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All Journal Saintia Matematika Journal of Mathematics Education and Application (JMEA) Sinkron : Jurnal dan Penelitian Teknik Informatika CARTESIUS : Jurnal Pendidikan Matematika Journal of Research in Mathematics Trends and Technology FARABI: Jurnal Matematika dan Pendidikan Matematika Journal of Mathematics Technology and Education Cartesius Jurnal Riset Rumpun Matematika dan Ilmu Pengetahuan Alam (JURRIMIPA)
Open Darnius
Universitas Sumatera Utara
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Environmental Science Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Journal : Sinkron : Jurnal dan Penelitian Teknik Informatika

 1 
OPTIMIZATION MODEL IN CLUSTERING THE HAZARD ZONE AFTER AN EARTHQUAKE DISASTER Monica Natalia Bangun; Open Darnius; Sutarman
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2022): Article Research Volume 7 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11598

Abstract

There are a large number of approaches to clustering problems, including optimization-based methods involving mathematical programming models to develop efficient and meaningful clustering schemes. Clustering is one of the data labeling techniques. K-means clustering is a partition clustering algorithm that starts by selecting k representative points as the initial centroid. Each point is then assigned to the nearest centroid based on the selected specific proximity measure. This writing is focused on the grouping of post-earthquake hazard zones based on grouping with regard to certain characteristics which aim to describe the process of partitioning the N-dimensional population into K-sets based on the sample. This research consists of three steps, namely standardization, data clustering using K-means and data interpolation using the K-means clustering algorithm and zoning of 7 variables, namely magnitude, depth, victim died, the victim didn’t die, public facilities were heavily damage, public facilities were slightly damage, and affected areas.
Modelling of Subject Scheduling Systems Using Hybrid Artificial Bee Colony Algorithm Sri Wahyuni Lingga; Sutarman; Open Darnius
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2023): Article Research Volume 8 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

A common schedule problem found in colleges is the positioning of courses in a certain space and time. This placement process often encounters barriers that must be met so that there is no imbalance in the school schedule. One of the problems that often arise is the placement of class capacity that does not match the course requirements. In this study, the researchers used the Artificial Bee Colony Hybrid Algorithm (HABC) to construct course schedules efficiently at the college. The objective of the research was to develop a course scheduling system using the HABC algorithm by combining the Engineering of Artificial Bee Colony (ABC) and genetic algoritms, especially on the crossover process to better address the schedule problems. The research procedure used is to design and implement a course scheduling system using the Hybrid ABC algorithm. The results of the research demonstrate that the Hybrid ABC algorithm is effective in generating optimal course schedule schedules, in line with time limits, room needs, and lecturer requirements and can automate course schedule processes, saving time and resources, while ensuring optimal schedules.
Inventory Model for Order Quantity Optimization with Partial Backlogging on Greater Demand at The Beginning Reanty Teresa Aritonang; Open Darnius; Sutarman Sutarman
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2023): Article Research Volume 8 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12600

Abstract

This article discusses the model of inventory with greater demand at the beginning which allows shortages. During the shortage period, it is assumed that there is a backlogged demand, and the remainder is considered lost sales. This research is completed by using the deterministic inventory model method, namely the EOQ model. The result of using the EOQ method is to determine the inventory lot size and length, with the goal of minimizing the total cost of inventory and generating maximum profits related to the inventory model. An numerical example is given to show the use of this model.
Simplifying Complexity: Linearization Method for Partial Least Squares Regression Herlin Simanullang; Sutarman Sutarman; Open Darnius
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2023): Article Research Volume 8 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12754

Abstract

This research investigates Romera’s local linearization approach as a variance prediction method in partial least squares (PLS) regression. By addressing limitations in the original PLS regression formula, the local linearization approach aims to improve accuracy and stability in variance predictions. Extensive simulations are conducted to assess the method's performance, demonstrating its superiority over traditional algebraic methods and showcasing its computational advantages, particularly with a large number of predictors. Additionally, the study introduces a novel computational technique utilizing bootstrap parameters, enhancing computational stability and robustness. Overall, the research provides valuable insights into the local linearization approach's effectiveness, guiding researchers and practitioners in selecting more reliable and efficient regression modeling techniques.
Co-Authors Asima Manurung Elvin Juliani Gulo Fahrul Rozi Harahap Hasoloan M Nababan Henry Rani Sitepu Herlin Simanullang Ide Prasanti Hutagalung Israil Sitepu Kristina Pestaria Sinaga Laksono Trisnantoro Lisna Astria Meili Yanti Monica Natalia Bangun Mutia Sari Nofrida Elly Zendrato Parapat Gultom Pasukat Sembiring Reanty Teresa Aritonang Rifalin Delustia Purba Rifan halomoan tua sinaga Sri Wahyuni Lingga SRI WULANDARI Sutarman Sutarman Sutarman Sutarman Sutarman Sutarman Sutarman Tulus Tulus Ujian Sinulingga Utari Sri Mayanti Widya Hardiyanti Yoga Fromega Saragih Yuni Wardani