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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
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Grouping Data On Infrastructure Development In Langkat District Using The Clustering Method (Case Study: PUPR, Langkat Regency) Diva Alifya; Buaton, Relita; Ramadani, Suci
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.278

Abstract

A building is a man-made structure consisting of walls and a roof permanently erected in a place. Buildings can also be called houses and buildings, namely all facilities, infrastructure or infrastructure in culture as well as human life in building their civilization. Public Works and Public Housing (PUPR) play an important role in increasing the development of national infrastructure in Indonesia so that PUPR can assist in clustering research in infrastructure development in Langkat Regency which is very large every year by grouping the data based on activity names, company names, sub-districts development, and look at the last four years.To classify existing development infrastructure in Langkat Regency with the previous system used by the PUPR Service which is still running by recording in a ledger and hindering reporting performance in grouping PUPR service infrastructure development in road construction, bridge construction and others. So that the existence of grouping using the clustering method helps the PUPR service in clustering infrastructure development data in Langkat Regency to be more effective and efficient.The clustering method is one of the methods that can be applied in classifying infrastructure development data taken from the analysis of Langkat Regency PUPR data regarding developments that have taken place in several sub-districts in Langkat Regency. This clustering method has been widely used by previous studies to group data
Application of Data Mining in Analyzing the Effect of Parents' Employment and Education Level on Student Behavior Using the A PRIORI Method (Case Study: SDN 024769 Binjai) Mayaza, Suha Baby; Buaton, Relita; Ramadani, Suci
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.279

Abstract

Behavior is a person's reaction to a stimulus that comes from the external environment. Parents are one of the main factors in the formation of children's behavior. This study aims to find out the effect of parents' work and education on student behavior. By using RapidMiner in testing 234 SDN 024769 Binjai student data, using the Apriori method and setting a minimum support value of 8% and 70% confidence, 1207 rules were obtained in the entire set and 2 rules in 9 itemsets. And the best rule with the highest value is obtained, if the father's job is self-employed, the mother's job is self-employed, the father's last education is high school, the mother's last education is high school, the time the father spends working is more than 8 hours per day, the time the mother spends working is more than 8 hours per day, the time the father spends on family is every day, and the time the mother spends on family is every day then the student has good behavior at school, with a support value of 8.5% and a certainty value of 95.2%.
Application of the Clustering Algorithm for the Classification of General Criminal Cases at the Binjai District Attorney's Office Ratih; Buaton, Relita; Lumbanbatu, Katen
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.296

Abstract

The Binjai District Attorney's Office in carrying out its duties and functions, one of which handles general crimes, where so far the SPDP (Warranty to Commence Investigation) from the police that has entered the Binjai District Prosecutor's Office amounted to approximately 50 (fifty) cases each month. This amount consists of several types of general criminal cases. It is known that the types of general criminal cases amount to approximately 215 (two hundred and fifteen) types of cases, from this data, a method of classifying/clustering is needed from the types of cases that exist each month so that the data can be processed so as to produce the highest, moderate and highest scores. the lowest value of a type of case. The Binjai District Attorney's Office often receives requests for data from other ministries or agencies such as the BPS (Central Statistics Agency), the National Commission on Women and the National Commission on Children in the form of data recapitulation of crimes against women and children as perpetrators of crimes. The Binjai District Attorney's Office has a case handling system where the recapitulation cannot be taken directly but instead collects data manually, because the existing case handling system does not have the recapitulation as requested.The application of clustering has been carried out by many previous researchers. Among them, the K-Means Clustering Algorithm Analysis Mapping the Number of Crimes. The research was carried out using a data mining model in classifying illegal fishing with the K-Means algorithm analysis by determining the shortest distance using the eulclidean distance, more optimal than using the mahattan distance and chbchep distance in classifying student achievement, determining the centroid (central point) in the early stages of the algorithm K-Means is very influential on cluster results as the results of tests carried out using 267 records with different centroids produce different cluster results as well, a clustering model is obtained that can be used for illegal fishing in decision making for illegal fishing crimes high, medium, moderate .
Klasifikasi Tingkat Minat Belanja Online Melalui Media Sosial pada Masyarakat di Kota Binjai Meggunakan Algoritma K-Means Dhea Agustina Akmal; Relita Buaton; Anton Sihombing
Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi Vol. 2 No. 3 (2024): Agustus: Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Publisher : Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/bridge.v2i3.169

Abstract

The advancement of information technology and globalization has transformed shopping behaviors, with social media becoming the primary platform for online shopping. This study aims to analyze the online shopping preferences of residents in Binjai City through social media using clustering methods, specifically the K-Means algorithm. Data were collected via a questionnaire targeting 523 respondents in Binjai City, focusing on variables such as gender, age, and the social media platforms used. Clustering methods are employed to group online shopping data into representative clusters, helping identify community preferences for specific social media platforms for shopping. Matlab is used to process the data and generate relevant insights into online shopping patterns, facilitating decision-making regarding the selection of the most suitable social media platform for transactions.The findings of this study are expected to provide valuable insights for both sellers and buyers in determining the most effective social media platforms for online shopping. Additionally, the results will be useful for residents of Binjai City to understand and choose the social media platforms that best meet their online shopping needs.
Penerapan Metode K – Means Clustering untuk Menentukan Kepuasan Mahasiswa terhadap Fasilitas Sarana dan Prasarana Kampus di STMIK Kaputama Binjai Dicha Mutia Dhani; Relita Buaton; I Gusti Prahmana
Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi Vol. 2 No. 3 (2024): Agustus: Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Publisher : Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/bridge.v2i3.170

Abstract

Technological advancements in the era of globalization demand improvements in the quality of academic services and educational facilities in institutions. STMIK Kaputama is committed to creating a conducive academic environment by providing optimal facilities. This study aims to determine student satisfaction with campus facilities using the K-Means Clustering method. Data were obtained from recapitulated survey reports and questionnaires filled out by students in 2024. The K-Means Clustering method was chosen for its ability to group students based on their similar preferences for campus facilities. The results show that, in general, students are fairly satisfied, though their preferences for specific facilities vary. These findings can be used to make recommendations for the improvement and development of campus facilities, help STMIK Kaputama allocate resources more efficiently, and plan strategies to enhance the quality of facilities to meet student expectations.
Pengelompokan Data Kasus Keracunan Makanan Biologis Berdasarkan Faktor Penyebab Menggunakan Metode Clustering Dwi Astuti; Relita Buaton; Magdalena Simanjuntak
Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi Vol. 2 No. 4 (2024): November: Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Publisher : Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/bridge.v2i4.199

Abstract

Cases of biological food poisoning can be caused by several causative factors, one of which is a food processing site that does not meet health requirements. According to the BPOM report (2016) cases of food poisoning in Indonesia in 2016 reached 1,068 cases. In 2016, 60 extraordinary events (KLB) of food poisoning were reported by 31 BB/BPOM throughout Indonesia. From the many cases of food poisoning that occur, it is necessary to take action in prevention by processing data on existing cases of poisoning to follow up on existing problems to reduce the number of cases of food poisoning by using a system on a computer so that the managed data can be processed quickly to obtain further information. Therefore the author wants to use a system with the clustering method to assist in processing data on biological poisoning cases grouping objects based on the characteristics of each object. Based on the research conducted, it can be seen that in cluster 2 in the dasta group of biological poisoning cases there are 11 data with centroid point age (x) 2, namely 12-16 years, centroid point on the type of poisoning (y) 6.36, namely sandwiches, and centroid point on the causative factor (z) 2.9, namely Gram-negative rod-shaped bacteria which are usually found in the intestines of humans and warm-blooded animals.
Jaringan Saraf Tiruan (JST) Memprediksi Penjualan UMKM Kota Binjai dengan menggunakan Metode Backpropagation Sherly Eka Wahyuni; Relita Buaton; Suci Ramadani
Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi Vol. 2 No. 4 (2024): November: Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Publisher : Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/bridge.v2i4.214

Abstract

The development of information technology that is currently developing serves to facilitate, accelerate, benefit and provide other alternatives for people who have businesses and have a big influence in the future. One of the things that is very influential is the sale of MSMEs. MSMEs are productive businesses owned by individuals or business entities that have met the criteria as micro businesses that have an important role in the economy because they provide employment, encourage local economic growth, and create innovation. MSMEs still face challenges such as limited access to financing, digital readiness, and marketing access that hinder the development of MSMEs. Therefore, it is necessary to take action to predict MSME sales in Binjai City using the backpropagation method so that later it can create new innovations and encourage community economic growth. Based on the process carried out using the backpropagation method, it can be seen that the value obtained has reached more than the predetermined target with a target value (t) of 0.26, learningrate 0.2, maximum epoch 10000 target error 0.01.
PENERAPAN METODE APRIORI UNTUK MENGIDENTIFIKASI POLA PENGHAPUSAN ASET PEMERINTAHAN KOTA BINJAI Sihombing, Novena Putri Antonia; Buaton, Relita; Selfira
Jurnal Informatika Kaputama (JIK) Vol 9 No 2 (2025): Volume 9, Nomor 2, Juli 2025
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jik.v9i2.1144

Abstract

Government assets are essential components for supporting operational performance and public services. Over time, some assets depreciate and require removal to avoid unnecessary budget burdens. However, asset disposal processes in government institutions are often still manual and not data-driven, which can lead to inefficiencies. This study aims to apply the Apriori algorithm to discover asset disposal patterns in the Binjai City Government. The data used includes asset attributes such as Regional Government Organizations (OPD), Item Type, Age, Brand/Type, Material, and Acquisition Method. The method employed is data mining with the Apriori algorithm, and the analysis is supported by the RapidMiner tool. The results reveal strong associative patterns among specific asset attributes that tend to be disposed of, such as assets over 10 years old, made of synthetic materials, and acquired through purchase. Identifying these patterns facilitates more efficient, transparent, and objective decision-making in asset disposal. This research contributes to the development of data-driven asset management systems and supports bureaucratic reform in local government institutions. Keywords: Data Mining, Apriori Algorithm, Asset Disposal, Local Government, RapidMiner
Grouping of Student Learning Interest Data after the Pandemic at SMK Abdi Negara Binjai Using the K-Means Algorithm Clustering Method Ivan Candra Dinata; Relita Buaton; Novriyenni
International Journal of Health Engineering and Technology Vol. 1 No. 3 (2022): IJHET-SEPTEMBER 2022
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (827.988 KB) | DOI: 10.55227/ijhet.v1i3.75

Abstract

The online learning system is a learning system without face to face directly between teachers and students but is carried out online using the internet network. This is in accordance with the regulation of the Minister of Education and Culture of the Republic of Indonesia regarding Circular Letter Number 4 of 2020 concerning the Implementation of Educational Policies in the Emergency Period for the Spread of Corona Virus Disease (COVID-19). Abdi Negara Vocational School is one of the schools in Binjai City that carries out offline and online learning for its students, learning began in March 2020 when COVID-19 began to hit Binjai City. The COVID-19 pandemic has had many impacts on the state of society, one of which is in the field of education. All educational institutions are trying hard to maximize their respective ways of learning according to the circumstances of their students. Abdi Negara Vocational School which follows government regulations through the Minister of Education and Culture of the Republic of Indonesia also carries out online learning, with the aim that teachers, staff and students are not infected with COVID-19 and can break the chain of spreading the virus. With these conditions, SMK Abdi Negara Binjai needs to build a system that can classify student learning interests, so that it can be used as material for consideration and evaluation of student learning outcomes. Data grouping can apply the Data Mining process with the K-Means algorithm Clustering method which is a process of processing very large amounts of data using statistical, mathematical methods, to utilizing Artificial Intelligence technology to produce a data group. The system is designed with the MATLAB R2014a programming application, after testing with the system the results are that in group 1 there are 836 data, group 2 there are 178 data and group 3 there are 91 data with a total of 1105 student data from the questionnaire results on August 31, 2022 .
Use of internet of things (IOT) on fish feeding tools with nodemcu Khairul, Habib; Buaton, Relita; Syahputra, Siswan
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.v3i1.1216

Abstract

In everyday life whether in the city or in the countryside, there are lots of fish keepers in both large, medium sized ponds or small ones. Raising fish is an activity people who are very popular from the past until now, because ease of maintenance and care that makes most people want to cultivate fish. Fish kept in considered pond must give time to feed so that the fish requires a regular and continuous feeding schedule. ESP8266 NodeMCU is an integrated chip component that designed for today's connected world. these chips offers a complete, unified Wi-Fi networking solution that can used as an application provider or to sell all functions Wi-Fi networking to other application processors. One of its uses namely as an Automatic Fish Feeder Using ESP8266 Based on the Internet of Things (IOT). By using the components of the tool above as well as some supporting software When the tool runs, the fish feeder can automatically work in accordance with the schedule options that have been previously arranged, and capable displays data to web pages in the form of notifications when feed has been given and when the reservoir is empty or exhausted.
Co-Authors Achmad Fauzi Ade Chairany Adek Maulidya 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 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, 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