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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) 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 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) Jurasik (Jurnal Riset Sistem Informasi dan Teknik 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) 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 RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI JPM: JURNAL PENGABDIAN MASYARAKAT DEVICE Journal of Informatics Management and Information Technology KLIK: Kajian Ilmiah Informatika dan Komputer J-SAKTI (Jurnal Sains Komputer dan Informatika) 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

Wanto, Anjar

STIKOM Tunas Bangsa, Pematangsiantar, Indonesia.

Author-ID : 621424

Aerospace Engineering Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering 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 Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Analisis Dan Pemodelan Posisi Access Point Pada Jaringan Wi-Fi Menggunakan Metode Simulate Annealing Anjar Wanto; Jaya T Hardinata; Herlan F Silaban; Widodo Saputra
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 1, No 1 (2017): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Laying the position of the access point on the Wi-Fi network in a room is needed to optimize the signal strength received from the transmitter to the receiver. The parameters that determine the performance of the access point is the value of the signal strength. Strong or weak a signal access point will be affected by distance and barriers that exist between the access point and a client that accesses the access point. This study has been performed several simulations in multiple rooms are placed the access point to the receiver. The parameters used to measure the signal strength using inSSIDer applications that generate value RSSI (Received Signal Strength Indication) of a transmitter to the receiver and barriers (barriers) that may influence the strength of the signal. From this research strength of the signal received by the receiver not only in pengaruhui by the distance between accespoint to the recipient, but rather influenced by barriers (barriers) which is in a room. From the results of the research are expected to be able to obtain appropriate modeling to optimize access point placement position using the Simulate annealing method.

Performance Analysis and Model Determination for Forecasting Aluminum Imports Using the Powell-Beale Algorithm Nur Arminarahmah; Syafrika Deni Rizki; Okta Andrica Putra; Anjar Wanto
IJISTECH (International Journal of Information System and Technology) Vol 5, No 5 (2022): February
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Aluminum is one of the most important metals for the industrial world, but currently, aluminum is scarce due to a shortage of electricity, which makes manufacturers limit their production. Therefore, to overcome this scarcity, the government imports aluminum. Imports that are carried out continuously will more or less affect the wheels of the economy in this country. Therefore, it is necessary to predict the value of aluminum imports in the future so that later the demand for aluminum in Indonesia is stable and not too excessive in importing. The prediction method used is the Powell-Beale algorithm, which is one of the most commonly used artificial neural network methods for data prediction. This paper does not discuss the prediction results. Still, it discusses the ability of the Powell-Beale algorithm to make predictions based on imported Aluminum datasets obtained from the Central Statistics Agency. The research data used is aluminum import data by the leading country of origin from 2013-to 2020. A network architecture model will be formed and determined based on this data, including 3-15-1, 3-20-1, and 3-25-1. From these five models, after training and testing, the results show that the best architectural model is 3-20-1 with an MSE value of 0,03010927, the lowest among the other four models. So it can be concluded that the model can be used to predict aluminum imports.

Analysis of Artificial Neural Network Accuracy Using Backpropagation Algorithm In Predicting Process (Forecasting) Sandy Putra Siregar; Anjar Wanto
IJISTECH (International Journal of Information System and Technology) Vol 1, No 1 (2017): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Artificial Neural Networks are a computational paradigm formed based on the neural structure of intelligent organisms to gain better knowledge. Artificial neural networks are often used for various computing purposes. One of them is for prediction (forecasting) data. The type of artificial neural network that is often used for prediction is the artificial neural network backpropagation because the backpropagation algorithm is able to learn from previous data and recognize the data pattern. So from this pattern backpropagation able to analyze and predict what will happen in the future. In this study, the data to be predicted is Human Development Index data from 2011 to 2015. Data sourced from the Central Bureau of Statistics of North Sumatra. This research uses 5 architectural models: 3-8-1, 3-18-1, 3-28-1, 3-16-1 and 3-48-1. From the 5 models of this architecture, the best accuracy is obtained from the architectural model 3-48-1 with 100% accuracy rate, with the epoch of 5480 iterations and MSE 0.0006386600 with error level 0.001 to 0.05. Thus, backpropagation algorithm using 3-48-1 model is good enough when used for data prediction.

Architectural Model of Backpropagation ANN for Prediction of Population-Based on Sub-Districts in Pematangsiantar City Marseba Situmorang; Anjar Wanto; Zulaini Masruro Nasution
IJISTECH (International Journal of Information System and Technology) Vol 3, No 1 (2019): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

A population is a group of individuals who occupy or live in a place or area that interacts with one another. Because the population has a very important role in an area, it is important to make predictions to find out how much the level of increase or descent of the population in an area, especially in Pematangsiantar. Therefore this research was conducted. This study uses population data in 8 Sub-Districts in Pematangsiantar. Data was taken from the Central Statistics Agency (BPS) of Pematangsiantar city in 2011-2017. The method used is the Artificial Neural Network (ANN) Backpropagation. These data will be processed into 2 parts namely training data and Testing data. This research will use 5 architectural models namely, 3-25-1, 3-30-1, 3-45-1, 3-54-1 and 3-68-1. From these 5 architectural models, after analysis, models 3-45-1 were chosen as the best models with epoch 553 values, MSE training 0,0001108768, MSE testing 0.0012355953 and an accuracy rate of 88%. The results of this paper are expected to be widely useful, especially for academics as further research material, especially those related to population in Pematangsiantar, because this research is still limited to discussing the level of accuracy, not prediction results.

The Application of Data Mining in Determining Timely Graduation Using the C45 Algorithm Asro Pradipta; Dedy Hartama; Anjar Wanto; Saifullah Saifullah; Jalaluddin Jalaluddin
IJISTECH (International Journal of Information System and Technology) Vol 3, No 1 (2019): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Graduating on time is one element of higher education accreditation assessment. In the Strata 1 level, students are declared to graduate on time if they can complete their studies <= eight semesters or four years. BAN-PT sets a timely graduation standard of >= 50%. If the standard is not met, it will reduce the value of accreditation. These problems encourage the Universitas Simalungun Pematangsiantar to conduct evaluations and strategic steps in an effort to increase student graduation rates so that the targets of BAN-PT can be achieved. For this reason it is necessary to know in advance the pattern of students who tend not to graduate on time. In this study, C4.5 Algorithm is proposed to predict student graduation. This algorithm will process student profile datasets totaling 150 data. This dataset has a graduation status label. The value of the label is categorical, that is, right and late. The features or attributes used, namely the name of the student, gender, student status, GPA. The results of the C4.5 algorithm are in the form of a decision tree model that is very easy to analyze. In fact, even by ordinary people. This model will map the patterns of students who have the potential to graduate on time and late.

ANALISIS ALGORITMA AES DALAM MENGAMANKAN DATA PADA KANTOR WALIKOTA PEMATANGSIANTAR eko hartato; Indra Gunawan; Iin Parlina; Solikhun Solikhun; Anjar Wanto
JURNAL ILMIAH INFORMATIKA Vol 8 No 01 (2020): Jurnal Ilmiah Informatika (JIF)
Publisher : Teknik Informatika

Data is information that is kept very confidential because it contains important information about the company or agency. Computers are currently the main component in the company that is able to store data, speed up work, improve the quality and quantity of services, simplify the transaction process, and others. But in terms of computer security still has several loopholes that allow a person or group to easily retrieve data or information on the computer. To avoid theft and manipulation of data, it is necessary to implement a security system. Cryptography is the study of how to change information from normal conditions / forms (can be understood) into a form that cannot be understood. One method that can be used to secure messages / information is the Advanced Encryption Standard (AES). The application of the AES cryptographic algorithm in securing data at the Pematangsiantar Mayor's Office shows that this algorithm can generate encryption that cannot be understood by humans and produces the exact decryption with the initial plaintext input.

PREDIKSI PRODUKSI SUSU SEGAR DI INDONESIA MENGGUNAKAN ALGORITMA BACKPROPAGATION Jonas Rayandi Saragih; Dedy Hartama; Anjar Wanto
JURNAL ILMIAH INFORMATIKA Vol 8 No 01 (2020): Jurnal Ilmiah Informatika (JIF)
Publisher : Teknik Informatika

Milk is a white liquid produced from female mammals that contain carbohydrates that are useful for humans. Based on data from the Indonesian Statistics Agency, milk productivity in Indonesia from 2012 to 2018 experienced an unstable curve. Therefore this research was conducted to predict and find out the level of development of milk productivity in Indonesia for the following years, so that companies that use milk have a reference to continue to strive to increase milk productivity in Indonesia to remain stable in order to meet the needs of the community and minimize milk imports. This algorithm used is backpropagation neural network. This algorithm is able to predict good data especially data that is sustainable in a certain period of time. to simplify this research the author uses the Matlab 2011 application. To facilitate writers, authors use 5 architectural model, namely 5-9-1 = 94%, 5-12-1 = 88%, 5-14-1 = 88%, 5-15-1 = 94%, 5-17-1 = 94 %. So we get the best architectural model using the architectural mode 5-15-1 with an accuracy rate of 94% with MSE = 0,000999842. Finally, this model is good enough to predict fresh milk production by province in Indonesia

Penerapan Mikrokontroler Arduino Uno pada Desain Perancangan Sistem Ayunan Bayi Otomatis Agung Pratama; Poningsih; Sundari Retno Andani; Solikhun; Anjar Wanto
Journal of Informatics Management and Information Technology Vol. 1 No. 3 (2021): July 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v1i3.113

A baby swing is one of the objects commonly used by mothers to help put their babies to sleep. Starting from mothers who live in big cities to remote villages, they are familiar with baby swings. Usually, babies fall asleep quickly when sleeping in a swing. Another reason is that the baby can sleep longer, so the mother can do other unfinished activities. This research aims to design the design of an automatic baby swing system using the Arduino Uno R3 microcontroller Atmega 328. The assembly process of this tool uses a combination of the Arduino Uno R3 microcontroller with sound sensors, servo motors, led lights, and several supporting components such as jumper cables, boards, and others. Based on the experimental results, this tool can be used as a control system for the baby's swing, so that the swing will automatically move on its own when the baby cries, so that the baby can fall back asleep. So it can be concluded that with this automatic baby swing, it will help ease the work of a mother who wants to do other work.

Penerapan ML dengan Teknik Bayesian Regulation untuk Peramalan Usia Penduduk di Beberapa Negara Asia Ratih Puspadini; Anjar Wanto; Nur Arminarahmah
Journal of Computer System and Informatics (JoSYC) Vol 3 No 3 (2022): May 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i3.1692

Knowing the age of life of the population in a country is useful for evaluating the performance of the government, whether the government is able to prosper the population in general, and improve health status in particular. The purpose of this paper is to forecast the age of the population in several major countries in Asia, so that the government has a benchmark in determining policies to further improve the welfare and health of the population in their respective countries. The forecasting method in this paper will use Machine learning algorithms with Bayesian Regulation techniques. The research data used is data on population expectations in several Asian countries sourced from the United Nations: "World Population Prospect: The 2010 Revision Population Database". This research is a development of research that has been done before, using the Cyclical order technique. Previous research used 5 architectural models (3-5-1, 3-8-1, 3-10-1, 3-5-8-1 and 3-5-10-1), with the best model being 3-5-10 -1 which results in an accuracy of 97%, MSE 0.0008358919, training time of 27 seconds and an error rate of 0.03. Meanwhile, this research only uses 3 modified architectural models (2-5-1, 2-10-1 and 2-5-10-1), with the best model being 2-5-1. The result is that this study is better than previous studies. The benchmark is seen from a smaller error rate (0.02), better accuracy (100%), to a faster training time (5 seconds). So it can be concluded, Bayesian Regulation technique works better than Cyclical order and the 2-5-1 architectural model will be used to make predictions

Akurasi Prediksi Ekspor Tanaman Obat, Aromatik dan Rempah-Rempah Menggunakan Machine Learning Muhammad Mahendra; Roy Chandra Telaumbanua; Anjar Wanto; Agus Perdana Windarto
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 2 No. 6 (2022): Juni 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v2i6.402

Spices are parts of plants that have a strong aroma and are used in small amounts in foods as flavours, preservatives, and food coloring. Spices are usually used as medicines, natural dyes, and spices. As a kitchen spice, spices have a variety of types, but have almost the same shape and color. In this study, the Machine Learning algorithm was tested which is one of the Artificial Neural Network methods that is often used to predict data. The research data used are export data of medicinal, aromatic and spice plants in 2012-2020. Based on this data, a network architecture model will be determined, including 3-10-1, 3-15-1, 3-20-1, 3-25-1. From the five models, training and testing were carried out first and then obtained the results that the best architectural model was 3-10-1 with 0.01929300. So it can be concluded that the model can be used to predict the export data of medicinal, aromatic and spice plants

Co-Authors Abdi Rahim Damanik Agung Pratama Agung Wibowo Agung Yusuf Pratama Agus Perdana Windarto Agus Perdana Windarto Andi Sanggam Sidabutar Arifah Hanum Asro Pradipta Ayu Artika Fardhani Azwar Anas Manurung Azwar Anas Manurung Bahrudi Efendi Damanik Bil Klinton Sihotang Cici Astria 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 Fikri Yatussa’ada Fitri Anggraini Flora Sabarina Napitupulu GS , Achmad Daengs Gumilar Ramadhan Pangaribuan Hartama, Dedy Hartama, Dedy Herlan F Silaban Heru Satria Tambunan Heru Satria Tambunan 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 Gunawan Indra Gunawan Indra Satria Indra Satria Indri Sriwahyuni Purba Irawan Irawan Irfan Christian Saragih Irfan Sudahri Damani, Irfan Sudahri Jalaluddin Jalaluddin Jalaluddin Jalaluddin Jaya T Hardinata Jaya Tata Hardinata Jonas Rayandi Saragih Jonas Rayandi Saragih Joni Wilson Sitopu Jufriadif Na`am, Jufriadif Juli Wahyuni Khairunnissa Fanny Irnanda Kirana, Ika Okta M Mesran M Safii M.Ridwan Lubis 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 Nasution, Rizki Alfadillah Nasution, Zulaini Masruro Ni Luh Wiwik Sri Rahayu Ginantra Nur Ahlina Febriyati Nur Arminarahmah Nur Arminarahmah Nuraysah Zamil Purba Nurhayati Nurhayati Okprana, Harly Okta Andrica Putra Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih R Tri Hadi Febriyanto Rahmat W Sembiring Rahmat W. Sembiring 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 Safruddin Safruddin Saifullah Saifullah Samuel Palentino Sinaga Samuel Palentino Sinaga Sandy Putra Siregar Saragih, Irfan Christian Saragih, Jonas Rayandi Saragih, Mhd. Billy Sandi Sari, Riyani Wulan Sari, Riyani Wulan Sarjon Defit Sigit Anugerah Wardana Silfia Andini Silitonga, Hotmalina Silitonga, Hotmalina Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun, Solikhun Suhada Suhada Suhada Suhada Sumarno Sumarno Sumarno Sumarno Sumarno Sumarno Sundari Retno Andani Sunil Setti Surya Hendraputra Susi Fitryah Damanik Syafri Maradu Manurung Syafrika Deni Rizki Syahri Ramadhan Tia Imandasari Titin Handayani Sinaga Tri Febri Damayanti Tri Welanda Vasma Vitriani Sianipar 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

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