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All Journal Jurnal Media Infotama Jurnal Sains dan Teknologi Jurnal Pilar Nusa Mandiri JITK (Jurnal Ilmu Pengetahuan dan Komputer) METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) JISICOM (Journal of Information System, Infomatics and Computing) Jurnal Informatika Kaputama (JIK) Jurnal Sistem Informasi Kaputama (JSIK) Majalah Ilmiah Kaputama JTIK (Jurnal Teknik Informatika Kaputama) MEANS (Media Informasi Analisa dan Sistem) Jurnal Manajemen Informatika Jayakarta Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Society : Jurnal Pengabdian dan Pemberdayaan Masyarakat Journal of Vision and Ideas (VISA) EXPLORER Bulletin of Multi-Disciplinary Science and Applied Technology Archive: Jurnal Pengabdian Kepada Masyarakat Jurnal Nasional Teknologi Komputer Sci-Tech Journal Journal of Artificial Intelligence and Engineering Applications (JAIEA) International Journal of Informatics, Economics, Management and Science Journal of Engineering, Technology and Computing (JETCom) Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY International Journal of Health, Engineering and Technology Jurnal Penelitian Sistem Informasi Indonesian Journal of Education And Computer Science Indonesian Journal of Science, Technology, and Humanities Jurnal Penelitian Teknologi Informasi dan Sains Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi Modem : Jurnal Informatika dan Sains Teknologi Repeater: Publikasi Teknik Informatika dan Jaringan Switch: Jurnal Sains dan Teknologi Informasi Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Saturnus: Jurnal Teknologi dan Sistem Informasi International Journal of Information Engineering and Science Jurnal Publikasi Ilmu Komputer dan Multimedia
Buaton, Relita
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Student Character Grouping Based on Six Dimensions of Pancasila Student Profile Using Clustering Method (Case Study of SMK Swasta Setia Budi Binjai) Zuliani, Zuliani; Ramadani, Suci; Buaton, Relita
International Journal of Informatics, Economics, Management and Science Vol 2 No 2 (2023): IJIEMS (August 2023)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/ijiems.v2i2.1202

Abstract

Character education is one of the important aspects in developing students into individuals with integrity, ethics, and responsibility. Pancasila as the foundation of the Indonesian state has a central role in shaping students' character. This study aims to categorize student character based on six dimensions of the Pancasila learner profile at SMK Swasta Setia Budi Binjai. The six dimensions of the Pancasila learner profile that are the focus of this study include: 1) Faithful, Devoted to God Almighty and Noble, 2) Global Diversity, 3) Mutual Cooperation, 4) Independent, 5) Creative, 6) Critical Reasoning. The clustering method is used to group students based on the Pancasila learner profile measured through questionnaires distributed to subject teachers. The collected data will be analyzed using relevant clustering algorithms to identify the pattern of student characters present in the school population. This research is expected to provide deeper insight into the character of students at SMK Swasta Setia Budi Binjai based on Pancasila values. The results of this study are expected to be the basis for the development of a more effective character education program that focuses on strengthening the values of Pancasila in an effort to produce a young generation with strong character, love for the country, and contribute positively to society and the nation.
Application of the Monte Carlo Method in Modeling and Simulation of Service Queuing Systems at PT. Pos Indonesia Persero Binjai Yusrina, Eli; Buaton, Relita; Prahmana, I Gusti
International Journal of Informatics, Economics, Management and Science Vol 2 No 2 (2023): IJIEMS (August 2023)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/ijiems.v2i2.1181

Abstract

Queues are events that we often encounter in various places that provide services to the public, one of which is the Post Office. Service to customer satisfaction is a very important thing, so that improving the quality of customer service must always be done. A good queuing system will affect consumer behavior and satisfaction. PT. Pos Indonesia Persero Binjai is a service company where the purpose of PT. Pos Indonesia (Persero) itself is customer satisfaction oriented. The problems that occurred at PT. Pos Indonesia Persero Binjai caused long queues to build up in queues. To overcome these problems, it is necessary to improve the system such as applying the queuing model application by applying the queuing model method and Monte Carlo simulation. Monte Carlo is a probabilistic simulation method that generates random input to mimic the existing conditions of a problem by estimating the same distribution and in accordance with reality. So that with the improvement of the system, the application of the queuing model can be applied, directing customers to take queue numbers, and monitoring the queue card arrangement, adding tellers to serve customers, enlarging the waiting room so that customers are comfortable waiting and also determine the characteristics and performance measures of the queuing system in part of the payment counter and delivery of goods that will help PT. Pos Indonesia Binjai Company.
Expert System for Diagnosing Cancer Using Bayes Theorem Method Sembiring, Indri Aurellia Apsari; Buaton, Relita; Khair, Husnul
International Journal of Informatics, Economics, Management and Science Vol 3 No 1 (2024): IJIEMS (January 2024)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/ijiems.v3i1.1231

Abstract

Cancer is a dangerous disease that is not contagious and is caused by abnormal cells or tissues that can grow rapidly. The rapid development of this network will cause several complications of this disease which develop rapidly as well. Adam Malik General Hospital is one of the government hospitals that has complete facilities to treat cancer patients. Because it is a regionally centralized general hospital, each patient has quite a long queue when conducting consultations and treatment, this can result in physical fatigue in patients because it takes too long in the queue. To overcome these problems, we need a system that can provide information and detect early cancer diagnoses. So that the doctor can use the results of the diagnosis issued by the system so that it can be analyzed further. This of course can speed up the time the patient is in the examination, so that the treatment process can run effectively and efficiently. An expert system is a system that can store information from an expert, such as a doctor, for example. One of the methods that can be used is the Bayes Theorem method, which is a theory of probable conditions that calculates the probability of an event that depends on evidence. From the results of the trials that have been carried out, the results show that the patient suffers from cancer, namely breast cancer with a value of 81.60%.
IOT Based Automatic Light Control System Using MQTT Protocol Sima, Brema Arisma; Buaton, Relita; Sihombing, Marto
International Journal of Informatics, Economics, Management and Science Vol 3 No 1 (2024): IJIEMS (January 2024)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/ijiems.v3i1.1213

Abstract

An Internet of Thing-based automatic light control system using the MQTT protocol is an efficient solution for controlling lights on or off. This study aims to design and implement an IOT-based automatic light control system that can be accessed and controlled via the internet network. This system uses the MQTT protocol to communicate between the hardware and software connected to the MQTT Broker. This system also consists of several main components, namely a light sensor, NodeMCU ESP8266, and a user application. The light sensor is used to detect the intensity of surrounding light, NodeMCU ESP8266 to connect to Wi-Fi networks and broker MQTT. The MQTT broker serves as a communication center between publishers and subscribers. MQTT Dash is a user application that provides an interface for manually controlling the user's lights or setting the automatic mode.
PENGCLUSTERAN JENIS USAHA UKM BERDASARKAN PROGRAM BANTUAN DI KOTA BINJAI MENGGUNAKAN ALGORITMA K-MEANS Azizah, Siti Nur; Buaton, Relita; Selfira, Selfira
DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Vol 6, No 2: DESEMBER 2025
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/device.v6i2.7277

Abstract

Penelitian ini bertujuan untuk mengelompokkan jenis usaha UKM berdasarkan program bantuan yang diterima di Kota Binjai menggunakan algoritma K-Means. Permasalahan distribusi bantuan yang belum tepat sasaran dan tidak merata mendorong perlunya pemetaan berbasis data. Metode yang digunakan adalah algoritma K-Means yang diimplementasikan dengan MATLAB R2014a, dengan variabel domisili kecamatan, jenis usaha, dan jenis bantuan. Pengujian dilakukan dengan jumlah cluster 3 hingga 6 untuk menentukan model paling optimal. Hasil terbaik diperoleh pada model 6 cluster dengan nilai cluster variance terendah sebesar 0,7759, menunjukkan distribusi data yang paling kompak. Masing-masing cluster memiliki karakteristik berbeda yang merepresentasikan kebutuhan spesifik UKM di tiap wilayah. Dengan pendekatan ini, strategi penyaluran bantuan dapat dilakukan secara lebih objektif, efisien, dan sesuai kebutuhan. Penelitian ini diharapkan menjadi acuan dalam pengambilan keputusan berbasis data oleh pemerintah daerah dalam mendukung pemerataan ekonomi di Kota Binjai.
Application of Numerical Measure Variations in K-Means Clustering for Grouping Data Relita Buaton; Solikhun Solikhun
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 1 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i1.3269

Abstract

The K-Means Clustering algorithm is commonly used by researchers in grouping data. The main problem in this study was that it has yet to be discovered how optimal the grouping with variations in distance calculations is in K-Means Clustering. The purpose of this research was to compare distance calculation methods with K-Means such as Euclidean Distance, Canberra Distance, Chebychev Distance, Cosine Similarity, Dynamic TimeWarping Distance, Jaccard Similarity, and Manhattan Distance to find out how optimal the distance calculation is in the K-Means method. The best distancecalculation was determined from the smallest Davies Bouldin Index value. This research aimed to find optimal clusters using the K-Means Clustering algorithm with seven distance calculations based on types of numerical measures. This research method compared distance calculation methods in the K-Means algorithm, such as Euclidean Distance, Canberra Distance, Chebychev Distance, Cosine Smilirity, Dynamic Time Warping Distance, Jaccard Smilirity and Manhattan Distance to find out how optimal the distance calculation is in the K-Means method. Determining the best distance calculation can be seen from the smallest Davies Bouldin Index value. The data used in this study was on cosmetic sales at Devi Cosmetics, consisting of cosmetics sales from January to April 2022 with 56 product items. The result of this study was a comparison of numerical measures in the K-Means Clustering algorithm. The optimal cluster was calculating the Euclidean distance with a total of 9 clusters with a DBI value of 0.224. In comparison, the best average DBI value was the calculation of the Euclidean Distance with an average DBI value of 0.265.
Penerapan Human Centered Technology untuk Ekosistem Pertanian Digital Berkelanjutan di Desa Sei Penjara, Kecamatan Sei Bingai, Kabupaten Langkat Buaton, Relita; Luta, Devi Andriani; Selfira, Selfira; Prahmana, I Gusti
Society : Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol. 7 No. 1 (2026): Vol. 7 No. 1, April 2026
Publisher : Universitas Dinamika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37802/society.v7i1.1285

Abstract

Technology implementation in rural areas often faces sustainability challenges due to a lack of user focus. In Sei Penjara Village, specific problems were identified in inefficient, high-risk agricultural management, and a high dependence on a single individual. To address these issues, this program adopted a Human Centered Technology approach through a two track strategy that integrates the development of Internet of Things (IoT) hardware for precision agriculture with human resource empowerment through digital marketing training. The implementation method is through technology design and preparation, including the design of soil and water nutrient monitoring tools, application development, and implementation, installation, and training on the use of IoT tools, sensors, and applications. The results in the field show that the results of community service activities have a real, direct, and measurable impact on increasing the capacity of village communities, the application of IoT-based soil and water nutrient monitoring tools has been proven to increase fertilization efficiency by ± 25% and reduce agricultural operational costs by around 35%, more than 80% of training participants are able to use ChatBot independently, participants are able to produce promotional content independently, understand product storytelling strategies, and utilize social media analytics features to reach a wider market, and the next stage plan is to monitor the development of the impact of the IoT tools produced in optimizing community harvests. If there are obstacles, they will be evaluated, but if there are no obstacles, this program will be implemented in villages in Langkat Regency and its surroundings.            
Penerapan Metode Clustering Pada Kasus Kecelakaan Kerja Prisa Abela; Relita Buaton; Magdalena Simanjuntak
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 2 No. 5 (2024): September: Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v2i5.298

Abstract

Work accidents are one of the problems that often occur in companies/agencies where accidents happen to employees/workers and cause serious physical injuries. BPJS Employment is an insurance program that is trusted by agencies/companies by claiming Work Accident Insurance (JKK) which can help in easing the financial burden on families as well as initial efforts to handle cases of work accidents that occur. The main aim of this research is to assist companies in handling work accident cases that occur. The data used in this research includes work accident reports collected from the Bpjs Ketenagakerjaan Stabat office. The method used is the clustering method with the K-means algorithm, which was chosen because of its ability to group fairly large amounts of data with fast and efficient computing time. By using the clustering method that has been used to process work accident case data at Bpjs Ketenagakerjaan in Stabat, we can produce new information from the 672 data that have been tested. From 672 work accident case data at Bpjs Employment in Stabat, 3 clusters were obtained with the results of Cluster 1 having 2 work accident case data, Cluster 2 having 9 work accident case data and Cluster 3 having 9 work accident case data.
Penerapan Metode Apriori Untuk Menentukan Best Rule Pada Penjualan Pakaian: Studi Kasus : Toko Amezon Elisa Br. Sembiring; Relita Buaton; Lina Arliana Nur Kadim
Jurnal Publikasi Ilmu Komputer dan Multimedia Vol. 4 No. 3 (2025): September: Jurnal Publikasi Ilmu Komputer dan Multimedia
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupikom.v4i3.5197

Abstract

The Indonesian fashion industry is experiencing rapid and competitive growth, requiring businesses to be more responsive to consumer needs and preferences. Amezon Store, as a clothing retailer, faces challenges in stock management due to inaccurate forecasts of market demand. This mismatch between the quantity of goods provided and the items in demand by consumers can lead to stockpiling and hamper capital turnover. Therefore, a system capable of analyzing sales transaction patterns effectively is needed. This study applies the Apriori method to find the best rule or optimal purchasing pattern from clothing sales transaction data at Amezon Store. The Apriori method was chosen because of its ability to explore associations between frequently purchased items, thus supporting the decision-making process in inventory planning. The results of this study are expected to provide strategic recommendations to store management in providing products according to market needs, minimizing the risk of planning errors, and improving overall store operational efficiency. Based on the analysis conducted using RapidMiner, the best rule with 2 itemsets is obtained, namely IF buying Manset Then buying Hijab with support 0.0129 (1.29%) and confidence 0.564 (56.4%), the best rule with 3 itemsets is IF buying Long Pants, Pleated Skirt Then buying Distro T-Shirt with support 0.0101 (1.01%) and confidence 1 (100%) the best rule with 4 itemsets is IF buying Shirt, baby clothes, Short Pants Then buying One set with support 0.0101 (1.01%) and confidence 0.9167 (91.67%).
Sentiment Analysis of Social Media X Users Toward Finance Minister Purbaya Yudhi Sadewa Using the Support Vector Machine Algorithm Adian Fahreza Surbakti; Relita Buaton; Selfira
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2228

Abstract

In this digital era, the rapid advancement of information and communication technology has transformed social media platforms particularly X (formerly Twitter) into a primary space for public discourse concerning government policies. The Minister of Finance, Purbaya Yudhi Sadewa, has become a focal point of public debate, garnering reactions ranging from appreciation to criticism regarding his management of national finances. However, manual sentiment analysis is impractical, time-consuming, and prone to subjectivity when handling the massive and continuously expanding volume of social media data. Therefore, an automated, machine learning-based approach is essential to process this big data into strategic insights for mapping public sentiment. This study aims to objectively analyze public sentiment toward the Minister of Finance by implementing the Support Vector Machine (SVM) algorithm within the CRISP-DM (Cross-Industry Standard Process for Data Mining) framework. The methodology includes data crawling, text preprocessing, and feature extraction using the TF-IDF (Term Frequency – Inverse Document Frequency) method. Analysis of 3,927 tweets reveals that public opinion is dominated by negative sentiment at 54.2%, followed by positive sentiment at 36.9% and neutral sentiment at 8.9%. The developed SVM model achieved a classification accuracy of 72.43%, demonstrating that this machine learning approach is both effective and reliable for mapping public perception. These findings indicate that the Minister of Finance, Purbaya Yudhi Sadewa, faces significant public scrutiny, and this data-driven analysis serves as a strategic tool for evaluating the policies under his administration.
Co-Authors Achmad Fauzi Ade Chairany Adek Maulidya Adian Fahreza Surbakti Adinda Maudia Savira Ajisro Siringoringo Alma Diana Rangkuti Alma Diana Rangkuti Ambarita, Indah Ami Dilham Ana, Putri Andri Kristiawan Anisa Anisa Anisa Anisa Anisa Putri Pratiwi anjelia alsar anjeliaalsharlubis Anjelia Alsar Lubis Annatasia , Kristina Aprillianda Pasaribu Aula, Nurhasanah Auni Patrisyah Ayu Rahayu Febria Ayu Rahayu Febria Br. Ginting, Rosa Lina Budi Serasi Ginting Budi Serasi Ginting Cinta Apriliza Clara Rosa Wijaya David Jumpa Malem Sembiring Dea, Dea Puspita Deny Jollyta Deri Kurniawan Desva Karliana br Sembiring Dhea Agustina Akmal Dhea Alfiya Ningsih Dhovan Damara Santoso Dicha Mutia Dhani Dita Mawarni Diva Alifya Dwi ASTUTI Elisa Br. Sembiring Elviwani Fadillah Fadillah Fajar Amalia Putri Fany Juliawati Farid Reza Malau Fauzi, Achmad Febi Andini Fuji Dodo Aritonang Gultom, Imeldawaty Haryanto, Septian Hayati, Radhiah Heka Herawati Br Tarigan Herman Mawengkang Hermansyah Sembiring Hermansyah Sembiring Husnul K I Gusti Prahmana Indah Malasari Ivan Candra Dinata Kadim, Lina Arliana Nur Khadapi, Muammar Khair, Husnul Khairul, Habib Kristina Ananatasia Kristina Annatasia Leni Tri Ramadhayanti Lestari, Chintiya Wahyuni Indah lidya hasna Lidya Hasna Lishayani, Putri Lubis, Anjelia Alsar Lumbanbatu, Katen Luta, Devi Andriani M. Yogi Riyantama Isjoni Magdalena Simanjuntak Malau, Farid Reza Marto Sihombing Mayaza, Suha Baby Melda Pita Uli Sitompul Mili Alfhi Syari Muhammad Arif Ridho Muhammad Zarlis, Muhammad Muhammad, Zarlis N Novriyenni Nadila Rahmawati Nike Alpio Rizky Ningsih, Novia Novita Anggraini Novriyenni Nur Fariza Khairani Nurhayati Nurlaila Nurlaila Nurul Syahrani Pardede, Akim Manaor Hara PASARIBU, TIO RIA Prahmana , I Gusti Prahmana, I Gusti Pramudhita, Chika Prisa Abela Purba, Ramen Antonov Putri Purwani, Dea Nanda Raja Rizki Alanta Nasution Ramadani, Suci Rani Lestari Rani Nuraini Rani Nuraini Ratih Ratih Puspadini Reza Alexandra Rianty Zabitha Siregar rifa'i, Muhammad Rohana, Sherly Rusmin Saragih, Rusmin Sany Lubis, Fauzan Al An Sari Suwandi, Ema Selfira Selfira Selfira Selfira Yap Selfira, Selfira Sembiring, Hermansyah Sembiring, Indri Aurellia Apsari septian haryanto Septian Haryanto Sherly Eka Wahyuni Sihombing, Anton Sihombing, Marto Sihombing, Novena Putri Antonia Sima, Brema Arisma Simanjuntak, Magdalena Simanjuntak, Magdalena Sinaga, Ayu Puspita Sari Sinek Mehuli Br Perangin-Angin Siswan Syahputra Siti Nur Azizah, Siti Nur Solikhun Solikhun Sri Astuti Sri Hardiningsih Sundari, Yeni Sundari, Yeni Suria Alamsyah Putra Syahputra, Siswan Syahputra, Suria Alam Syahril Effendi Syari, Milli Alfhi T. Reza Pahlevi Teuku Reza Pahlefi Tiara Jelita Windy Indah Sary Sinaga Windy, Windy Alfira Yani Maulita Yel, Mesra Yusnan Sepriadi Ginting Yusnan Sepriadi Ginting Yusrina, Eli Yuyun Arnia Zuliani - Zulkifli Zulkifli