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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) Journal of Applied Data Sciences 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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Data Driven Evaluation of the New Learning Paradigm Using Machine Learning for Optimizing Graduate Outcomes Mesra Betty Yel; Relita Buaton; Yuma Akbar; Novriyenni Novriyenni
Journal of Applied Data Sciences Vol 7, No 3: September 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i3.1152

Abstract

In preparing students to face digital literacy and critical thinking transformations rapid, universities are therefore required to design and implement learning processes that are innovative, adaptive, and differentiated, in accordance with the new learning paradigm. However, the unemployment rate in Indonesia remains high approximately 5.98% vocational high school graduates and 4.8% diploma and university graduates. To develop highly skilled human resources, higher education must strengthen the competencies of students as future agents of change entering the workforce. The persistent unemployment rate among diploma and university graduates presents a national challenge that may hinder the progress of human capital development. Therefore, this study aims to develop a classification and association model linking new learning paradigm programs to student learning outcomes, in order to generate new knowledge and identify correlations among grade point average, employment waiting period, occupational field, and graduate income. The research employs a machine learning approach using association rule mining and the K-Nearest Neighbors algorithm to analyze correlations and predict graduate outcomes. Based on data processing of 450 graduate data who participated in the new paradigm learning program, the findings indicate that graduates under the new learning paradigm with grade point average ≥ 3.50 are significantly more likely to secure employment within ≤ 2 months, support = 20%, confidence = 100% based on processing a data set of 450 data. Participants in the teaching assistance program tend to experience longer waiting periods ≥ 6 months and lower initial earnings compared to those from other new learning paradigm pathways. Conversely, graduates involved in certified internships or independent study programs demonstrate higher earnings potential and stronger academic performance. The results confirm that the new learning paradigm exerts a positive influence on graduate employability, income level, and academic achievement, especially through experiential and industry-oriented learning mechanisms.
PENGCLUSTERAN JENIS USAHA UKM BERDASARKAN PROGRAM BANTUAN DI KOTA BINJAI MENGGUNAKAN ALGORITMA K-MEANS Siti Nur Azizah; Relita Buaton; 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.
Penerapan algoritma naive bayes untuk memprediksi bantuan subsidi upah bsu di kantor pos cabang binjai mayla zuhrina; Relita Buaton; Selfira
Jurnal Nasional Teknologi Komputer Vol 6 No 3 (2026): Juli 2026
Publisher : CV. Hawari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jnastek.v6i3.507

Abstract

Bantuan Subsidi Upah (BSU) merupakan salah satu program pemerintah yang bertujuan membantu pekerja atau buruh dalam menghadapi tekanan ekonomi serta menjaga daya beli masyarakat. Dalam proses penyalurannya, Kantor Pos Cabang Binjai memiliki peran penting sebagai lembaga penyalur bantuan. Namun, proses analisis dan pengolahan data penerima bantuan masih menghadapi kendala, seperti ketidaktepatan sasaran dan keterbatasan dalam melakukan analisis terhadap data historis penerima bantuan. Penelitian ini bertujuan untuk menerapkan algoritma Naïve Bayes dalam memprediksi penerima Bantuan Subsidi Upah (BSU) di Kantor Pos Cabang Binjai. Metode yang digunakan dalam penelitian ini adalah metode data mining dengan algoritma Naïve Bayes sebagai metode klasifikasi. Data yang digunakan berupa data historis penerima BSU yang diperoleh dari Kantor Pos Cabang Binjai. Variabel yang digunakan dalam proses prediksi meliputi usia, jenis kelamin, status pekerjaan, pendapatan, wilayah domisili, tahun penerimaan, dan status penerimaan BSU. Hasil penelitian menunjukkan bahwa penerapan algoritma Naïve Bayes dapat digunakan untuk melakukan klasifikasi dan prediksi terhadap status penerimaan Bantuan Subsidi Upah berdasarkan data historis yang tersedia. Sistem yang dibangun mampu membantu proses pengolahan data penerima bantuan secara lebih cepat dan terstruktur dengan menghasilkan prediksi berupa kategori menerima atau tidak menerima bantuan berdasarkan nilai probabilitas yang diperoleh dari proses perhitungan algoritma Naïve Bayes. Berdasarkan penelitian yang dilakukan, dapat disimpulkan bahwa algoritma Naïve Bayes dapat diterapkan sebagai metode pendukung dalam proses analisis prediksi penerima BSU di Kantor Pos Cabang Binjai.
Optimization of Higher Education Internal Quality Audits Based on Artificial Intelligence Relita Buaton; Zarlis Muhammad; Elviwani; Ami Dilham
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 2 (2022): February 2022
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (404.155 KB) | DOI: 10.59934/jaiea.v1i2.83

Abstract

Internal Quality Audit is an independent and documented systematic testing process to ensure that the implementation of activities in higher education is in accordance with the procedures and the results are in accordance with the standards to achieve the goals of the institution. Quality can be guaranteed by ensuring that each individual has the skills he needs to do the job properly. Quality orientation in development life in Indonesia is something that is very urgent, must be supported and developed in order to respond to the trend of global competition. There are significant differences in the accreditation and quality assurance system with the previous version, it is necessary to develop a strategy by building an artificial intelligence-based system. The method used is to build an online system by involving experts and assessors to develop concepts in accordance with the points of the 9 criteria accreditation forms, to build a digital quality audit form for matching and the level of conformity between the implementation of higher education standards and the standards set, the benefit is to help universities implement digital and intelligent based internal quality audits, know the tri dharma standards of higher education that must be improved, maintained and deviated
New Paradigm E-Learning Model Based on Artificial Intelligence: New Paradigm E-Learning Model Based on Artificial Intelligence Relita Buaton; Achmad Fauzi; Mesra Yel
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 2 No. 1 (2022): October 2022
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v2i1.116

Abstract

This research concerns the application of a new paradigm learning that provides flexibility for educators to formulate learning designs and assessments according to the characteristics and needs of students. To improve the quality of education in Indonesia, the government has made various breakthroughs and most recently is a new paradigm learning system to create a Pancasila student profile that accommodates all differences in students, is open to all and provides the needs needed by each individual. Therefore an application system is needed to support learning a new paradigm based on artificial intelligence, artificial intelligence plays a role in knowing the level of abilities and needs of students and follow-up learning according to the needs and abilities of students available in online learning media. With the e-learning application, a new paradigm based on intelligence is produced by smart adaptive e-learning that can accommodate each individual or student with a background of different levels of abilities, weaknesses, talents and interests with artificial intelligence and machine learning technology approaches that will identify students with a diagnostic assessment that is used as a recommendation for planning learning according to the needs and abilities of students
Model of the Independent Learning Campus Internal Quality Assurance System Program based on Artificial Intelligence: Model of the Independent Learning Campus Internal Quality Assurance System Program based on Artificial Intelligence Muhammad Zarlis; Elviwani; Ami Dilham; Relita Buaton
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 2 No. 1 (2022): October 2022
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v2i1.117

Abstract

Research on models of internal quality assurance systems in tertiary institutions online and digitally based on artificial intelligence in supporting the Merdeka Learning Campus Merdeka program in accordance with the cycle of determination, implementation, evaluation, control and improvement. The system is supported by an artificial intelligence approach to determine the implementation and achievement of the Merdeka Learning Campus Merdeka standard and to help universities detect early the impact of the implementation of Merdeka Learning Kampus Merdeka on the development of student competence. The implementation of the Merdeka Learning Campus Merdeka program is recorded in a database with cycles of Determination, Implementation, Evaluation, Control and Improvement to analyze compliance with the establishment, implementation, evaluation, control and improvement of standards for one cycle each year. At the evaluation stage, standard achievement will be produced whether it exceeds, is achieved or deviates to be followed up at the control and improvement stage. With this application, it helps tertiary institutions carry out the standards for the Merdeka Learning Campus Merdeka program standards to be carried out and developed according to the cycle of Determination, Implementation, Evaluation, Control and Improvement
Implementation of Mechine Learning Eligibility for Customer Credit Payments at Bank BTN Using the K – Nearst Neighbor Algorithm Ema Sari Suwandi; Relita Buaton; Rusmin Saragih
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 Putri Lishayani; Relita Buaton; Tio Ria Pasaribu
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; Relita Buaton; Suci Ramadani
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 Muhammad Rifa'i; Relita Buaton; I Gusti Prahmana
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.
Co-Authors ., Novriyenni Achmad Fauzi ACHMAD FAUZI Ade Chairany Adek Maulidya Adian Fahreza Surbakti Adinda Maudia Savira Ajisro Siringoringo Akbar, Yuma 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 Betty Yel, Mesra 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 Elviwani Ema Sari Suwandi 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 I Gusti Prahmana Indah Malasari Ivan Candra Dinata Kadim, Lina Arliana Nur Katen Lumbanbatu Khadapi, Muammar Khair, Husnul Khairul, Habib Kristina Ananatasia Kristina Annatasia Leni Tri Ramadhayanti Lestari, Chintiya Wahyuni Indah Lidya Hasna lidya hasna Lubis, Anjelia Alsar Luta, Devi Andriani M. Yogi Riyantama Isjoni Magdalena Simanjuntak Malau, Farid Reza Marto Sihombing mayla zuhrina Melda Pita Uli Sitompul Mesra Yel Mili Alfhi Syari Muhammad Arif Ridho Muhammad Rifa'i Muhammad Zarlis Muhammad Zarlis, Muhammad N Novriyenni Nadila Rahmawati Nike Alpio Rizky Ningsih, Novia Novita Anggraini Novriyenni Nur Fariza Khairani Nurhayati Nurlaila Nurlaila Nurul Syahrani Pardede, Akim Manaor Hara Prahmana , I Gusti Prahmana, I Gusti Pramudhita, Chika Prisa Abela Purba, Ramen Antonov Putri Lishayani Putri Purwani, Dea Nanda Raja Rizki Alanta Nasution Ramadani, Suci Rani Lestari Rani Nuraini Rani Nuraini Ratih Ratih Puspadini Reza Alexandra Rianty Zabitha Siregar Rohana, Sherly Rusmin Saragih, Rusmin Sany Lubis, Fauzan Al An Selfira 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 Azizah, Siti Nur Solikhun Solikhun Sri Astuti Sri Hardiningsih Suha Baby Mayaza 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 Tio Ria Pasaribu Windy Indah Sary Sinaga Windy, Windy Alfira Yani Maulita Yusnan Sepriadi Ginting Yusnan Sepriadi Ginting Yusrina, Eli Yuyun Arnia Zarlis Muhammad Zuliani - Zulkifli Zulkifli