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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 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
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A COMPARATIVE EVALUATING NUMERICAL MEASURE VARIATIONS IN K-MEDOIDS CLUSTERING FOR EFFECTIVE DATA GROUPING Relita Buaton; Solikhun Solikhun
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 2 (2024): JITK Issue November 2024
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i2.5545

Abstract

The K-Medoids Clustering algorithm is a frequently employed technique among researchers for data categorization. The primary difficulty addressed in this investigation pertains to the extent of optimality achieved when varying distance computation methodologies are applied within the framework of K-Medoids Clustering. This study is primarily concerned with the application of K-Medoids Clustering, employing a multitude of distance calculation methods, specifically those involving numerical metrics. The aim is to undertake a comparative analysis of Davies-Bouldin Index (DBI) values in order to ascertain the most productive distance calculation technique. In this research, the distance calculation methodologies include Manhattan Distance, Jaccard Similarity, Dynamic Time Warping Distance, Cosine Similarity, Chebyshev Distance, Canberra Distance and Euclidean Distance. The dataset consists of sales data from Devi Cosmetics, covering the period between January and April 2022 and comprising 56 distinct sales items. The research provides an exhaustive evaluation of numerical metrics concerning the K-Medoids Clustering algorithm. The findings indicate that the optimal clustering is achieved using the Chebyshev distance, resulting in 9 clusters with a DBI value of 166.632. The study's contribution is that it can improve more optimal data grouping to help make decisions correctly.
Pengelompokan Penanganan Resiko Pada Kegiatan Panen Berdasarkan Alat Pelindung Diri Yang digunakan : (Studi Kasus: PT. Langkat Nusantara Kepong Kebun Padang Brahrang) Nur Fariza Khairani; Relita Buaton; Melda Pita Uli Sitompul
Modem : Jurnal Informatika dan Sains Teknologi. Vol. 2 No. 4 (2024): Oktober : Modem : Jurnal Informatika dan Sains Teknologi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/modem.v2i4.232

Abstract

Personal Protective Equipment (PPE) is essential for worker safety, especially in oil palm harvesting activities. PT Langkat Nusantara Kepong faces major challenges related to work safety, with analysis showing that work accidents still occur frequently in the Padang Brahrang Plantation. This indicates the need for an in-depth evaluation of the use of Personal Protective Equipment (PPE) to reduce the risk of work accidents. By using the clustering method to group data based on the type of Personal Protective Equipment (PPE) used and aims to provide recommendations for optimizing the use of personal protective equipment based on risk management and reducing the incidence of work accidents. From testing the results of cluster 3, cluster 4 and cluster 5 it can be concluded that clustering with 5 clusters provides the most efficient and precise results, followed by 4 clusters, while 3 clusters provide greater variation within clusters, indicating that clustering with fewer clusters is less able to capture subtle differences in the data.
Klasifikasi Tingkat Kepuasan Masyarakat Penggunaan BPJS Kesehatan di Kota Binjai Menggunakan K-Means Clustering Nadila Rahmawati; Relita Buaton; Indah Ambarita
Switch : Jurnal Sains dan Teknologi Informasi Vol. 2 No. 5 (2024): September : Switch: Jurnal Sains dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/switch.v2i5.188

Abstract

The health Social Security Administering Agency (BPJS) is a legal entity specifically assigned by the government to administer social security. Seen in the vision and mission of the Long Term Develompment Plan For the Health Sector 2005-2025, namely that the community is expacted to have the ability to access quality health services and also obtain heald insurance, namely that the community gets protection in meeting their basic health needs. Especially for the people of Binjai city, to see the level of satisfaction of peolbe using BPJS Health in the city of Binjai, it is necessary to build a clustering that can group the level of satisfaction in each domicile. Data Mining Grouping using the K-Menas Clustering algoritma metdhod, which is a process of processing quite large amounts of data using statistical methods, this producing a group of data. It is hoped that clustering can complete the grouping of satisfaction levels of BPJS user commuites in the city of Binjai. There are 400 data from correspondent responses from the community regarding the level of satisfaction in using BPJS Health in the city of Binjai. From the results of trials with 400 data carried out with MATLAB, it was found that group 3, cluster 1, had 244 data, cluster 2 had 69 data, cluster 3 had 87 data, group 4 cluster 1 has 78 data, cluster 2 68 data, cluster 3 has 109 data, group 5 cluster 1 has 63 data, cluster 2 has 63 data, cluster 3 has 145 data, cluster 4 has 24 data, cluster 5 has 100 data.
Prediksi Jumlah Pendonor Darah di Kabupaten Langkat Menggunakan Metode Regresi Linear Fajar Amalia Putri; Relita Buaton; Selfira Selfira
Switch : Jurnal Sains dan Teknologi Informasi Vol. 2 No. 5 (2024): September : Switch: Jurnal Sains dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/switch.v2i5.189

Abstract

A blood donor is someone who wants to donate their own blood to people in need without any element of coercion from anyone. Predicting the number of blood donors is very important and necessary to find out the number of blood donors in Langkat Regency in 2023-2024, and the prediction results can help PMI Langkat Regency in increasing the number of blood donors. The method applied in this prediction system is Linear Regression, where this analysis determines whether or not each variable is in accordance with the prediction results being tested and estimates that the value of the variable will increase or decrease each month. The prediction system is carried out using the RapidMiner application because this application is very appropriate for producing information output in the form of prediction results for the coming year. The prediction results obtained by testing using the Linear Regression method show increases and decreases every month. There are 11 months where there has been an increase and decrease in the predicted results and are in accordance with the data in 2023, then there is 1 month which has decreased in the predicted results and does not match the data in 2023. From the overall data results, it can be calculated the number of blood donors in Langkat Regency in 2023 and every month. Measuring the error level of prediction results using RMSE, the resulting accuracy level was 83.574%.
Pengelompokan Tingkat Kecerdasan berdasarkan Kecerdasan Ganda (Multiple Intelligence) Anak di Sekolah Menggunakan Metode Clustering: Studi Kasus: SD Islamiyah Adinda Maudia Savira; Relita Buaton; Juliana Naftali Sitompul
Switch : Jurnal Sains dan Teknologi Informasi Vol. 2 No. 5 (2024): September : Switch: Jurnal Sains dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/switch.v2i5.197

Abstract

Education is an important place for students to develop their potential based on their intelligence. Multiple intelligences offer an approach that considers the various potentials of students in the learning process. SD Islamiyah, as an educational institution with a vision to produce intelligent and creative generations, faces challenges in delivering learning that meets the needs of students. To address this issue, a system is needed that can analyze and group students based on their intelligence levels using the clustering method. This study is inspired by the application of data mining in the educational context, particularly in adapting the clustering method as applied in other related research. Previous research has demonstrated the success of the clustering method in accurately grouping data, as seen in studies related to flood warnings and cesarean operations. By applying a similar approach, this research aims to assist SD Islamiyah in identifying and grouping students based on their potential, thereby facilitating a more effective learning process tailored to the individual needs of students. The results of this study are expected to contribute positively to improving the quality of education at SD Islamiyah and provide a foundation for the development of more advanced decision support systems in the future
Penggunaan Metode Rough Set Pada Pola Minat Dan Bakat Siswa Dalam Menentukan Tema P5: Studi Kasus : SMPS Esa Prakarsa Febi Andini; Relita Buaton; Imeldawaty Gultom
Switch : Jurnal Sains dan Teknologi Informasi Vol. 2 No. 5 (2024): September : Switch: Jurnal Sains dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/switch.v2i5.210

Abstract

This research aims to identify the patterns of students' interests and talents at Esa Prakarsa Junior High School and apply the Rough Set method in data analysis to determine the most appropriate theme of the Pancasila Student Profile Strengthening Project (P5). The study involved data collection from 178 students through a questionnaire designed to explore their interests and talents. The results of the analysis showed a significant correlation between the patterns of interest and talents of students with the selection of the P5 theme. The Rough Set method successfully identified relevant rules, such as students who have an interest in the field of art are more suitable for the theme of sustainable lifestyle, while talented students in the field of sports are more in line with the theme of Build the Soul and Body. The use of Rosetta software in data analysis provides recommendations for interesting and relevant P5 themes, supporting the achievement of national education goals in forming a young generation with character and competence. This research is expected to provide guidance for schools in developing P5 themes that are more relevant and interesting for students, as well as improving learning outcomes based on their interest and talent characteristics.
Classification Of Students Based On Factors That Affect Student Learning Achievement Using The K-Means Clustering Algorithm (Case Study: STMIK Kaputama Binjai) Dea, Dea Puspita; Buaton, Relita; Khair, Husnul
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 1 (2024): October 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i1.546

Abstract

In the world of education, students are the main object of every educational implementation that always prioritizes disciplines that are beneficial to the students themselves. However, in lecture activities there are students who are diligent in participating in lecture activities and there are also those who rarely participate in lecture activities, this can be caused by internal and external factors, so that there can be significant variations in student learning achievements, with some achieving high grades, while others face difficulties in achieving the same achievements. Based on the description of the problem, the researcher conducted a study that aimed to group students based on factors that affect student learning achievement using the k-means clustering algorithm. The results of the research conducted produced 3 clusters with cluster 1 there were 5 data, the group of students with a very satisfactory predicate GPA (3.50-4.00), supported by both internal and external factors (interval 3.1-4). Cluster 2 has 3 data, the group of students with a satisfactory predicate GPA (3.00-3.49), supported by both internal and external factors (interval 2.1-3), and cluster 3 has 5 data, the group of students with a satisfactory predicate GPA (3.00-3.49), supported by both internal and external factors (interval 3.1-4).
Implementation of Chatbot Artificial Intelligence in a Company Website to Improve Customer Service Automatically Using the TF-IDF Method Hayati, Radhiah; Buaton, Relita; Ramadani, Suci
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 1 (2024): October 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i1.584

Abstract

In today's digital age, improving customer service is one of the keys to business success. Successfully retaining and attracting new customers is a challenge that must be faced. The application of chatbot technology powered by artificial intelligence (AI) on business websites has been proven to provide more efficient and responsive customer service. This research aims to develop and implement an AI chatbot that uses the TF-IDF (Term Frequency-Inverse Document Frequency) method to automatically understand and answer customer queries. The TF-IDF method is used to extract key features from the text of customer questions and match them with the most relevant answers in the database. The results of implementing this AI chatbot showed a significant improvement in the speed and quality of customer service responses, thus helping to improve customer satisfaction and company performance. This research provides valuable insights for businesses looking to integrate AI technology into their customer service strategy.
Application of Apriori to Determine Correlations between Source Competencies Human Resources with Education and Working Period Reza Alexandra; Buaton, Relita; Suria Alamsyah Putra
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 1 (2024): October 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i1.626

Abstract

Human resource competence (HR) is a key factor in supporting organizational performance. Referring to several problems in the Binjai City BKD, such as there is a difference between the competencies possessed by employees and the competencies needed to carry out their duties and responsibilities effectively, the placement of employees that are not in accordance with the competencies, the absence of a system to map and monitor employee competencies can cause difficulties in identifying development needs, as well as in the placement of appropriate employees. Employee competency mapping is relevant in the implementation of human resource management, both in planning, development and employee placement activities. Therefore, it is necessary to carry out competency mapping that can be used for various human resource management needs and this is in accordance with the priority program that will be carried out in the 2025 RKPD, namely improving the quality of innovative human resources. This study uses a priori algorithm with the Rapidminer application to be able to provide correlation results of human resource competencies. From the results of the research, a correlation was formed between human resource competence and education and work period, namely 8 association rules and the highest best rule was obtained with support of 32% and confidence value of 99.4%.
Design and Build Temperature and Humidity Control Equipment in IoT-Based Rice Storage Windy, Windy Alfira; Buaton, Relita; Sihombing, Marto
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 1 (2024): October 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i1.648

Abstract

This research aims to design and build a temperature and humidity control device in an Internet of Things (IoT)-based rice storage bin using the Blynk platform, ESP8266 module, DHT22 sensor, buzzer, 2-channel relay, fan, and lamp. The quality of rice is greatly affected by the conditions of the storage environment, especially temperature and humidity. Therefore, a system is needed that is able to monitor and control these two parameters in real-time to maintain the quality of rice during storage. The system is designed to use a DHT22 sensor to detect temperature and humidity, and then the data is sent to a ESP8266 microcontroller. A 2-channel relay sets the fan and lights to adjust the temperature and humidity, while the buzzer serves as a warning alarm. In addition, the system is equipped with an automatic notification feature through the Blynk application that informs users if the temperature or humidity exceeds a predetermined limit.
Co-Authors Achmad Fauzi 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 Eli Yusrina 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 I Gusti Prahmana I Gusti Prahmana Indah Malasari Ivan Candra Dinata Kadim, Lina Arliana Nur Katen Lumbanbatu Khair, Husnul Kristina Ananatasia Kristina Annatasia Leni Tri Ramadhayanti Lestari, Chintiya Wahyuni Indah Lidya Hasna lidya hasna Lubis, Anjelia Alsar Magdalena Simanjuntak magdalena simanjuntak Malau, Farid Reza Marto Sihombing Melda Pita Uli Sitompul Mesra Yel Mili Alfhi Syari Muammar Khadapi 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 Nurlaila Nurlaila Nurul Syahrani Pardede, Akim Manaor Hara Prahmana , I Gusti 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 Sembiring, Hermansyah Septian Haryanto septian haryanto Sherly Eka Wahyuni Sihombing, Anton Sihombing, Marto Simanjuntak, Magdalena Sinaga, Ayu Puspita Sari Sinek Mehuli Br Perangin-Angin Siswan Syahputra Solikhun Solikhun Solikhun Solikhun, Solikhun Sri Astuti Sri Hardiningsih suci ramadani Suha Baby Mayaza Sundari, Yeni Sundari, Yeni Suria Alamsyah Putra 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 Yuyun Arnia Zarlis Muhammad Zuliani Zuliani Zulkifli Zulkifli