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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) JURNAL SISTEM INFORMASI BISNIS Jurnal Pendidikan Teknologi dan Kejuruan Techno.Com: Jurnal Teknologi Informasi Jurnas Nasional Teknologi dan Sistem Informasi CESS (Journal of Computer Engineering, System and Science) Register: Jurnal Ilmiah Teknologi Sistem Informasi KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Jurnal Informatika Upgris E-Dimas: Jurnal Pengabdian kepada Masyarakat JOIN (Jurnal Online Informatika) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) SemanTIK : Teknik Informasi JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JIKO (Jurnal Informatika dan Komputer) AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat JURNAL MEDIA INFORMATIKA BUDIDARMA JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL ILMIAH INFORMATIKA SINTECH (Science and Information Technology) Journal Jurnal Infomedia MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA J-SAKTI (Jurnal Sains Komputer dan Informatika) IJISTECH (International Journal Of Information System & Technology) KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) JURTEKSI Building of Informatics, Technology and Science Journal of Computer System and Informatics (JoSYC) TIN: TERAPAN INFORMATIKA NUSANTARA Brahmana : Jurnal Penerapan Kecerdasan Buatan Jurnal Tunas Journal of Computer Networks, Architecture and High Performance Computing Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Revolusi Indonesia JiTEKH (Jurnal Ilmiah Teknologi Harapan) IJISTECH Journal of Applied Data Sciences RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI JPM: JURNAL PENGABDIAN MASYARAKAT DEVICE Bulletin of Computer Science Research 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 Penelitian Inovatif BEES: Bulletin of Electrical and Electronics Engineering JOMLAI: Journal of Machine Learning and Artificial Intelligence Jurnal Krisnadana STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Jurnal Krisnadana Journal of Informatics, Electrical and Electronics Engineering
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Penerapan Algoritma Backpropagation Dalam Memprediksi Produksi Tanaman Padi Sawah Menurut Kabupaten/Kota di Sumatera Utara Meychael Adi Putra Hutabarat; Muhammad Julham; Anjar Wanto
semanTIK Vol 4, No 1 (2018): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (382.027 KB) | DOI: 10.55679/semantik.v4i1.4225

Abstract

North Sumatra Province is a province well known for its rice field production. But from all regencies and cities in North Sumatra, its rice production is uneven and unstable, sometimes its production goes up, sometimes down. Therefore, it is needed a research in the form of prediction for Production of Rice Field Crops, so that local government of North Sumatra can make policy as early as possible, so that production of paddy rice field can continue to rise in order to support the achievement of food self-sufficiency. In this study data that will be predicted sourced from the Central Bureau of Statistics of North Sumatra Province from 2012 until 2016. The algorithm used to make this prediction is the Backpropagation algorithm. This algorithm has the ability to remember and make generalizations of what has been there before. There are 5 architectural models used in this research, among others 3-5-1 which later will produce predictions with 78% accuracy rate, 3-7-1 = 70%, 3-10-1 = 82%, 3-15 -1 = 82% and 3-9-1 = 91%. The best architecture of the 5 models is 3-9-1 with 91% accuracy and error rate of 0.001-0.05. It is expected that the results of this study can contribute to the government in determining agricultural policy in the future.Keywords—Application, Backpropagation, Prediction, Production, RiceDOI : 10.5281/zenodo.1402832
Analisis Jaringan Saraf Tiruan Untuk Prediksi Luas Panen Biofarmaka di Indonesia Eko Hartato; Daniel Sitorus; Anjar Wanto
semanTIK Vol 4, No 1 (2018): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (251.812 KB) | DOI: 10.55679/semantik.v4i1.4201

Abstract

Analysis of a prediction is very important to do in a study, so that research becomes more precise and directed. Just as in predicting the extent of biopharmaceutical harvests in Indonesia, it is necessary to study and use appropriate methods to obtain optimal results. This research is expected to be widely used for both local government and biopharmaca farmers as one of the study materials in the development of biopharmaca harvest production, as well as for academics as research material especially related to agriculture and health. The data used in this research is the data of Harvested Area of Biopharmaceutical in Indonesia from National Bureau of Statistics from 2012 until 2016. This research uses the method of artificial neural network Backpropagation using 5 architectural models, namely: 3-3-1 later it will generate predictions with an accuracy rate of 80%, 3-4-1 = 87%, 3-5-1 = 73%, 3-6-1 = 60%, and 3-8-1 = 73% ,. So obtained the best architectural model using 3-4-1 model that yields an accuracy of 87%, MSE 0.062235528 with error rate used 0.001 to 0.05. Thus, this model is good enough to predict the area of biopharmaca harvest in IndonesiaKeywords—Analysis, Prediction, ANN, Backpropagation, BiopharmacaDOI : 10.5281/zenodo.1402402
Estimasi Wisatawan Mancanegara Yang Datang Ke Sumatera Utara Menggunakan Jaringan Saraf Ruri Eka Pranata; Samuel Palentino Sinaga; Anjar Wanto
semanTIK Vol 4, No 1 (2018): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (161.142 KB) | DOI: 10.55679/semantik.v4i1.4244

Abstract

North Sumatra is one of the areas in Indonesia which has various tourist attractions with its natural beauty. The potential of North Sumatra makes the attraction of foreign tourists want to visit the existing tourist attractions in the area. Every year foreign tourists who come to North Sumatra, especially tourists who come from the ASEAN region the number is changing. Therefore an estimate is needed to determine the number of tourists who come and later this estimate is useful for the government to anticipate the surge of tourists who come. The data to be estimated is the data of the number of tourists who come to North Sumatra according to national origin sourced from Central Bureau of Statistics of North Sumatra (BPS Sumut) in 2011-2015. The algorithm used to make estimates is the artificial neural network Backpropagation. There are five architectural models used in this estimate that is, 3-7-1 has 100% accuracy rate, 3-10-1 = 62.5%, 3-11-1 = 75%, 3-12-1 = 88% , and 3-15-1 = 87.5%. The best architecture of the five models is 3-7-1 with 100% accuracy rate and MSE of 0,006513Keywords—Estimates, Foreign Tourists, North Sumatra, Neural NetworksDOI : 10.5281/zenodo.1402836
Penerapan Algoritma Decision Tree C4.5 untuk Klasifikasi Tingkat Kesejahteraan Keluarga pada Desa Tiga Dolok Susi Fitryah Damanik; Anjar Wanto; Indra Gunawan
Jurnal Krisnadana Vol 1 No 2 (2022): Jurnal Krisnadana - Januari 2022
Publisher : Yayasan Sinergi Widya Nusantara (Sidyanusa)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1051.957 KB) | DOI: 10.58982/krisnadana.v1i2.108

Abstract

Klasifikasi tingkat kesejahteraan keluarga di Desa Tiga Dolok merupakan permasalahan yang dialami Masyarakat di desa itu. Dimana klasifikasi Tingkat kesejahteraan keluarga di Desa tersebut belum sepenuhnya akurat sehinga mengakibatkan penyaluran subsidi pemerintah tidak tepat sasaran. Permasalahan klasifikasi tingkat kesejahteraan menjadi tujuan dilakukannya penelitian agar mendapatkan hasil yang akurat dalam status tingkat kesejahteraan keluarga. Untuk mengatasi masalah tersebut diusulkan model baru dengan memanfaatkan sebuah metode komputasi C4.5 agar menghasilkan klasifikasi tingkat kesejahteraan yang akurat. Pada penelitian ini algoritma yang digunakan untuk melakukan klasifikasi tingkat kesejahteraan pada Desa Tiga Dolok adalah algoritma C4.5. Algoritma ini dipilih karena proses klasifikasinya sederhana dan cepat. Data penelitian yang digunakan nantinya adalah Data Isian Dasar Keluarga Desa Tiga Dolok Tahun 2019. Sumber data diperoleh berdasarkan kuisioner yang dibagikan kepada masyarakat Tiga Dolok. Berdasarkan data ini akan dilakukan klasifikasi tingkat kesejahteraan dengan menggunakan aplikasi rapid miner. Dengan metode ini akan dibentuk pohon keputusan agar nantinya mendapatkan hasil klasifikasi yang diinginkan.
PkM: Pelatihan Peningkatan Skill Siswa Sekolah Kejuruan pada Pembuatan Game Sederhana berbasis Android Agus Perdana Windarto; M Mesran; Anjar Wanto
Jurnal TUNAS Vol 3, No 2 (2022): Edisi April
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jtunas.v3i2.63

Abstract

In accordance with the title of this community service program (P2M), the method of applying science and technology is in the form of android training in making simple games. Skills training activities are supported by lectures, questions and answers, and of course hands-on practice in the computer laboratory. The training module will be given to participants as a tool for practical activities in the laboratory. The purpose of implementing this community service program is to improve the skills of Pematangsiantar Exemplary Private Vocational School Students, by making simple android-based games for Pematangsiantar Exemplary Private Vocational High School Students, so as to minimize the gap between the skill levels of the Pematangsiantar Exemplary Private Vocational High School students. with the needs of the real world of work. From the evaluation results and the findings obtained during the implementation of this P2M activity, it can be concluded that this P2M program has been able to provide enormous and targeted benefits for Pematangsiantar Exemplary Private Vocational High School Students in this activity. This form of training is a very effective form of providing refreshment and additional insight and new knowledge in the field of information technology outside of the learning process received in their respective schools.
PkM Kelompok SMK dalam Pemanfaatan Digital Art untuk Membentuk Manajemen Kewirausahaan di Simalungun Anjar Wanto; Harly Okprana; Rizki Alfadillah Nasution
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.v4i1.70

Abstract

This PkM activity aims to improve skills and creativity and form partner entrepreneurship management (Students of SMK Swasta Anak Bangsa Simalungun Regency) so that later partners can make their products according to their respective wishes by utilizing digital art by marketing it using a marketplace. The PkM team provides training and assistance on entrepreneurship management to Partners in the hope that Partners can open their jobs without relying on and waiting for employment opportunities. This service is carried out at the Children of the Nation Private Vocational School in Simalungun Regency. The activity was carried out for two days, Monday and Tuesday, July 18 and 19, 2022, starting at 09.00-17.00 WIB, with 60 students as participants. This activity uses presentation/lecture methods, discussions, questions and answers, and practice/practice on making products such as digital keychain pins, digital screen printing t-shirts, digital wood screen printing and digital mug glass printing. The results of this service activity, based on the results of the Pre-test, showed that of the 60 students participating in PkM at this school, 34 students were able to answer questions >10 (57%) and <= ten as many as 26 students (43%) with an average score of 51. Meanwhile, based on the Post Test, students who were able to answer questions >10 were 57 students (95%) or an increase of 38% compared to before the PkM activity was carried out, and <= as many as three students (5%) with an average score of 71. So it can be concluded that students' knowledge about digital art increased after this PkM activity was carried out.
Rancang Bangun Alat Pengusir Hama Burung Berbasis Arduino Uno Syafri Maradu Manurung; Anjar Wanto; Indra Gunawan
JITEKH Vol 10 No 2 (2022): September 2022
Publisher : Universitas Harapan Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35447/jitekh.v10i2.581

Abstract

Bird pests are one of the problems that always haunt farmers, these pests often make it difficult for farmers, plus during the rice harvest period, bird pests will increase, thereby reducing the production yields that will be produced. The purpose of this study is to make an Arduino Uno-based bird repellent using an ultrasonic sensor, which is to read if a bird approaches it will automatically activate the sound that has been installed on a bird repellent that resembles a scarecrow. In addition, this tool can also move automatically if there are pests that come, the result of this study is the application of Bird Pest Repellents that can be implemented in rice fields.
Akurasi Algoritma Fletcher-Reeves untuk Prediksi Ekspor Karet Remah Berdasarkan Negara Tujuan Utama Rapianto Sinaga; Mora Malemta Sitomorang; Deri Setiawan; Anjar Wanto; Agus Perdana Windarto
Journal of Informatics Management and Information Technology Vol. 2 No. 3 (2022): July 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v2i3.170

Abstract

Crumb rubber is a natural rubber specially designed to ensure its technical quality. Rubber is produced mainly in Southeast Asia, where Indonesia is the second largest producer in the world after Thailand. This study aims to predict the export of powdered rubber in Indonesia. The prediction method used is FletcherReeves which is one of the artificial neural network methods commonly used to predict data. The research data used is crumb rubber export data by main destination country for the period 2012-2020 which was obtained from the website of the Indonesian Central Statistics Agency. Based on this data, network architecture models will be trained and defined, including 7-10-1, 7-15-1, 7-20-1, 7-25-1, 7-30-1 (trancgf). Of the five models, after training and testing, the best data architecture model is 7-15-1 (trancegf) 7 is the input layer, 15 is the number of neurons in the hidden layer and 1 is the exit layer. The level of accuracy of the architectural model with the MSE value is 0.00482054.
Implementasi Algoritma Resilient untuk Prediksi Potensi Produksi Bawang Merah di Indonesia Nurhayati Nurhayati; Mhd. Buhari Sibuea; Dedi Kusbiantoro; Martina Silaban; Anjar Wanto
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2269

Abstract

Shallots are seasonal horticultural crops with high economic value. They are one of the horticultural commodities prioritized by the Director General of Horticulture and the Ministry of Agriculture in their development and handling. Therefore, it is necessary to predict the potential of shallot production in Indonesia so that the government has benchmarks and information in determining the right economic policy so that shallot production can continue to be increased or at least be unstable every year. In this study, the prediction algorithm used is the Resilient algorithm. The research data used are shallot production data obtained from the Indonesian Central Statistics Agency. This research will be analyzed using four network architecture models: 6-5-1, 6-10-1, 6-17-1 and 6-29-1. Based on the analysis of the four models used, the results show that the 6-17-1 model is the best because it has a lower Mean Square Error (MSE) value than the other three models, which is 0.0337792, and the accuracy level is quite good. Of 79% with an error rate of 0.04 used. This architectural model will be used to predict the potential for shallot production in Indonesia. Based on the overall prediction results from each province, the potential for Indonesian shallot production at the end of 2022 tends to decrease compared to 2021. The conclusion can be drawn that the application of the Resilient algorithm to the problem of red onion production data in Indonesia is quite good, but the accuracy is not too high, so a more profound study is needed
Optimization of Performance Traditional Back-propagation with Cyclical Rule for Forecasting Model Anjar Wanto; Ni Luh Wiwik Sri Rahayu Ginantra; Surya Hendraputra; Ika Okta Kirana; Abdi Rahim Damanik
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 22 No 1 (2022)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i1.1826

Abstract

The traditional Back-propagation algorithm has several weaknesses, including long training times and significant iterations to achieve convergence. This study aims to optimize traditional Back-propagation using the cyclical rule method to cover these weaknesses. Optimization is done by changing the training function and standard Back-propagation parameters using the training function and cyclical rule parameters. After that, a comparison of the two results will be carried out. This study uses quantitative method of time-series data on coronavirus cases sourced from the Worldometer website, then analyzed using three forecasting models with five input layers, one hidden layer (5, 10, and 15 neurons) and one output layer. The results showed that the 5-10-1 model with the training function and cyclical rule parameters and the tansig and purelin activation functions could perform well in optimization, including faster training time and smaller iterations (epochs), MSE training performance, and better tests. Low and high accuracy (92%) with an error rate of 0.01. So it was concluded that the training function and cyclical rule parameters with the tansig and purelin activation functions were able to optimize the traditional Back-propagation method, and the 5-10-1 model could be used for forecasting active cases of the coronavirus in Asia
Co-Authors Abdi Rahim Damanik Abdullah Ahmad Achmad Noerkhaerin Putra Adnan, Syed Muhammad Agung Pratama Agung Wibowo Agung Yusuf Pratama Agus Perdana Windarto Akbari, Imam Anan Wibowo Andi Sanggam Sidabutar Arifah Hanum Arifin Nur, Khairun Nisa Asro Pradipta Astuti, Wiwik Sri Ayu Artika Fardhani Azwar Anas Manurung Azwar Anas Manurung Bil Klinton Sihotang Cici Astria Damanik, Bahrudi Efendi Damayanti, Tri Febri Daniel Sitorus Dedi Kusbiantoro Dedi Suhendro Dedi Suhendro Dedy Hartama Dedy Hartama Dedy Hartama Dedy Hartama Dedy Hartama Deri Setiawan Desi Insani Natalia Simanjuntak Dewi, Rafiqa Dinda Nabila Batubara Edu Wardo Saragih eko hartato Eko Hartato Eko Kurniawan Eko Purwanto Elfin Efendi Eva Desiana Fajar Ramadan Fazira, Rizky Nazwa Febriyanto, R Tri Hadi Fikri Yatussa’ada Fitri Anggraini GS , Achmad Daengs Gumilar Ramadhan Pangaribuan Hardinata, Jaya T Harly Okprana Hartama, Dedy Hartama, Dedy Heru Satria Tambunan Heru Satria Tambunan, Heru Satria Ht. Barat, Ade Ismiaty Ramadhona Hutasoit, Rahel Adelina Hutasoit, Rahel Adelina Ihsan Maulana Muhamad Iin Parlina Iin Parlina Iin Parlina Iin Parlina Iin Parlina Iin Parlina Ika Okta Kirana Ika Okta Kirana Ika Okta Kirana Ika Okta Kirana Ika Okta Kirana Ika Purnama Sari Ilham Syahputra Saragih Imelda Asih Rohani Simbolon Indra Gunawan Indra Gunawan Indra Satria Indra Satria Indra Satria Indri Sriwahyuni Purba Irawan Irawan Irfan Sudahri Damanik Jalaluddin Jalaluddin Jalaluddin Jalaluddin Jaya Tata Hardinata Jeni Sugiandi Jonas Rayandi Saragih Jonas Rayandi Saragih Joni Wilson Sitopu Jufriadif Na`am, Jufriadif Juli Wahyuni Khairun Nisa Arifin Nur Khairunnissa Fanny Irnanda Kirana, Ika Okta M Mesran M Safii M. Safii M.Ridwan Lubis Manurung, Azwar Anas MARIA BINTANG Marseba Situmorang Martina Silaban Mesran, Mesran Meychael Adi Putra Hutabarat Mhd Ali Hanafiah Mhd Gading Sadewo Mhd. Billy Sandi Saragih Mhd.Buhari Sibuea Mora Malemta Sitomorang Muhammad Aliyul Amri Muhammad Aliyul Amri Muhammad Julham Muhammad Julham Muhammad Mahendra Muhammad Ridwan Lubis Muhammad Ridwan Lubis Muhammad Ridwan Lubis Muhammad Ridwan Lubis Muhammad Syafiq Muhammad Wijaya Napitupulu, Flora Sabarina Nasution, Rizki Alfadillah Nasution, Zulaini Masruro Nazlina Izmi Addyna Ni Luh Wiwik Sri Rahayu Ginantra Nur Ahlina Febriyati Nur Arminarahmah Nur Arminarahmah Nur, Khairun Nisa Arifin Nuraysah Zamil Purba Nurhayati Nurhayati Okprana, Harly Okta Andrica Putra Parlina, Iin Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih, Poningsih Putrama Alkhairi Rahmat W Sembiring Rahmat W. Sembiring Rahmat Zulpani Ramadani, Saputra Rapianto Sinaga Ratih Puspadini Reza Pratama Rita Mawarni Rizky Khairunnisa Sormin Ronal Watrianthos Roulina Simarmata Roy Chandra Telaumbanua Ruri Eka Pranata S Solikhun S Solikhun S Sumarno Sadewo, Mhd Gading Safii, M. Safruddin Safruddin Saifullah Saifullah Samuel Palentino Sinaga Samuel Palentino Sinaga Sandy Putra Siregar Saputra Ramadani Saragih, Irfan Christian Saragih, Jonas Rayandi Saragih, Mhd. Billy Sandi Sari, Riyani Wulan Sari, Riyani Wulan Sarjon Defit Setti, Sunil Sigit Anugerah Wardana Silaban, Herlan F Silfia Andini, Silfia Silitonga, Hotmalina Silitonga, Hotmalina Siregar, Sandy Putra Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun, Solikhun Suhada Suhada Suhada Suhada Sumarno Sumarno Sumarno Sumarno Sumarno Sumarno Sundari Retno Andani Sundari Retno Andani Sunil Setti Surya Hendraputra Susi Fitryah Damanik Syafri Maradu Manurung Syafrika Deni Rizki Syahri Ramadhan Teuku Afriliansyah Tia Imandasari Titin Handayani Sinaga Tri Welanda Vasma Vitriani Sianipar Veithzal Rivai Zainal Venny Vidya utari Vitri Roma Sari Wida Prima Mustika Widodo Saputra Widya Tri Charisma Gultom Widyasuti, Meilin Widyasuti, Meilin Winanjaya, Riki Yuhandri Yuhandri, Yuhandri Yuli Andriani Yuri Widya Paranthy Zulaini Masruro Nasution Zulaini Masruro Nasution Zulaini Masruro Nasution Zulaini Masruro Nasution Zulia Almaida Siregar