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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
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Model Prediksi Jaringan Saraf Tiruan Pada Anggaran Inventaris Di Pemerintahan Kota Pematang Siantar Tatahardinata, Jaya; Okprana, Harly; Winanjaya, Riki
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 8, No 1 (2023): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v8i1.614

Abstract

Inventory is the process of managing the procurement or inventory of goods owned by an office or company in carrying out its operational activities. Without an inventory a business activity will not be carried out, the existence of an inventory is very important. Office inventory is very important for the continuity of an agency. If one or more equipment is disturbed, it will definitely hinder the running of the company's economy which is usually in the form of irregular office inventory organization or lack of a system for inventorying office equipment. Therefore, the Neural Network is a powerful data model that is able to capture and represent complex Input-Output relationships, because of its ability to solve several problems, it is relatively easy to use, robustness of data input speed for execution, and initialization of complex systems. The method used in this research is the Backpropagation algorithm, which is a supervised method, with the help of the MATLAB application with Fletcher-reeves parameters. The research data used is Goods Identity Card data for 2018-2021. Based on this data, a network architecture model will be determined, including 1-10-1, 1-15-1, 1-20-1, and 1-30-1. From the five models, training and testing were carried out first and then obtained the results that the best architectural model was 1-10-1 with 0.01397196. So it can be concluded that the model can be used to predict inventory budget data, especially in Pematangsiantar City.
Kajian Pertanian Indonesia: Estimasi Perkembangan Ekspor Kopi Menggunakan Algoritma Fletcher-Reeves Safruddin, S; Efendi, Elfin; Batubara, Lokot Ridwan; Purba, Deddy Wahyudin; Hardinata, Jaya Tata
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 1 (2024): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i1.760

Abstract

Research on coffee exports to main destination countries is important because it provides an in-depth understanding of the markets that are the main focus. This allows governments and businesses to allocate resources efficiently and design appropriate marketing strategies. In addition, this research provides a strong basis for the government in formulating coffee export policies. By monitoring the development of coffee exports to main destination countries, Indonesia can be better prepared to face changes in global market demand and take appropriate steps in responding to market dynamics. . This research will use the Conjugate Gradient Fletcher-Reeves algorithm, which is one of the algorithms of Artificial Neural Networks. The research was analyzed using 3 architectural models, including: 5-5-1, 5-10-1, and 5-15-1. As a result, the 5-5-1 model was selected as the best model, with the highest accuracy of 94% and the lowest MSE of 0.00500142. Higher than the accuracy of the 5-10-1 model which is only 83% with MSE 0.05058359, and 78% accuracy with MSE 0.01975643 on the 5-15-1 model. Based on the estimation results regarding the development of coffee exports according to main destination countries using the 5-5-1 model, the conclusion that can be drawn is that there will likely be a decline in the level of coffee exports to main destination countries in 2024.
Sistem Informasi Berbasis Web Pembayaran SPP Di SMA RK BT Rantauprapat Manalu, Dudes; Saragih , Reagan Surbakti; Hardinata , Jaya Tata
Jurnal Gemilang Informatika (GIT) Vol. 2 No. 1: Januari 2024
Publisher : Himpunan Dosen Gemilang Indonesia (HDGI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58369/git.v2i1.168

Abstract

Penggunaan teknologi komputer pada saat ini sangat dibutuhkan terutama dalam bidang pengolahan data, baik untuk kepentingan perorangan dan instansi. Sumbangan Pembinaan Pendidikan (SPP) merupakan sumbangan pembinaan pendidikan yang diartikan bahwa sumbangan berupa dana untuk pembinaan pendidikan yang berada dalam suatu lembaga pendidikan. Lembaga pendidikan saat ini sebagian besar dalam melakukan pengolahan data pembayaran SPP, osis, kelengkapan sekolah, masih dengan cara mencatat di buku besar termasuk pada sistem pembayaran SPP pada SMA SWASTA RK BINTANG TIMUR RANTAU PRAPAT. Dari permasalahan diatas maka penulis membuat suatu sistem pengolahan data pembayaran yang bertujuan membangun suatu pengolahan data pembayaran SPP yang mudah digunakan dan dapat diandalkan serta menjamin ketersediaan data. Hasil dari studi ini berupa sistem pembayaran yang dapat diimplementasikan pada SMA RK BINTANG TIMUR RANTAU PRAPAT, atau lembaga pendidikan, yang akhirnya bisa digunakan untuk penyimpanan, pengolahan, dan pelaporan data pembayaran yang terkomputerisasi, dalam memberikan pelayanan dan kinerja pembayaran SPP dapat berjalan dengan baik, serta dapat mempercepat dalam pelayanan informasi data bagi pihak-pihak yang membutuhkan seperti siswa, bagian keuangan dan laporan kepada kepala sekolah.
Sistem Informasi Berbasis Web Pembayaran SPP Di SMA RK BT Rantau Prapat Saragih, Reagan; Manalu, Dudes; Hardinata, Jaya Tata
Jurnal Gemilang Informatika (GIT) Vol. 1 No. 2: Juli 2023
Publisher : Himpunan Dosen Gemilang Indonesia (HDGI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58369/git.v1i2.169

Abstract

The use of computer technology at this time is needed, especially in the field of data processing, both for the benefit of individuals and agencies. tuition fee is a contribution to education development which means that donations are in the form of funds for educational development within an educational institution. Currently, most of the educational institutions in processing the payment data for tuition fee, student council, school equipment, are still by recording in the ledger including the tuition fee payment system at SMA RK Bintang Timur Rantau Prapat. From the problems above, the authors create a payment data processing system that aims to build a payment data processing system that is easy to use and reliable and ensures data availability. The results of this study are in the form of a payment system that can be implemented at SMA RK Bintang Timur Rantau Prapat, or educational institutions, which can eventually be used for storage, processing, and reporting of computerized payment data, in providing services and the performance of school fee payments can run well, and can speed up the service of data information for parties in need such as students, the finance department and reports to the principal. Kata kunci: tuition fee payment system, PHP, Mysql, Javascript, CSS
Analisis Laju Pembelajaran dalam Mengklasifikasi Data Wine Menggunakan Algoritma Backpropagation Hardinata, Jaya Tata; Okprana, Harly; Windarto, Agus Perdana; Saputra, Widodo
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 3, No 2 (2019): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (810.284 KB) | DOI: 10.30645/j-sakti.v3i2.161

Abstract

Backpropagation is an artificial neural network that has the architecture in conducting training and determining the right parameters to produce the correct output of similar but not the same input. One of the parameters that influences the determination of bacpropagation architecture is the rate of learning, where if the value of the learning rate is too high then the network architecture becomes unstable otherwise if the value of the learning rate is too low the network architecture converges and takes a long time in training network architecture. This research data is secondary data sourced from UCI Data Mechine Learning. The best network architecture in this study is 13-10-3, with different learning rates ranging from 0.01, 0.03, 0.06, 0.01, 0.13, 0.16, 0.2, 0.23, 0.026, 0.3, 0.35, 0.4, 0.45, 0.5, 0.55, 0.6, 0.65, 0.7, 0.75, 0.8, 0.9. From the 21 different learning rate values in the 13-10-3 network architecture, it is found that the level of learning rate is very important to get the right and fast network architecture. This can be seen in experiments with a learning rate of 0.65 can produce a better level of accuracy compared to a learning rate smaller than 0.65.
PELATIHAN OLIMPIADE SAINS NASIONAL (OSN) BIDANG MATEMATIKA Sianturi, Rektor; Rick Hunter Simanungkalit; Juli Antasari Br Sinaga; Samuel Alex Lubis; Sam Putra Sitorus, Peniel; Voni Roulina Sinaga, Christa; Surbakti Saragih, Reagan; Manalu, Dudes; Tata Hardinata, Jaya; Ojak Immanuel Pardede, Ferri; Exaudi Sirait, Debora
Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Vol. 1 No. 6 (2023): Desember
Publisher : CV. Alina

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59407/jpki2.v1i6.179

Abstract

Olimpiade Sains Nasional merupakan ajang lomba yang difasilitasi oleh tingkat kabupaten/kota, tingkat provinsi maupun nasional. Oleh karena itu setiap sekolah perlu membekali siswa-siswi nya dalam ajang tersebut. Dalam hal membekali siswa-siswi mengikuti lomba tersebut maka perlu persiapan yang matang yaitu dengan melakukan pelatihan Olimpiade Sains nasional (OSN) khusus nya bidang matematika. Setelah melakukan pelatihan olimpiade sains nasional, ternyata masih banyak siswa yang masih belum mengerti apa itu olimpiade sains nasional khususnya bidang matematika dan belum pernah mempelajari sama sekali soal-soal OSN bidang matematika. Akibat dari permasalahan tersebut maka perlu diadakan pelatihan-pelatihan Olimpiade Sains Nasional khusus nya Bidang matematika, setiap guru yang mengajar di kelas tersebut agar memberikan soal tambahan yaitu soal-soal Olimpiade Sains Nasional bidang matematika yang mana tingkatan nya mulai dari tingkat kabupaten/kota, tingkat provinsi dan tingkat nasional dan bahkan tingkat internasional serta setiap guru harus memberikan kunci jawaban nya. Kata Kunci: Olimpiade Sains Nasional, Bidang Matematika.
Analisis Laju Pembelajaran dalam Mengklasifikasi Data Wine Menggunakan Algoritma Backpropagation Hardinata, Jaya Tata; Okprana, Harly; Windarto, Agus Perdana; Saputra, Widodo
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 3, No 2 (2019): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v3i2.161

Abstract

Backpropagation is an artificial neural network that has the architecture in conducting training and determining the right parameters to produce the correct output of similar but not the same input. One of the parameters that influences the determination of bacpropagation architecture is the rate of learning, where if the value of the learning rate is too high then the network architecture becomes unstable otherwise if the value of the learning rate is too low the network architecture converges and takes a long time in training network architecture. This research data is secondary data sourced from UCI Data Mechine Learning. The best network architecture in this study is 13-10-3, with different learning rates ranging from 0.01, 0.03, 0.06, 0.01, 0.13, 0.16, 0.2, 0.23, 0.026, 0.3, 0.35, 0.4, 0.45, 0.5, 0.55, 0.6, 0.65, 0.7, 0.75, 0.8, 0.9. From the 21 different learning rate values in the 13-10-3 network architecture, it is found that the level of learning rate is very important to get the right and fast network architecture. This can be seen in experiments with a learning rate of 0.65 can produce a better level of accuracy compared to a learning rate smaller than 0.65.
Penerapan Data Mining pada Tata Letak Buku Di Perpustakaan Sintong Bingei Pematangsiantar dengan Metode Apriori Andini, Yulia; Hardinata, Jaya Tata; Purba, Yuegilion Pranayama
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 7, No 1 (2022): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v7i1.410

Abstract

The library is a place that has a large collection of knowledge books, magazines and other media that are arranged or arranged in a certain way so that it is easy for users to use properly and well. In placing books in the library, books are placed according to the book category given the numbering. However, the placement of books has not been regulated by looking at the level of books that are often borrowed and many visitors find it difficult to find books that are often borrowed. So it is necessary to create a system using a priori data mining method to determine the pattern of book layout arrangement in the library, this system can help to make it easier to determine the layout of the book as needed. Based on the results of the implementation of RapidMiner, the highest combination pattern of library book layout is Pure Science and Social Sciences with 50% support and 86% confidence. General Works and Pure Science were obtained with 41% support and 83% confidence. Furthermore, Public Works and Social Sciences with 41% support and 83% confidence.
Analisis Penjualan Produk Paket Kuota Internet Dengan Metode K-Nearest Neighbor Handoko, Dedi; Tambunan, Heru Satria; Hardinata, Jaya Tata
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 6, No 1 (2021): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v6i1.275

Abstract

PT. Akses Lintas Nusantara is a company engaged in the sale of Internet Quota Packages and package balances. This company has various data packages ranging from 6 GB, 11 GB, 21 GB and 32 GB with various price variations. Based on data on sales of internet quota package products for the past 1 (one) year, predictions for future sales are needed in order to facilitate the company in planning the provision of internet quota package stock. The K-Nearest Neighbor (KNN) algorithm is a method that is a supervised algorithm where the results of the new test sample are classified based on the majority of the categories on the KNN. To find out the sales of these products, the K-Nearest Neighbor algorithm is used. The expected result is to make it easier for companies to predict the future supply of internet quota packages in each region or region. The results of the research that have been carried out are prediction of Internet Quota Package Sales consisting of SP CL1, SPCL2, SPCL4 and SP CL8 with an Accuracy of 71.43%.
Klusterisasi Impor Beras Di Indonesia Menurut Negara Asal Utama Menggunakan Algoritma K-Medoids Arminarahmah, Nur; GS, Achmad Daengs; Hardinata, Jaya Tata
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 8, No 2 (2023): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v8i2.657

Abstract

This study aims to classify rice import data in Indonesia based on the main country of origin using the K-Medoids algorithm. The rice import data used in this study covers the last six years (2017-2022), which is quantitative data, namely rice import data in Indonesia quoted from the Indonesian Statistical Publication, and processed based on the customs archives of the Directorate General of Customs and Excise. The K-Medoids method was chosen because of its ability to handle outliers and provide more stable clustering results compared to other clustering algorithms. The results of the analysis show that there are three main clusters of rice-supplying countries in Indonesia. The first cluster consists of countries with high import volumes, the second includes countries with moderate import volumes, and the third comprises countries with low import volumes. These findings provide important insights for the government and industry players in formulating rice import strategies, particularly in choosing the country of origin of imports and determining tariff policies. In addition, the results of this clustering can be used as a basis for making decisions regarding the diversification of rice import sources to increase national food security.
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