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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics CommIT (Communication & Information Technology) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Informatika JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Pilar Nusa Mandiri Abdimas Talenta : Jurnal Pengabdian Kepada Masyarakat JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Technomedia Journal International Journal of Natural Science and Engineering J-SAKTI (Jurnal Sains Komputer dan Informatika) Data Science: Journal of Computing and Applied Informatics Aptisi Transactions on Technopreneurship (ATT) Building of Informatics, Technology and Science Journal of Information Systems and Informatics Jurnal Informasi dan Teknologi Computer Science and Information Technologies TIN: TERAPAN INFORMATIKA NUSANTARA Journal of Applied Data Sciences Narra J J-SAKTI (Jurnal Sains Komputer dan Informatika) Action Research Literate (ARL) Proceeding Of International Conference On Education, Society And Humanity
Muhammad Zarlis, Muhammad
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Weighting Comparative Analysis Using Fuzzy Logic and Rank Order Centroid (ROC) in the Simple Additive Weighting (SAW) Method Ghazali, Alfin; Sihombing, Poltak; Zarlis, Muhammad
International Journal of Natural Science and Engineering Vol 5, No 2 (2021): July
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (307.467 KB) | DOI: 10.23887/ijnse.v5i2.37847

Abstract

The Covid-19 outbreak has changed the learning system in Indonesia into distance learning, better known as online learning. In determining student learning outcomes on student learning satisfaction with distance learning during the Covid-19 pandemic, a study was carried out using the Simple Additive Weighting (SAW) method. This study aims to determine student learning outcomes during the Covid-19 pandemic. The type of research used in this research is applied research, in which this research is directed to obtain information that can be used to solve problems. The method used is Simple Additive Weighting (SAW) by comparing the results of the decision of the SAW method between the weighting based on the Fuzzy Logic method and the weighting based on the ROC method. The subjects involved in this study were 36 students of Vocational High School (SMK). Data collection in the study was carried out using direct observation, interviews, and questionnaires. The criteria contained in the questionnaire are factors that affect the process of student learning outcomes on learning satisfaction during the Covid-19 pandemic. The criteria used are device ownership, accessibility, ease of obtaining materials, method accuracy, monitoring ability, interactivity, and independent learning. From the seven criteria, the priority scale is determined. The results showed that the analysis of the search for weight scores using the Simple Additive Weighting (SAW) method using Fuzzy Logic and Simple Additive Weighting (SAW) using the Rank Order Centroid (ROC) method resulted in different sub-criteria weighting scores, so it can be said that the combination of SAW- ROC provides a more accurate and more selective selection of the number of students.
Analysis Of The Role Of Blockchain Technology In Recording Motor Vehicle Ownership Data Santoso, Ahmad Imam; Zarlis, Muhammad; Mawengkang, Herman
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 7 No. 2 (2024): Vol. 7 No. 2 (2024): Issues January 2024
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v7i2.10938

Abstract

The importance of the role of motor vehicles in human life is revealed through its transformation from a tertiary need to a secondary one. In Indonesia, the number of motor vehicles reached 136.191 million units in 2020, prompting the government to regulate registration and identification through Presidential Regulation No. 5 of 2015. This research addresses issues related to motor vehicle administration in Indonesia, focusing on transparency, data integrity, and information availability. Inspired by the rapid growth in the number of motor vehicles and the increasing cases of theft, this research aims to design and implement an innovative motor vehicle ownership recording system using blockchain technology. This approach aims to enhance the accessibility of information on the origin and ownership of vehicles or Vehicle Registration Numbers (VRN), which is currently limited in both manual and online forms. The research methodology involves the design and implementation of blockchain technology, tested to verify its effectiveness in achieving transparency and data security goals. The research results indicate that this system can provide more comprehensive and distributed information to the general public, overcoming the limitations of centralized systems. The conclusion of this research affirms that the application of blockchain technology can be an innovative and effective solution to improve motor vehicle administration. The implications of this research include increased efficiency, security, and availability of information in handling vehicle administration, potentially having a positive impact on the general public and related industries
Penerapan Metode K-Means Clustering Untuk Daging Ayam Buras Miralda, Viya; Zarlis, Muhammad; Irawan, Eka
Building of Informatics, Technology and Science (BITS) Vol 2 No 2 (2020): December 2020
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (431.256 KB) | DOI: 10.47065/bits.v2i2.493

Abstract

Free-range chicken is a local Indonesian poultry whose population is widely found in every region of Indonesia. However, the level of consumption of free-range chicken meat in North Sumatra Province is still relatively low. This research data contains data on the production of free-range chicken in North Sumatra Province. One data mining technique is clustering. Grouping itself is a method by grouping data. The data of this study contains data on the production of free-range chicken in North Sumatra Province which began in 2010, 2011, 2012, 2013, 2014, 2017. (7 years), and data obtained from the Directorate General of Animal Husbandry and Animal Health as well as on animal access to BPS Sumatra site North (Central Statistics Agency). The purpose of this study is to group Regencies / Cities in North Sumatra Province into 2 parts. These are the Regency / City group with high free-range chicken meat and Regency / City with low-free chicken meat. This can be a contribution of the provincial government of North Sumatra, Regency / City which is of more concern than free-range chicken based on the cluster that has been done. The results of this research are taken from 33 data of free-range chicken meat in regencies / cities in North Sumatra province, 3 high-level districts, namely: Mandailing Natal, Langkat, Serdang Bedagai and 30 other regencies / cities including
Detection and Tracking Different Type of Cars With YOLO model combination and deep sort algorithm based on computer vision of traffic controlling Hasibuan, Nisma Novita; Zarlis, Muhammad; Efendi, Syahril
Sinkron : jurnal dan penelitian teknik informatika Vol. 5 No. 2B (2021): Article Research October 2021
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v6i1.11231

Abstract

The application of CCTV cameras for traffic surveillance and monitoring is one effective solution to address urban traffic problems, as the number of vehicles that continue to increase rapidly but the area of the road remains the same will cause congestion. However, the problem in traffic surveillance and monitoring is not just focusing on vehicle detection based on category inference on video sequence data sourced from CCTV cameras alone, another important, challenging task is to combine calculations, classification and tracking of different vehicle movements in urban traffic control systems. The study expanded on previous research by breaking down the problem into different sub-tasks using the YOLOv4 approach combined with the Deep Sort algorithm for the detection and tracking of objects directly on CCTV footage of vehicle activity on the city's three-stop highway. Based on the results of YOLOv4 testing resulted in a detection accuracy rate with mAP of 87.98% where the combination of YOLOv4 with the Deep Sort algorithm can detect, track and calculate 13 types of vehicles.
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
ANALISIS PERBANDINGAN PEMBOBOTAN ROC DAN FULL CONSISTENCY METHOD (FUCOM) PADA MOORA DALAM PENGAMBILAN KEPUTUSAN Prayoga, Nanda Dimas; Zarlis, Muhammad; Efendi, Syahril
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.v7i3.11643

Abstract

Decision support system is a system that can assist companies in making policy. There are several methods in a decision support system, one of which is the MOORA method. The MOORA method does not have a systematic weight determination. In several studies, the determination of the weight value is determined by experts in their field so that the value is less objective. So in this study, the Rank Order Centroid (ROC) and Full Consistency Method (FUCOM) weighting methods will be used systematically and objectively which will be applied to the MOORA method and a comparison of the results of these methods will be carried out with the calculation of the accuracy of the confusion matrix. The purpose of this study was to analyze the results of the weighting comparison using Rank Order Centroid (ROC) and Full Consistency Method (FUCOM) on the MOORA method so as to produce good accuracy. Based on the results of the study, testing with ROC weights on MOORA obtained results of 77.78% accuracy, 84% precision and 84% recall. While testing with ROC weights on MOORA obtained results of 77.78% accuracy, 84% precision and 84% recall. And testing with ROC+FUCOM weights on MOORA obtained 91.67% accuracy, 94% precision and 94% recall. So it can be concluded that the ROC+FUCOM weighting on MOORA produces good accuracy.
Combination of Ant Colony Tabu Search Algorithm with Firefly Tabu Search Algorithm (ACTS-FATS) in Solving the Traveling Salesman Problem (TSP) Harahap, Siti Sarah; Sihombing, Poltak; Zarlis, Muhammad
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.v8i1.12016

Abstract

Traveling Salesman Problem (TSP) is a classic combinatorial optimization problem, one of the optimization problems that can be applied to various activities such as finding the shortest path. The optimization problem in TSP is the most widely discussed and has become the standard for testing computational algorithms. TSP is a good object to test optimization performance. With scientific developments in the field of informatics, many researchers have optimized the application of algorithms to solve the Traveling Salesman Problem (TSP). In this study, researchers used a combination of Ant Colony Tabu Search – Firefly Algorithm Tabu Search (ACTS-FATS). The combination is doneto overcome Premature Convergence (trapped local optimum) which is a shortcoming of the ant colony algorithm, get the best running time by looking at the process of each point movement with the ant colony and firefly methods. After testing, getting the best running time results of 27.79%, and getting an accuracy rate of 17%.
Improved Accuracy In Data Mining Decision Tree Classification Using Adaptive Boosting (Adaboost) Riansyah, Muhammad; Suwilo, Saib; Zarlis, Muhammad
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 2 (2023): Research Article, Volume 7 Issue 2 April, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i2.12055

Abstract

The Decision Tree algorithm is a data mining method algorithm that is often applied as a solution to a problem for a classification. The Decision Tree C5.0 algorithm has several weaknesses, including: the C5.0 algorithm and several other decision tree methods are often biased towards modeling whose features have many levels, some problems for the model can occur such as over-fit or under-fit challenges, big changes to decision logic can result in small changes to data training, C5.0 can experience modeling inconvenience, data imbalance causes low accuracy in C5.0 algorithm. The boosting algorithm is an iterative algorithm that gives different weights to the distribution of training data in each iteration. Each iteration of boosting adds weight to examples of misclassification and decreases weight to examples of correct classification, thereby effectively changing the distribution of the training data. One example of a boosting algorithm is adaboost. The purpose of this research is to improve the performance of the Decision Tree C5.0 classification method using adaptive boosting (adaboost) to predict hepatitis disease using the Confusion matrix. Tests that have been carried out with the Confusion Matrix use the Hepatitis dataset in the Decision Tree C5.0 classification which has an accuracy rate of 80.58% with a classification error rate of 19.15%. Whereas in the Decision Tree C5.0 classification Adaboost has a higher accuracy rate of 82.98%, a classification error rate of 17.02%. This difference is caused by the adaboost algorithm, because the adaboost algorithm is able to change a weak classifier into a strong classifier by increasing the weight of the observations, and adaboost is also able to reduce the classifier error rate.
Performance Analysis Of The Combination Of Advanced Encryption Standard Cryptography Algorithms With Luc For Text Security Ady Putra, Wahyu; Suyanto, Suyanto; Zarlis, Muhammad
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 2 (2023): Research Article, Volume 7 Issue 2 April, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i2.12202

Abstract

Data security is very important as it is easy to exchange data today. Cryptographic techniques are needed as data security techniques. Combining two cryptographic algorithms is a solution for a better level of security. The Advanced Encryption Standard (AES) cryptographic algorithm requires low computational power and is the best symmetric algorithm. The LUC algorithm is an asymmetric algorithm that was developed from the RSA algorithm and has advantages in a better level of security and processing speed. In this research, two symmetric and asymmetric cryptographic algorithms will be combined in a hybrid scheme, namely the AES and LUC algorithms to improve data security. the AES algorithm will encrypt and decrypt messages, while the LUC algorithm performs encryption and decryption of the AES key. The results showed that the combination of the two AES and LUC algorithms was successful. However, the computational time needed by the two algorithms to perform the encryption and decryption process increases. The simulation results of the brute force attack performed show that the LUC algorithm can still be attacked. The greater the value of E (the public key of the LUC algorithm), the longer it takes for the brute force attack to be successful. The value of E is also directly proportional to the computational time required by the LUC. So it can be concluded that the AES algorithm is less precise when combined with the LUC algorithm.
Co-Authors , Rahmad Sembiring Achmad Noerkhaerin Putra Adisasmito, Wiku Bakti Bawono Ady Putra, Wahyu Aidil Halim Lubis AIRLANGGA, EKA Aminuyati Andrian, Kevin Ayodhia P. Pasaribu, Ayodhia P. Benfano Soewito Buaton, Relita Budhiarti Nababan, Erna Bugis M. Lubis, Bugis M. Christefa, Dea Cut Ita Erliana Dahlan Abdullah Defi Irwansyah Deny Jollyta Dewi, Rafiqa Efendi, Syahril Efendi, Syahril Eka Irawan Elviwani, Elviwani Erlina Erlina Erma Julita, Erma Erna Budhiarti Nababan Erna Budiarti Ghazali, Alfin Ginting, Emnita Boru Gunawan Gunawan Hadistio, Ryan Rinaldi Haq, Fesa Asy Syifa Nurul Harahap, Eka Purnama Hartama, Dedy Hasibuan, Nisma Novita Herman Mawengkang Hidayati, Indri Husna, Lina Naelal Indra Gunawan Lewis, Andreas Liana Liana Lidya Rosnita Mahyuddin K. M Nasution Malisie, Ririe F. Marischa Elveny, Marischa Marpaung, Tulus Joseph Herianto Mesran, Mesran Miralda, Viya Mohammad Andri Budiman Muhammad Reza Aulia Muliati, Vika Febri Nasution, Zulaini Masruro Novi Dian Nathasia Nurhayati Siregar, Nurhayati Nurwita, Siti Rakhmawati Ovirianti, Nurul Huda Pasaribu, Roni Fredy Halomoan Poltak Sihombing Prayoga, Nanda Dimas Pulungan, Annisa Fadhillah purba, lia cintia Purba, Roimal Hafizi Purnomo Sidi Priambodo Rahmad, Sofyan Rahman Aulia, Rahman Rahman, Abdu Riansyah, Muhammad Romanus Damanik Saib Suwilo Saifullah Saifullah Santoso, Ahmad Imam Sawaluddin Sembiring, Rahmat Widia Siregar, Jelita Siti Sarah Harahap Sri Melvani Hardi Suherman, Suherman Sukiman, T. Sukma Achriadi Sumarno . Sutarman Sutarman Suyanto Suyanto Syah, Rahmad B. Y. Syahputra, Muhammad Romi Syahril Effendi Syauqi, Muhammad Irfan Tanjung, Yulia Windi Tobing, Ricardo Joynest Tulus Tulus Tulus Ucuk Darusalam Wahyuni, Arlinda S. Wardhani, Widiastuti Kusumo Zakaria Zakaria Zakarias Situmorang Zulham Zulkarnain Lubis