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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

Author-ID : 1199431

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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Implementation of Resilient Methods to Predict Open Unemployment in Indonesia According to Higher Education Completed Saputra, Widodo; Hardinata, Jaya Tata; Wanto, Anjar
JITE (JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING) Vol 3, No 1 (2019): EDISI JULI
Publisher : Universitas Medan Area

Unemployment is a big problem faced by the Indonesian people from year to year besides poverty. Therefore it is necessary to predict the level of open unemployment in Indonesia so that later the government and private parties have the right references and references to work together to overcome this problem. The prediction method used is Resilient Backpropagation which is one method of Artificial Neural Networks which is often used for data prediction. The research data used is open unemployment data according to the highest education completed in 2005-2018 based on the semester obtained from the website of the Indonesian Central Bureau of Statistics. Based on this data a network architecture model will be formed and determined, including 12-6-2, 12-12-2, 12-18-2, 12-24-2, 12-12-12-2, 12-12-18 -2, 12-18-18-2 and 12-18-24-2. From these 8 models after training and testing, the results show that the best architectural model is 12-18-2 (12 is the input layer, 18 is the number of hidden neurons and 2 is the output layer). The accuracy of the architectural model for semester 1 and semester 2 is 75% with an MSE value of 0.0022135087 and 0.0044974696

SPK DALAM MEREKOMENDASIKAN PESTISIDA TERBAIK UNTUK MEMBUNUH HAMA PADA TANANAMAN PADI MENGGUNAKAN METODE MAUT Simbolon, Maria Etty; Saifullah, Saifullah; Hardinata, Jaya Tata
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 3, No 1 (2019): Smart Device, Mobile Computing, and Big Data Analysis
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v3i1.1676

Pesticides are chemicals and organic which are used by farmers to protect rice plants from pests, farmers often experience difficulties in choosing the pesticides to be used. Where pesticide products circulate very much in the market and offer various advantages of each product, but often farmers experience incompatibility with what has been offered by each product Where pesticide products circulate very much in the market and offer various advantages of each product, but often farmers experience incompatibility with what has been offered by each product. The incompatibility of pesticides used by farmers can affect the yields of farmers. The purpose of this study is as knowledge of farmers in determining the best pesticides to eradicate pests in rice plants, especially in the village of Bah Sampuran and apply the MAUT method (Multi Attribute Utility Theory) to calculate each criterion of alternatives and produce cracking in recommending the best pesticides to eradicate pests in plants rice. The criteria used are: the workings of the pesticides, the price of pesticides, many pests, shelf life, the effect on humans, the influence on rice plants, the influence on other animals, climate resistance. This application was built using Vb net programming language and MySql database. From the results of this study it was found that Alternative Plenum had the highest value with a value of 0.79 so that it became the best Pesticide recommendation.Keywords: Decision Support System, Pesticides, FOREIGN, Vb net, MySql

Analisis Kualitas Pelayanan Terhadap Kepuasan Konsumen Berbelanja Baju Polos dan Sablon Digital di Toko Cititex Cabang Kota Pematangsiantar Chairani, Yulia; Suhada, Suhada; Hardinata, Jaya Tata
TIN: Terapan Informatika Nusantara Vol 2 No 10 (2022): Maret 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v2i10.1373

The satisfaction of consumers shopping for plain clothes at the Cititex store in the Pematangsiantar branch is one of the most important things in assessing the level of service and quality provided by the store to its consumers. The purpose of this study was to determine the quality of service to consumers in terms of Quality (Quality), Responsiveness (Responsiveness), Empathy (Empathy) to consumers. At the Cititex plain clothes shop, the Pematangsian branch, these three aspects have not been measured with certainty, so the shop finds it difficult to determine which aspects should be improved. The method used in this study is the C4.5 Algorithm, where the data source used is a questionnaire technique given to consumers. The research test process uses RapidMiner software to create a decision tree. The results obtained 2 rules for the classification of the level of consumer satisfaction with the quality of materials and store service. The C4.5 algorithm can be used in the case of consumer satisfaction at the Cititex plain clothes shop, Pematangsiantar branch with an accuracy rate of 96.50%. From the results of the analysis is expected to improve the quality of materials and services in providing services to consumers to be even better

Implementation of Resilient Methods to Predict Open Unemployment in Indonesia According to Higher Education Completed Widodo Saputra; Jaya Tata Hardinata; Anjar Wanto
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 3, No 1 (2019): EDISI JULI
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v3i1.2704

Model Jaringan Saraf Tiruan untuk Estimasi Penduduk Miskin di Indonesia Sebagai Upaya Pengentasan Kemiskinan Anjar Wanto; Jaya Tata Hardinata
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2019: Peran Sains Data Dari Perspektif Akademisi dan Praktisi
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Penelitian ini bertujuan menentukan model arsitektur jaringan terbaik yang tepat untuk melakukan estimasi Penduduk Miskin di Indonesia menggunakan salah satu algoritma jaringan saraf tiruan, yakni dengan metode Bayesian Regulation. Metode ini melakukan fungsi pelatihan jaringan dengan cara memperbarui bobot dan nilai bias menurut pengoptimalan LevenbergMarquardt. Data yang digunakan pada penelitian ini adalah data penduduk miskin tiap provinsi di Indonesia tahun 2012 sampai tahun 2018 berdasarkan semester, yang bersumber dari Badan Pusat Statistik Indonesia (BPS). Berdasarkan data ini akan dibentuk dan ditentukan model arsitektur jaringan yang digunakan dengan metode Bayesian Regulation, antara lain 10-5-10-2, 10-10-15-2, 10-15-10-2, 10-15-20-2, dan 10-25-25-2. Dari 5 model ini setelah dilakukan pelatihan dan pengujian diperoleh hasil bahwa model arsitektur terbaik adalah 10-25-25-2 (10 adalah input layer, 25 adalah jumlah neuron hiden layer pertama dan 25 selanjutnya juga merupakan jumlah neuron hiden layer kedua, 2 adalah output layer). Tingkat akurasi dari model arsitektur ini adalah 94,1% dan 61,8% dengan nilai MSE sebesar 0,00013571 dan 0,00005189. Dari penentuan model terbaik ini selanjutnya akan dapat digunakan untuk mengestimasi penduduk miskin di Indonesia sebagai upaya dini pemerintah dalam pengentasan kemiskinan.

Penerapan Metode Resilient dalam Menentukan Model Arsitektur Terbaik untuk Prediksi Pengangguran Terbuka di Indonesia Widodo Saputra; Jaya Tata Hardinata; Anjar Wanto
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2019: Peran Sains Data Dari Perspektif Akademisi dan Praktisi
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Metode Resilient merupakan salah satu metode Jaringan Saraf Tiruan yang sering digunakan untuk melakukan sebuah prediksi, terutama pada data times series (berkelanjutan). Metode ini mampu melakukan prediksi dengan belajar dari data-data yang sudah pernah terjadi sebelumnya dengan terlebih dahulu membentuk model arsitektur jaringan yang tepat. Oleh karena itu, penelitian ini akan membahas tentang model arsitektur jaringan terbaik yang tepat untuk melakukan prediksimenggunakan metode Resilient. Metode ini pengembangan dari metode Backpropagation. Data yang digunakan pada penelitian ini adalah data pengangguran terbuka menurut pendidikan tertinggi yang ditamatkan di Indonesia tahun 2005-2018 berdasarkan semester, yang bersumber dari Survei Angkatan Kerja Nasional (Sakernas) yang diperoleh dari website Badan Pusat Statistik Indonesia. Berdasarkan data ini akan dibentuk dan ditentukan model arsitektur jaringan yang digunakan dengan metode Resilient, antara lain 12-6-2, 12-12-2, 12-18-2, 12-24-2, 12-12-12-2, 12-12-18-2, 12-18-18-2 dan 12-18-24-2. Dari 8 model ini setelah dilakukan pelatihan dan pengujian diperoleh hasil bahwa model arsitektur terbaik adalah 12-18-2 (12 adalah input layer, 18 adalah jumlah neuron hiden layer dan 2 adalah output layer). Tingkat akurasi dari model arsitektur untuk semester 1 dan semester 2 ini adalah 75% dengan nilai MSE sebesar 0,00052083 dan 0,00105823.

ESTIMASI PENDUDUK MISKIN DI INDONESIA SEBAGAI UPAYA PENGENTASAN KEMISKINAN DALAM MENGHADAPI REVOLUSI INDUSTRI 4.0 Anjar Wanto; Jaya Tata Hardinata
CESS (Journal of Computer Engineering, System and Science) Vol 4, No 2 (2019): JULI 2019
Publisher : Universitas Negeri Medan

Kemiskinan merupakan masalah serius yang dihadapi Indonesia. Oleh karena itu, penulis mencoba membantu pemerintah dengan melakukan analisa untuk melihat tingkat perkembangan penduduk miskin di Indonesia untuk tahun yang akan datangi. Metode yang digunakan untuk melakukan hal ini adalah jaringan saraf tiruan Bayesian Regulation. Metode ini merupakan pengembangan dari metode backpropagation yang sering digunakan untuk mengestimasi data. Data yang digunakan adalah data penduduk miskin di Indonesia tahun 2012-2018, yang bersumber dari Badan Pusat Statistik Indonesia. Berdasarkan data ini akan dibentuk dan ditentukan model arsitektur jaringan yang digunakan dengan metode Bayesian Regulation, antara lain 10-5-10-2, 10-10-10-2, 10-10-15-2, 10-10-20-2, 10-15-10-2, 10-15-15-2, 10-15-20-2, 10-20-20-2, 10-25-25-2 dan 10-30-30-2. Dari 10 model ini setelah dilakukan pelatihan dan pengujian diperoleh hasil bahwa model arsitektur terbaik adalah 10-25-25-2. Tingkat akurasi dari model arsitektur ini adalah 94,1% dan 61,8% dengan nilai MSE sebesar 0,00013571 dan 0,00005189. Hasil penelitian ini berupa estimasi penduduk miskin untuk 5 tahun yang akan datang

IMPLEMENTASI ASSOCIATION RULE MINING UNTUK MENENTUKAN POLA KOMBINASI MAKANAN DENGAN ALGORITMA APRIORI Marina Rajagukguk; Rafiqa Dewi; Eka Irawan; Jaya Tata Hardinata; Irfan Sudahri Damanik
JURNAL FASILKOM (teknologi inFormASi dan ILmu KOMputer) Vol 10 No 3 (2020): Jurnal Fasilkom
Publisher : Fakultas Ilmu Komputer, Unversitas Muhammadiyah Riau

OH5 Hash Cafe is a business that is engaged in the food sector and there is a lot of competition in doing business that is increasingly difficult to do so it is necessary to develop a strategy, this study aims to determine the pattern of food combinations, the method used in this research is the Apriori Algorithm to be able to find out and processed using the Rapid Miner 9.7 software in determining food combination patterns, the Apriori Algorithm is an interesting type of association rule in data mining and an interesting association analysis to produce an efficient algorithm that is high frequency pattern analysis, an association can be identified with two benchmarks, namely: Support and Cofindence. Support is the percentage of item combinations in the database, while Confidence is the strong relationship between items in the association rule.

Analisa Jaringan Saraf Tiruan Backpropagation Untuk Memprediksi Prestasi Siswa SMA Muhammadiyah Serbelawan Aulia Ichwanda Ramadhan; Jaya Tata Hardinata; Yuegilion Pranavarna Purba
Brahmana : Jurnal Penerapan Kecerdasan Buatan Vol 3, No 1 (2021): Edisi Desember
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/brahmana.v3i1.88

Achievements achieved by graduates from an educational institution show the quality and quality. One of them is seen from one of the assessment criteria for assessing the achievement of graduates at the secondary school level, namely through the average score. This average value is often used as a measure to assess students who will enter the next level of education. In addition, the acceptance of students at a level of education is also adjusted to the capacity of the school in question. The high average score at the high school level does not guarantee student achievement at the tertiary level. So that this study aims to obtain an output architecture prediction of student achievement at SMA Muhammadiyah Serbelawan which correlates between the average value and the total score of class XII (twelve) high school students according to the data trained using Artificial Neural Network Analysis using the Backpropagation method. The data taken in the form of the average value of students and the total value of the second semester of class XII students. Furthermore, the data were analyzed using Backpropagation ANN method, with the help of MATLAB software. From the results of testing the Student Achievement data above, we can see in the 5-5-5-1 architecture which shows from the target minus the ANN output that SSE is 0.17625 which shows that there is a measuring tool in predicting the best students using academic value data as a target. From the data obtained, the computational performance of artificial neural networks with the Backpropagation Algorithm is 85%.

Sistem Pendukung Keputusan Pemilihan Sekolah SMA Swasta Terbaik Dengan Menggunakan Metode PROMETHEE Di Kota Pematangsiantar Yuni Arista Saragih; Jaya Tata Hardinata; Muhammad Ridwan Lubis
Brahmana : Jurnal Penerapan Kecerdasan Buatan Vol 1, No 1 (2019): Edisi Desember
Publisher : LPPM STIKOM Tunas Bangsa

Selection of the best private schools in embassy cities with the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) method. This decision support system is built through 6 stages. The first stage is collecting data and information through interviews and document analysis. The second stage is processing data and information to get the system design to be built. The third stage is system analysis which includes school data input, weighting criteria with the PROMETHEE method, and alternative ranking with the PROMETHEE method. The Fourth stage is designing the system using the concept of Object Oriented Design. The fifih stage is the implementation of a web-based system. The last step is evaluating the system by comparing the level of accuracy between the PROMETHEE method. With the implementation of the PROMETHEE method for the selection of the best private schools that will result in the ranking of the best private schools, it is expected that in the selection of the best schools that are truly recommended in accordance with the wishes and abilities of students

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

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