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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) 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 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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Journal : International Journal of Electrical and Computer Engineering

Analysis of earthquake hazards prediction with multivariate adaptive regression splines Dadang Priyanto; Muhammad Zarlis; Herman Mawengkang; Syahril Efendi
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2885-2893

Abstract

Earthquake research has not yielded promising results, either in the form of causes or revealing the timing of their future events. Many methods have been developed, one of which is related to data mining, such as the use of hybrid neural networks, support vector regressor, fuzzy modeling, clustering, and others. Earthquake research has uncertain parameters and to obtain optimal results an appropriate method is needed. In general, several predictive data mining methods are grouped into two categories, namely parametric and non-parametric. This study uses a non-parametric method with multivariate adaptive regression spline (MARS) and conic multivariate adaptive regression spline (CMARS) as the backward stage of the MARS algorithm. The results of this study after parameter testing and analysis obtained a mathematical model with 16 basis functions (BF) and 12 basis functions contributing to the model and 4 basis functions not contributing to the model. Based on the level of variable contribution, it can be written that the epicenter distance is 100 percent, the magnitude is 31.1 percent, the location temperature is 5.5 percent, and the depth is 3.5 percent. It can be concluded that the results of the prediction analysis of areas in Lombok with the highest earthquake hazard level are Malaka, Genggelang, Pemenang, Tanjung, Tegal Maja, Senggigi, Mangsit. Meninting, and Malimbu.
A stochastic approach for evaluating production planning efficiency under uncertainty Mochamad Wahyudi; Hengki Tamando Sihotang; Syahril Efendi; Muhammad Zarlis; Herman Mawengkang; Desi Vinsensia
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i5.pp5542-5549

Abstract

Planning production is an essential component of the decision-making process, which has a direct bearing on the effectiveness of production systems. This study’s objective is to investigate the efficiency performance of decision-making units (DMU) in relation to production planning issues. However, the production system in a manufacturing environment is frequently subject to uncertain situations, such as demand and labor, and this can have an effect not only on production but also on profit. The robust stochastic data envelopment analysis model was proposed in this study with maximizing the number of outputs as the objective function thus means of handling uncertainty in input and output in production planning problems. This model, which is based on stochastic data envelopment analysis and a method of robust optimization, was proposed with the intention of providing an efficient plan of production for each DMU of stage production. The model is applied to small and medium-sized businesses (SMEs), with inputs consisting of the cost of labor, the number of customers, and the quantity of raw materials, and the output consisting of profit and revenue. It has been demonstrated through implementation that the proposed model is both efficient and effective.
Discrete optimization model for multi-product multi-supplier vehicle routing problem with relaxed time window Firdaus, Muliawan; Mawengkang, Herman; Tulus, Tulus; Sawaluddin, Sawaluddin
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i1.pp592-603

Abstract

This study examines the complicated logistics optimization issue known as the vehicle routing problem for multi-product and multi-suppliers(VRP-MPMS), which deals with the effective routing of a fleet of vehicles to convey numerous items from multiple suppliers to a set of consumers. In this problem, products from various suppliers need to be delivered to different customers while considering vehicle capacity constraints, time windows, and minimizing transportation costs. We propose a hybrid approach that combines a generalized reduced gradient method to identify feasible regions with a feasible neighborhood search to achieve optimal or near-optimal solutions. The aim of the exact method is to get the region of feasible solution. Then we explore the region using feasible neighborhood search, to get an integer feasible optimal (suboptimal) solution. Computational experiments demonstrate that our model and method effectively reduce transportation costs while satisfying vehicle capacity constraints and relaxed time windows. Our findings provide a viable solution for improving logistics operations in real-world scenarios.
Optimization model of vehicle routing problem with heterogenous time windows Mawengkang, Herman; Syahputra, Muhammad Romi; Sutarman, Sutarman; Weber, Gerhard Wilhelm
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i4.pp4043-4057

Abstract

This study proposes a novel optimization framework for the vehicle routing problem with heterogeneous time windows, a critical aspect in logistics and supply chain operations. Unlike conventional vehicle routing problem (VRP) models that assume uniform service schedules and fleet capacities, our approach acknowledges the diverse time constraints and vehicle specifications often encountered in real-world scenarios. By formulating the problem as a mixed integer linear programming model, we incorporate constraints related to time windows, vehicle load capacities, and travel distances. To tackle the NP-hard complexity, we employ a hybrid strategy combining metaheuristic algorithms with exact methods, thus ensuring both solution quality and computational efficiency. Extensive computational experiments, conducted on benchmark datasets and real-world logistics data, confirm the superiority of our model in terms of solution quality, runtime, and adaptability. These findings underscore the model’s practicality for industries facing dynamic routing requirements and tight service windows. Furthermore, the proposed framework equips decision-makers with a robust tool for optimizing route planning, ultimately enhancing service quality, reducing operational costs, and promoting more reliable delivery outcomes.
Co-Authors , Rahmad Sembiring Abi Rafdi Afdhaluzzikri, Afdhaluzzikri Afnaria, Afnaria Aghni Syahmrani Ahmad Zaki Mubarak, Ahmad Zaki Al Khowarizmi Anggi Anatasia Kinanti Anugreni, Fera Arjon Turnip 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 Elvina Herawati Ermawati Ermawati Erna B N Erna Budhiarti Nababan Fatma Sari Hutagalung Firmansyah Firmansyah Hadistio, Ryan Rinaldi Handayani, Sri Hartama, Dedy Hengki Tamando Sihotang Hengki Tamando Sihotang Heni Pujiastuti Heri Gustami Husain Husain Husain Husain Ignazio Ahmad Pasadana Iin Parlina Indah Purnama Sari Juanda Hakim Lubis 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 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 Sugiyarmasto Sugiyarmasto Sutarman Sutarman Sutarman Sutarman Syahputra, Muhammad Romi Syahril Effendi Tanjung, Ilyas Tulus Tulus Tulus Tulus Vinsensia, Desi Weber, Gerhard Wilhelm Wiryanto Wiryanto Wisnu Irsandi Pratama Zakarias Situmorang Zarkasyi, Muhammad Imam Zarlis, M Zarlis, M Zoelkarnain Rinanda Tembusai Zulfian Azmi