, Mahyuddin Khairuddin Matyuso; Mawengkang, Herman
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i1.pp66-73

Abstract

Technological advances in the financial sector can certainly support the business decision-making process. Moreover, digital financial technology such as FinTech is a competitive industry that has both peer-to-peer (P2P) and merchant pillars. The industry must update its business activities through its information media. One of them is internet-based financial reporting or better known as internet financial reporting (IFR). IFR itself is a delivery of financial information that is carried out in real time and can be easily seen by the wider community by using the website as a medium. This study aims to determine whether the application of IFR to FinTech P2P Lending companies in Indonesia has been widely implemented or not. Later the variables used in this study are content, appearance, and timing with a total of 20 indicator variable items to be tested. The results of this paper show that 30 P2P lending FinTech Industries in Indonesia have been able to implement IFR with an average score of 80%. IFR scores obtained by each industry have almost the same value ranging from 65% to 95% with the highest total score of 95% and the lowest score of 65%.
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