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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and 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 Abdimas Talenta : Jurnal Pengabdian Kepada Masyarakat Juripol Jurnal Teknovasi : Jurnal Teknik dan Inovasi Mesin Otomotif, Komputer, Industri dan Elektronika MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Query : Jurnal Sistem Informasi Zero : Jurnal Sains, Matematika, dan Terapan JURIKOM (Jurnal Riset Komputer) Data Science: Journal of Computing and Applied Informatics ComTech: Computer, Mathematics and Engineering Applications Building of Informatics, Technology and Science Jurnal Mantik Indonesian Journal of Education and Mathematical Science International Journal of Advances in Data and Information Systems Randwick International of Social Science Journal Jurnal Scientia Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Journal of Applied Data Sciences TECHSI - Jurnal Teknik Informatika Prisma Sains: Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Proceeding of International Conference on Information Science and Technology Innovation (ICoSTEC) The Indonesian Journal of Computer Science Journal of Digital Market and Digital Currency
Efendi, Syahril
Department Of Computer Science And Information Technology, University Of North Sumatra, Indonesia
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Physics Social Sciences Other

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Predictive Analysis of Spatial Data and Time Series to Predict Earthquake Magnitudes by Using Data Mining Approach Ignazio Ahmad Pasadana; Herman Mawengkang; Syahril Efendi
Randwick International of Social Science Journal Vol. 4 No. 1 (2023): RISS Journal, January
Publisher : RIRAI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47175/rissj.v4i1.607

Abstract

The suggested methodology presented in this work uses data mining to identify seismic zones and time series to forecast earthquake magnitudes. Utilize historical earthquake data gathered from the United States Geological Survey (USGS) and obtained by utilizing hierarchical and fartherst first clustering to predict seismic activity. Latitude and longitude cluster data were used to create a prediction model to forecast the size of upcoming earthquakes in the Nanggroe Aceh Darussalam region and its nearby areas.
Vehicle detection system based on shape, color, and time-motion Afritha Amelia; Muhammad Zarlis; Suherman Suherman; Syahril Efendi
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 12, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v12.i3.pp1070-1082

Abstract

Vehicle detection application can assist in-vehicle surveillance functions and have implications for various fields. A vehicle can be identified through the license number attached to its license plate, the color and its shape. Vehicle detection can make use of multimedia sensors so that the design and detection performances can be optimal. Sensor performances are influenced by factors such as the number of multimedia sensors, sensor placement, sensor positioning, and schemes in case of system failure. This study makes use of multimedia sensors with cameras equipped by a phase detection auto focus (PDAF) technology which is like a pair of eyes to see an object. This study analyses 134 vehicles with number detection and various colors to see the effect on the detection and recognition processes. The cars were passed through the camera 10 times at a speed of 10-15 km/hour with various camera distances and positions. Various values and depths of the images were generated. The farther the distance the higher the disparity values. For maximum distance of 50 m, disparity is 6.20×106 and image depth is 16.88×109. Vehicle color influences detection with orange has the best accuracy, but the gray has the largest path error value.
Blockchain in Land Registry Fauzi Amri; Poltak Sihombing; Syahril Efendi
Prisma Sains : Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram Vol 11, No 1: January 2023
Publisher : IKIP Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/j-ps.v11i1.6537

Abstract

Blockchain technology that is increasingly developing can be a solution to land disputes. By designing a land title certificate system based on Blockchain technology, which has complete verification and recording of data history. So that it can help the government's efforts in Agrarian Reform. This research resulted in a system of recording of data history of Land Certificate. that can prove the Blockchain concept where every change that occurs in land title certificate data can be recorded, and distributed to all participants involved in the system.
Cluster Analysis using K-Means and K-Medoids Methods for Data Clustering of Amil Zakat Institutions Donor Hotmaida Lestari Siregar; Muhammad Zarlis; Syahril Efendi
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 2 (2023): April 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i2.5315

Abstract

Cluster analysis is a multivariate analysis method whose purpose is to classify an object into a group based on certain characteristics. In cluster analysis, determining the number of initial clusters is very important so that the resulting clusters are also optimal. In this study, an analysis of the most optimal number of clusters for data classification will be carried out using the K-Means and K-Medoids methods. The data were analyzed using the RFM model and a comparative analysis was carried out based on the DBI value and cluster compactness which was assessed from the average silhouette score. The K-Means method produces the smallest DBI value of 0.485 and the highest average silhouette score value of 0.781 at k=6, while the K-Medoids method produces the smallest DBI value of 1.096 and the highest average silhouette score value of 0.517 at k=3. The results show that the best method for data clustering donations Amil Zakat Institutions is using the K-Means method with an optimal number of clusters of 6 clusters.
Data-Driven Approach for Credit Risk Analysis Using C4.5 Algorithm Muhammad Iqbal; Syahril Efendi
ComTech: Computer, Mathematics and Engineering Applications Vol. 14 No. 1 (2023): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v14i1.8243

Abstract

Credit risk is bad credit, resulting in bank losses due to non-receipt of disbursed funds and unacceptable interest income. However, credit services still have to be done to achieve profit. The absence of an approach that can assist in making policies to reduce credit risk makes the risk opportunities even more significant. So, data processing techniques are needed that produce information to be used as the basis for policies in triggering credit risk with data mining. The research presented an application of data mining as a credit risk approach considering the ability of data mining techniques to extract data into useful information with the C4.5 algorithm. The research used a sample of 30 data banks with 6 factors (credit growth, net interest margin, type of bank, capital ratio, company size, and bank compliance level). Credit risk was evaluated by making a decision tree and a RapidMiner test application. The results show that credit growth is the main factor causing credit risk, followed by bank compliance level, net interest margin, and capital ratio. Based on the results obtained, the C4.5 algorithm can be used in analyzing credit risk with results that are easy to understand and can be used as useful information for banks.
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.
Applying the Simplex Method to Optimize Employee Distribution to Increase Sales Internet Data Package Mulkan Azhari; Syahril Efendi; Purwanto Purwanto; Halim Maulana
Indonesian Journal of Education and Mathematical Science Vol 4, No 3 (2023)
Publisher : UMSU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/ijems.v4i3.15151

Abstract

The goal of this article is to ascertain how to maximize sales of internet data packages while keeping the company's marketing budget within reasonable bounds. The technique utilized is linear programming using the Simplex method; this approach's benefit is the ability to compute two or more choice variables, which produces results that are superior to those of the graphical method. Variable Three are utilized in this study: senior marketing (X1), junior marketing (X2), and apprentice marketing (X3). The maximum amount of data package cards that may be sold by the three marketing is 3000. The marketing senior target can sell 1200 packages, whereas the marketing junior target can sell 1200 packages, according to optimization simulation findings using the simplex approach.
Enhancing Unbalanced Data Classification with Cross-Validation and Extreme Gradient Boosting: A Comprehensive Analysis muhammad riki atsauri; herman mawengkang; syahril efendi
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 7 No. 1 (2023): Issues July 2023
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v7i1.8690

Abstract

As a novel and efficient ensemble learning algorithm, XGBoost has been widely applied due to its multiple advantages, but its classification effect in cases of data imbalance is often not ideal. Aiming at this problem, efforts were made to optimize XGBoost and the Cross Validation algorithm. The main idea is to combine cross validation and XGBoost on unbalanced data for data processing, and then get the final model based on XGBoost through training. At the same time, optimal parameters are searched and adjusted automatically through optimization algorithms to realize more accurate classification predictions. In the testing phase, the area under the curve (AUC) is used as an evaluation indicator to compare and analyze the classification performance of various sampling methods and algorithm models. The results of the model analysis using AUC are expected to verify the feasibility and effectiveness of the proposed algorithm.
ENHANCED OF ANALYSED OPTIMIZATION LEARNING MODEL FOR MULTI PRODUCT RETAIL AND DISTRIBUTION SYSTEM Solly Aryza; Syahril Efendi; Poltak Sihombing; Sawaluddin Sawaluddin
Jurnal Scientia Vol. 12 No. 04 (2023): Education, Sosial science and Planning technique, 2023, Edition September-Nov
Publisher : Sean Institute

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

Abstract

The progress of the business environment is highly dependent on several things such as cost issues, service, and product quality improvement which greatly impact customer satisfaction where the supply chain is faced with high dynamics and uncertainty in the business environment, which is more obvious when end customer demands and orders are considered. The supply chain network must be able to deal with uncertain demand from all its elements including manufacturers, suppliers, and distribution centers. Therefore, this study aims to optimize the multi-product distribution system and multi-level delivery of product flow under uncertain conditions. A multi-objective mathematical model is developed that minimizes supply chain costs while maximizing customer satisfaction and different scenarios. In addition, the significant diversity of different channels in terms of product information, price, consumer experience, and service level it possible to introduce of the Internet to the business world has offered new communication channels to facilitate shopping, making product sales by manufacturers, and product purchases by customers faster and more precise. In addition, purchases through computers, mobile phones, and various applications as well as traditional purchasing methods such as buying from a store or selecting desired items from a catalog have covered all social strata, tastes, and habits. This method of using all available means, called omnichannel, allows organizations to take greater control over pricing and product selection and to receive precise feedback from the market and customers assisting them in the best production and pricing decisions.
Deep Learning Approach For Modelling The Spread of Covid-19 Riah Ukur Ginting; Muhammad Zarlis; Poltak Sihombing; Syahril Efendi
Proceeding of International Conference on Information Science and Technology Innovation (ICoSTEC) Vol. 1 No. 1 (2022): Proceeding of International Conference on Information Science and Technology In
Publisher : Universitas Respati Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/icostec.v1i1.2

Abstract

In March 2020, the Covid-19 outbreak in Indonesia, where the symptoms of the corona virus made the Indonesian people worry and experience depression. It has been almost two years that Covid-19 has not known what causes it, let alone a person's body condition is not good which can result in being attacked by the virus. Covid-19 first appeared in the city of Wuhan, part of China, where it spread very quickly and was deadly. Its spread through direct physical contact with humans is transmitted through the mouth, nose and eyes, therefore a model is needed for the spread of the corona virus. The spread of COVID-19 affects the pattern of interaction between susceptible (susceptible) and infected (infectious) individuals, where human social contact is very heterogeneous and in groups. To influence the impact of the spread of COVID-19 using deep learning approach that is modeled on the spread of COVID-19, individuals are exposed, infected, recover and die. The purpose of this research is to produce good predictions with a deep learning approach for modeling the spread of COVID-19. The results of the deep learning approach for the COVID-19 spread model carried out the 400 time iteration with an MSE achievement of 0.021112.
Co-Authors Abdulbasah Kamil, Anton Abi Rafdi Ahmad Rozy Ahmadi, Fauzan Nur Al Khowarizmi Aminuyati Andysah Putera Utama Siahaan Arjon Turnip Asrizal Asrizal Badawi, Afif Br Bangun, Desy Milbina Br Ginting, Dewi Sartika Budi K. Hutasuhut Chairil Umri Dadang Priyanto Devi Maiya Sari Nasution Erna Budhiarti Erna Budhiarti Nababan Erna Budhiarti Nababan Fahmi Fahmi Fajar Muhajir Fatma Sari Hutagalung Fauzan Nurahmadi Fauzi Amri Fuzy Yustika Manik, Fuzy Yustika Ginting, Dewi Sartika Br Halim Maulana Hamzani, Fitri Rezky Harahap, Lailan Hariyati Lubis, Hariyati Harumy, T. Henny Febriana Hasibuan, Nisma Novita Hasugian , Paska Marto Hengki Tamando Sihotang Hengki Tamando Sihotang Herianto, Tulus Joseph Herimanto Herimanto herman mawengkang Herman Mawengkang Hotmaida Lestari Siregar Ichsanuddin Hakim Ignazio Ahmad Pasadana Iin Parlina Indah Purnama Sari Indra Edy Syahputra Irzal Sofyan Jaya, Ivan Khowarizmi, Al- Lailan Harahap Lidya Rosnita lili Tanti Lubis, Fahrurrozi M Safii M. Isa Indrawan Mahyuddin K. M Nasution Manurung, Rodiyah Aini Mardiansyah, Heru Marischa Elveny, Marischa Maya Silvi Lydia Mesran, Mesran Mochamad Wahyudi Mohammad Andri Budiman Muhammad Iqbal Muhammad Iqbal Muhammad Riki Atsauri Muhammad Rusdi dan Afritha Amelia - Muhammad Zarlis Muhammad Zarlis Muhammad Zarlis Muhammad Zarlis Muhammad Zarlis Muhammad Zarlis Muhammad Zarlis, Muhammad Muliawan Firdaus Mulkan Azhari Naemah Mubarakah Nainggolan, Pauzi Ibrahim Nugroho Syahputra Oktaviana Bangun Pahala Sirait Poltak Sihombing Poltak Sihombing Poltak Sihombing Poltak Sihombing Poltak Sihombing Poltak Sihombing Prayoga, Nanda Dimas Purwanto Purwanto Rahmad Syah Riah Ukur Ginting Rika Permata Sari Siregar Rizki Suwanda Saib Suwilo Santoso, Zikri Akmal Saraswati Yoga Andriyani Sarif, Muhammad Irfan Sawaluddin Sawaluddin Sembiring, Rahmat W Seniman Seniman Seniman Seniman, Seniman Siagian, Deliyana Simamora, Windi Saputri Solly Aryza Sri Dwi Hastuti Sri Melvani Hardi Suherman Suherman Suherman, Suherman Sutarman Sutarman Sutarman Sutarman Syah, Rahmad B. Y. Syahputra, Indra Edy Syahputra, Muhammad Romi Syahraini, Syahraini Syahriol Sitorus Taufiqurrahman Taufiqurrahman Tulus Tulus Tulus Tulus Vinsensia, Desi Watts, Michael J. Weber, Gerhard Wilhelm yeni absah Yudhistira Yudhistira Yudhistira Zakarias Situmorang Zega, Imanuel Zuhri Ramadhan Zulkarnain Lubis