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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal sistem informasi, Teknologi informasi dan komputer Jurnal TIMES CESS (Journal of Computer Engineering, System and Science) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Martabe : Jurnal Pengabdian Kepada Masyarakat J-SAKTI (Jurnal Sains Komputer dan Informatika) KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) The IJICS (International Journal of Informatics and Computer Science) JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Informasi dan Komputer TIN: TERAPAN INFORMATIKA NUSANTARA Brahmana : Jurnal Penerapan Kecerdasan Buatan Jurnal Tunas Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Nusantara Hasana Journal Journal of Informatics Management and Information Technology KLIK: Kajian Ilmiah Informatika dan Komputer J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Pengabdian Kepada Masyarakat Jurnal Janitra Informatika dan Sistem Informasi Journal of Artificial Intelligence and Engineering Applications (JAIEA) JOMLAI: Journal of Machine Learning and Artificial Intelligence JOURNAL OF ICT APLICATIONS AND SYSTEM Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal Gemilang Informatika (GIT)
Jaya Tata Hardinata
Universitas HKBP Nommensen Pematangsiantar
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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IMPLEMENTASI DATA MINING MENGGUNAKAN ALGORITMA APRIORI DALAM MENENTUKAN PERSEDIAAN BARANG (STUDI KASUS : TOKO SINAR HARAHAP) Putri Mai Sarah Tarigan; Jaya Tata Hardinata; Hendry Qurniawan; Muhammad Safii; Riki Winanjaya
JUST IT : Jurnal Sistem Informasi, Teknologi Informasi dan Komputer Volume 12 No 2 Tahun 2022
Publisher : Universitas Muhammadiyah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24853/justit.12.2.%p

Abstract

UMKM ialah kegiatan usaha kecil ekonomi rakyat yang berskala kecil dan dilindungi dari kompetisi usaha yang tak sehat dan tak setara. Wirausaha yang bergerak dibidang pertokoan memiliki prospek yang menjanjikan, karena dapat melayanin masyarakat dengan kategori ekonomi menengah kebawah dan ke atas serta bisa mempermudah masyarakat untuk berbelanja keperluan tiap hari tanpa harus belanja ke supermarket atau swalayan. Namun persediaan barang atau bahan kebutuhan yang tidak dilakukan secara optimal dapat menyebabkan kekosongan pada barang atau bahan kebutuhan tersebut. Hal tersebut juga terjadi pada toko sinar harahap yang sering mengalami kekosongan pada persediaan beberapa barang dan kebutuhan yang di cari oleh pelanggan, ini di akibatkan dari tidak adanya kebiasaan pengontrolan persediaan pada toko. Maka penelitian ini bertujuan untuk melihat barang dan kebutuhan apa saja yang dibutuhkan oleh pelanggan toko. Penelitian ini menggunakan beberapa variabel yaitu tanggal transaksi, nama produk serta jumlah penjualan/pembelian. Maka, dari hasil penelitian menggunakan algoritma apriori tersebut akan di dapat data nama barang yang paling banyak terjual untuk di jadikan sebagai antisipasi persediaan barang agar tidak mengalami kekosongan yang dapat menyebabkan pelanggan kecewaKata Kunci: persediaan, barang, penjualan, data mining, algoritma apriori
Pemanfaatan Aplikasi Computer Based Test (CBT) Pada SMA swasta HKBP Hutabayuraja untuk meningkatkan efektivitas proses evaluasi Belajar Siswa Jaya Tata Hardinata; Reagan Surbakti Saragih; Dudes Manalu; Christa Voni Roulina Sinaga; Ferri Ojak Immanuel Pardede
Jurnal TUNAS Vol 4, No 1 (2022): Edisi November
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jtunas.v4i1.89

Abstract

Utilizing Computer Based Test (CBT) application at HKBP Hutabayuraja private high school can enhance the effectiveness of the student learning evaluation process by improving accuracy and objectivity, saving time and costs, and motivating students. However, the lack of knowledge among teachers and staff about CBT remains a major obstacle in implementing this technology. Hence, socializing and training teachers and staff is crucial to maximize the benefits of this technology, while also ensuring the protection of student data from unauthorized use. The CBT application provides flexibility in terms of time and place, as it can be accessed through a computer or mobile device, allowing students to carry out learning evaluations anytime and anywhere. To optimize its usage, adequate training and socialization for teachers and staff is necessary. The use of CBT applications offers numerous benefits for both teachers and students in the learning evaluation process, highlighting the need for broader implementation of technology such as CBT applications to increase efficiency and effectiveness in evaluating student learning.
Application of Data Mining on Patterns of Sales of Goods in Minimarkets Using the Apriori Algorithm Siti Hadija; Eka Irawan; Irfan Sudahri Damanik; Jaya Tata Hardinata
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 4 (2022): December
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (561.502 KB) | DOI: 10.55123/jomlai.v1i4.1668

Abstract

Minimarket is a shop that sells goods for daily needs. Each minimarket generates a lot of sales data every day. Sales transaction data can only be stored without further analysis. Based on this description, research was conducted to assist minimarket managers in making it easy to solve sales pattern problems at minimarkets using the Apriori algorithm. The Apriori algorithm is an algorithm that searches for item set frequencies using the association rule technique. The final result of using data mining using the Apriori association method is proven to be able to find out the results of the analysis that appear simultaneously based on sales data at the Mawar Simp.Tangsi Balimbingan Minimarket with a minimum amount of support of 30% and 80% confidence resulting in 8 association rules that are formed.
Analysis of the Fletcher-Reeves Algorithm in Determining the Best Model for Predicting School Life Expectancy in North Sumatra Jaya Tata Hardinata; Christa Voni Roulina Sinaga; Ferri Ojak Immanuel Pardede; Juli Antasari Sinaga
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 1 (2023): March
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i1.1819

Abstract

Expected Length of School is the length of school (in years) that is expected to be felt by children at a certain age in the future. It is assumed that the probability that the child will remain in school at the following ages is the same as the probability of the population attending school per total population for the current age. Length of School is also a benchmark for evaluating government programs in improving Human Resources who excel in the competition of technological advances. This writing is done to implement and prove that the Fletcher-Reeves Algorithm can be used to predict Old School Expectations in North Sumatra. The research data is School Expectancy in North Sumatra which consists of 10 districts/cities, which was obtained from the Central Statistics Agency of North Sumatra from 2010 to 2020. This study uses 5 architectural models, namely 9-10-1, 9-15-1, 9-20-1, 9-25-1 and 9-30-1. From the five architectural models used, the best architectural model is 9-10-1 with an MSE of 0.0130650400. Based on this best architectural model, it will be used to predict the Expectation of Long Schools in North Sumatra for the next 5 years, from 2021 to 2025.
Determining Product Suitability using Rule-Based Model with C4.5 Algorithm Chintya Carolina Situmorang; Dedy Hartama; Irfan Sudahri Damanik; Jaya Tata Hardinata
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 1 (2023): March
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i1.1923

Abstract

A hotel warehouse must have orderly, good, safe, comfortable, and usable procurement of goods. The common issue that occurs in a warehouse is damaged and unusable goods. The fluctuating production demand for goods sometimes leads to neglecting the quality of the goods in the warehouse. To determine usable goods, appropriate recommendations are needed. The C4.5 algorithm with data mining techniques is an appropriate recommendation for analyzing a large amount of data for classification. The data used in this study is the inventory data of Hotel Sapadia Pematangsiantar's warehouse. Implementing the C4.5 algorithm that produces a Decision Tree can assist the warehouse in determining which goods are still usable for hotel activities. This study resulted in the best variable from the rule model used to determine the feasibility of goods being the physical condition of the goods. The accuracy of the rule model generated from the C4.5 Algorithm modeling is 99.02% against the feasibility of goods.
Memajukan Generasi Muda Melalui Pengabdian Masyarakat Robotika di Lingkungan Siswa SMK Negeri 1 Siantar untuk Tantangan Teknologi Masa Depan Dudes Manalu; Reagan Surbakti Saragih; Peniel Sam Putra Sitorus; Jaya Tata Hardinata
Jurnal TUNAS Vol 4, No 2 (2023): Edisi April
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jtunas.v4i2.96

Abstract

The community service program "Advancing the Young Generation Through Robotics Community Service in the Siantar 1 State Vocational School Students Environment for Future Technological Challenges” aims to prepare future generations to face the complexities of modern technology. The focus of the program is to introduce robotics to SMK students through a community-based approach. Through this program, students will be involved in robotics learning, including programming, design, construction, and robotics applications. Practical training and activities will develop students' creativity, problem-solving and collaboration skills, essential preparation in the world of technology. Collaboration with teachers, parents and local communities is also emphasized, creating a comprehensive educational ecosystem. This program brings together formal and informal approaches to immersive learning experiences. This program has the potential to prepare young people to face a dynamic technological era. The focus on introducing robotics and community engagement is not only about technology, but also inspiring students to reach their full potential in facing the challenges of tomorrow. As such, the program plays an important role in shaping the direction of education towards the continuous development of technology.
Penerapan Metode Algoritma K-means Dalam Pengelompokan Angka Harapan Hidup Saat Lahir Menurut Provinsi Riska Oktavia; Jaya Tata Hardinata; I Irawan
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 1, No 4 (2020): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v1i4.41

Abstract

Life Expectancy (AHH) at birth estimates the average additional age of a person from a mother's womb during the birth process, which is expected to be able to live normally and healthy. Based on data obtained from the Government's official website address at https://bps.go.id/, which displays several amounts that vary from 2015 to 2018 according to the Province in Indonesia. For this reason, it is necessary to cluster each number of life expectancy at birth with the number from the lowest to the highest using the Data Mining method with the K-means Clustering Algorithm. In this research technique, the data will be classified based on the Province's name, which has the number of Life Expectancy at birth from 2015 to 2018. That is why the Data Mining method is used to facilitate data grouping on the number of Life Expectancy at birth according to the name of the Province in Indonesia. After grouping, the results will be obtained the number of Life Expectancy at birth, and grouping starts from the lowest to the highest cluster. In the research that has been carried out, it is expected that the Government will provide solutions of the highest life expectancy at birth that has the highest number so that in the following year, the life expectancy rate will be reduced.
Implementasi Data Mining Clustering Tingkat Kepuasan Konsumen Terhadap Pelayanan Go-Jek Sinta Maria Sinaga; Jaya Tata Hardinata; M. Fauzan
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 2, No 2 (2021): Edisi April
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v2i2.66

Abstract

Increasingly high demands for mobility in today's society, activities are also increasingly crowded, especially parents, employees, and even students so it is increasingly difficult to find free time to meet the needs of daily life. So that people need something that can answer and be a solution to the complaint without having to drain time and energy with results that do not disappoint. Gojek is a solution to the complaints of people who do not have much free time and want to relax while waiting for their needs to be met, Gojek is an online application that can be downloaded via a smartphone, has more than six services provided therein but the author only takes some of the services to be standard the level of community satisfaction with Gojek services. The purpose of this study was to determine the level of community satisfaction with Gojek services. One method contained in Data Mining used in this study is the Clustering method. To find out the level of community satisfaction done with interviews / questionnaires 120 people in the city of Pematangsiantar. The benefits are to make it easier for Gojek companies to know how the quality of services provided to the community is based on the level of community satisfaction and improve the quality of services provided to the community.
Penerapan Algoritma Backpropagation Dalam Memprediksi Jumlah Pengguna Kereta Api Di Pulau Sumatera Vivi Auladina; Jaya Tata Hardinata; M. Fauzan
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 2, No 1 (2021): Edisi Januari
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v2i1.58

Abstract

The purpose of this study is to analyze and test whether the number of train passengers in Indonesia can be predicted by using artificial intelligence techniques. In this study, the artificial intelligence technique used is the Artificial Neural Network Technique (ANN) with the Backpropagation method. Artificial neural network is a method that has been widely used to solve forecasting cases. The main difficulties in implementing neural network methods in forecasting are finding the right architectural combination, determining the appropriate learning rate parameter values and selecting the optimal training algorithm. The research data is secondary data sourced from the bps.go.id website from 2006 - 2019. The data in this study were computerized using the matlab application. From the 5 architectural models used, the best model based on computerized results with the Matlab application is 3-3-1 with an output value of 0.0215923 MSE. The accuracy of the truth obtained is 92%.
Penerapan Algoritma C4.5 Data Mining Dalam Mengukur Tingkat Kepuasaan Masyarakat Kecamatan Siantar Terhadap Perbaikan Jalan 2019 Riama Ester Angelina Sihombing; Jaya Tata Hardinata; Zulaini Masruro Nasution
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 2, No 2 (2021): Edisi April
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v2i2.63

Abstract

Roads are land transportation infrastructures that are used every day by humans both on the surface of the land, below the surface of the land or above the surface of the water. This means that the road is a very important supporting factor in carrying out daily human life, both roads in village and roads in the city. But not all people of Kabupaten Simalungun , especially Kec. Siantar feel that their roads are worth using, but not a few also feel happy that their roads are being repaired. For this reason, the writer would like to know the level of satisfaction of the people of Kabupaten Simalungun, especially Kec. Siantar towards road improvement in their respective areas that has been carried out by the Dinas Pekerjaan Umum Kabupaten Simalungun. The method that I use is the C4.5 algorithm, also called a decision tree, which uses a tree structure representation, the concept of this decision tree is to collect data, then a decision tree is created which will then produce rules for problem solutions, so that this method can know effectively the level of community satisfaction specifically Kabupaten Simalungun.
Co-Authors Abdi Rahim Damanik Adeita A. Ndraha Agus Perdana Windarto Andini, Yulia Andri Nata Arminarahmah, Nur Astri Veranita Sinaga Aulia Ichwanda Ramadhan Azarya N J Siahaan Batubara, Lokot Ridwan Chairani, Yulia Chintya Carolina Situmorang Damanik, Abdi Rahim Debby Febriani R. Saragih Deddy Wahyudin Purba Dedi Handoko Dedi Handoko Dedi Suhendro Dedy Hartama Dedy Hartama Dewi, Rafiqa Dinda Zefanya Simanjuntak Dudes Manalu Efendi, Elfin Eka Desriani Aritonang Eka Irawan Eka Irawan Eka Irawan Ema Deloris Silaban Exaudi Sirait, Debora Fadillah Alwi Pambudi Ferri Ojak Immanuel Pardede Ferri Ojak Immanuel Pardede Gayus Simarmata GS , Achmad Daengs Hartama, Dedy Hendry Qurniawan Hendry Qurniawan Heru Satria Tambunan Heru Satria Tambunan Heru Satria Tambunan Heru Satria Tambunan, Heru Satria I Irawan Ilham Syahputra Saragih Irfan Sudahri Damanik Juli Antasari Br Sinaga Kiki Aidi Saputra M Safii M. Fauzan Marina Rajagukguk Muhammad Arifullah Muhammad Azri Muhammad Fauzan Muhammad Ridwan Lubis Muhammad Ridwan Lubis Muhammad Safii Nur Arminarahmah Ojak Immanuel Pardede, Ferri Okprana, Harly Peniel Sam Putra Sitorus Purba, Yuegilion Pranayama Purnama Nuraini Putri Mai Sarah Tarigan Putri Mai Sarah Tarigan Putriyani Matondang Qurniawan, Hendry Rektor Sianturi, Rektor Riama Ester Angelina Sihombing Rick Hunter Simanungkalit, Rick Hunter Riska Oktavia Safii, M Safruddin, S Saifullah Saifullah Saifullah Saifullah Sam Putra Sitorus, Peniel Samuel Alex Lubis Saragih, Reagan Surbakti Simbolon, Maria Etty Simorangkir, Marhite Sinaga, Christa Voni Roulina Sinta Maria Sinaga Siti Hadija Sitorus, Peniel Sam Putra Situmorang, Eduward Suhada Suhada, Suhada Sundari Retno Andani Surbakti Saragih, Reagan Tarigan, Putri Mai Sarah Vina Merina Br Sianipar Vivi Auladina Voni Roulina Sinaga, Christa Wanto, Anjar Widodo Saputra Winanjaya, Riki Yuegilion Pranavarna Purba Yuegilion Pranayama Purba Yuegilion Pranayama Purba Yulia Andini Yuni Arista Saragih Zulaini Masruro Nasution