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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 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
Buaton, Relita
STMIK Kaputama
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Implementation of Mechine Learning Eligibility for Customer Credit Payments at Bank BTN Using the K – Nearst Neighbor Algorithm Sari Suwandi, Ema; Buaton, Relita; Saragih, Rusmin
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.v3i1.246

Abstract

Credit is the provision of money or bills that can be equated with that, based on a loan agreement or agreement between a bank and another party that requires the borrower to pay off the debt after a certain period of time with interest (Government of Indonesia, 1998). In its initial development, credit had a function in stimulating mutual assistance aimed at meeting needs, both in the field of business and meeting daily needs.In developing applications, it is necessary to predict applications at Bank BTN Medan accurately, accurate prediction results are very important in showing the right rating and decision-making in selecting customers. When customers experience arrears, the system used by Bank BTN Medan is still manual and has not applied predication in credit arrears to customers of Bank BTN Medan. Tests carried out in this test use a credit customer dataset from Bank BTN Medan. This study predicts the eligibility of customer credit payments at Bank BTN with the K – Nearst neighbor algorithm. The prediction of the level of smoothness of credit payments is made using K-Nearest Neighbor in order to be able to predict the smoothness of future credit payments.
Determining The Selection Of Departments At Abdi Negara Vocational School Using The Additive Ratio Assessment (Aras) Method Lishayani, Putri; Buaton, Relita; Pasaribu, Tio Ria
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.v3i1.251

Abstract

Along with the occurrence of competition and the development of technology and information in the current era of globalization requires skilled and ready-to-use human resources in the world of work. The efforts made are to improve the quality of education in Indonesia which always receives attention from various parties. One way to improve education is to determine the right majors at Vocational High Schools (SMK). The differences in each student with a different background must be considered because they can determine whether student achievement is good or bad. In ddition, the decision also greatly influences the alternative process chosen, especially in choosing the concentration of majors that are in accordance with the skills and expertise of students. Based on the author's observations at ABDI NEGARA VOCATIONAL SCHOOL through data collection both by conducting interviews and through available documents, the reasons students choose majors are usually based on student parents' references, besides that due to trend reasons (most students take that major). Therefore, through research using Decision Support Systems, it is hoped that it can provide recommendations to find out which majors to choose according to the interests or abilities of each student. So that there are no problems regarding failure or dropping out of school (drop out).
IoT-based Hydroponic Plant Monitoring System Fadillah, Fadillah; 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.v3i1.255

Abstract

The Industrial Revolution 4.0 has an impact in the form of changes in various fields of human civilization, one of which is the agricultural sector. By applying IoT technology, hydroponic plants will effectively be accurate. IoT has room for improvement in the quality and quantity of agricultural production because it facilitates the automation of monitoring various processes with high precision This research uses the prototype method. Which uses the concept of direct monitoring and allows iterative changes to be made until the desired results are achieved. So this prototype method makes it possible to display the display directly. The microcontroller used is ESP32 which is connected to 3 sensors, namely the TDS sensor, DHT11 sensor and HC-SR04 sensor which are directly updated in the blynk application. In making the software program used is the Arduino IDE. Implementation of the tool is carried out on a floating raft installation. This iot-based hydroponic plant monitoring system has been successfully made and is able to monitor well. Because the system made is related to water, it is necessary to design a tool that is safer and has more protection so that it can’t only run well but also safer for users and a high level of durability.
Sentiment Analysis Using Text Mining Techniques On Social Media Using the Support Vector Machine Method Case Study Seagames 2023 Football Final Rifa'i, Muhammad; Buaton, Relita; Prahmana, I Gusti
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.v3i1.274

Abstract

This thesis aims to analyze sentiment on text data from social media related to the 2023 SEA Games, especially in the final match of the soccer sport. The method used is the Text Mining Technique with the SVM (Support Vector Machine) algorithm to classify user sentiment as positive or negative regarding the match. Text data is retrieved from various social media platforms during and after the match. The results of the sentiment analysis are expected to provide insight into the public's view of the sporting event. This research can contribute to the understanding of public sentiment towards the 2023 SEA Games final football match through the analysis of text data from social media.
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): Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Publisher : Asosiasi Riset Teknik Elektro 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): Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Publisher : Asosiasi Riset Teknik Elektro 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): Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Publisher : Asosiasi Riset Teknik Elektro 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.
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 magdalena simanjuntak Magdalena Simanjuntak 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 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 Sinaga, Ayu Puspita Sari Sinek Mehuli Br Perangin-Angin Siswan Syahputra Siti Nur Azizah, Siti Nur Solikhun Solikhun Solikhun 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