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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) JURIKOM (Jurnal Riset Komputer) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) KLIK: Kajian Ilmiah Informatika dan Komputer BEES: Bulletin of Electrical and Electronics Engineering
Sumarno Sumarno
STIKOM Tunas Bangsa, Pematangsiantar
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Journal : Journal of Computer System and Informatics (JoSYC)

 1 
Implementasi Algoritma Data Encryption Standart (DES) Dalam Pengamanan Data Karyawan Ramayana Department Store Alan Boy Sandy Damanik; Indra Gunawan; Bahrudi Efendi Damanik; Sumarno Sumarno; Dedy Hartama
Journal of Computer System and Informatics (JoSYC) Vol 2 No 1 (2020): November 2020
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

Employee data is information that is very confidential because it contains important information about employees and their institutions. 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 data theft and manipulation, a security system must be implemented. Cryptography is a 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 DataEncryption Standard (DES). The application of the DES cryptography algorithm in securing Civil Servants data shows that this algorithm can generate encryption that cannot be understood by humans and produces the exact decryption of the initial plaintext input
Implementasi Algoritma Backpropagation Dalam Memprediksi Jumlah Penduduk Usia Produktif Pada Kota Pematangsiantar Mhd Ridho Azhar; Sumarno Sumarno; Indra Gunawan
Journal of Computer System and Informatics (JoSYC) Vol 2 No 2 (2021): February 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

The productive age itself is a population in the age group between 15 to 64 years, whether they work, go to school, and take care of the household, in this case individuals who are in the scope of productive age are people who can still work well to produce a product and services. This study uses an Artificial Neural Network (ANN) with the backpropgation method. The backpropagation algorithm is one of the existing methods of neural networks as a prediction, estimation, classification, and pattern recognition algorithm. The research data is secondary data sourced from the Central Statistics Agency (BPS) from 2013 to 2015. The data is divided into 2 parts, namely training and testing data. There are 5 architectural models used in this study. 2-20-1, 2-21-1, 2-22-1, 2-23-1, 2-24-1. Of the 5 architectural models used, the best 1 model is obtained, namely 2-24-1 with an accuracy level of 80%, MSE 0.00085177 and epoch 100. So this model is good for predicting the number of productive age population in the city of Pematangsiantar in the future
Algoritma Backpropagation Dalam Melakukan Estimasi Penjualan Beras Pada CV Hariara Pematangsiantar Ruri Eka Pranata; Indra Gunawan; Sumarno Sumarno
Journal of Computer System and Informatics (JoSYC) Vol 2 No 2 (2021): February 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

The need for rice is an important factor in Indonesia where people make rice as a staple food source. Pematangsiantar city has a rice mill and rice sale, one of which is CV Hariara Pematangsiantar. Every year the amount of rice in CV Hariara Pematangsiantar changes. Therefore a prediction is needed to determine the amount of rice sales that will come and this prediction will be useful for the company to increase rice sales in the future. The data to be predicted is data on the amount of rice sales in CV Hariara Pematangsiantar in 2014-2017. The algorithm used to make predictions is a backpropagation neural network. There are five architectural models used in this prediction namely, 2-25-1 has an accuracy rate of 60%, 2-32-1=40%, 2-47-1=80%, 2-50-1=80%, and 2-52-1=60%. The best architecture of the five models is 2-47-1 with an accuracy of 80% and MSE of 7,46434101. So this architectural model is good enough to predict the amount of rice sales in CV Hariara
Estimasi Pemberantasan Hama di Kebun Bah Jambi Menggunakan Algoritma Backpropagation Agung Bimantoro; Sumarno Sumarno; Heru Satria Tambunan
Journal of Computer System and Informatics (JoSYC) Vol 2 No 2 (2021): February 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

Oil palm, which is the largest palm oil producer, plays an important role in the welfare of the people in Indonesia because it creates many jobs. Oil palm plants cannot be separated from pests. The number of pest attacks on oil palm plants can cause a decrease in fruit production and can even cause the plant to die. In this study, the authors estimated the number of pest attacks in the oil palm plantation Unit Bah Jambi, North Sumatra using the backpropagation algorithm. The data used in this study were obtained directly from the Plantation Unit Bah Jambi plantation. In this study the authors used 5 architectural patterns; 2-10-1, 2-12-1, 2-14-1, 2-16-1, 2-16-1. Of the five architectural patterns used, the best architecture is obtained with an accuracy rate of 75%, 187 epoch iterations in 4 seconds, namely the 2-10-1 architectural pattern
Prediksi Hasil Produksi Kelapa Sawit PTPN IV Bahjambi Menggunakan Algoritma Backpropagation Venny Vidya utari; Anjar Wanto; Indra Gunawan; Sumarno Sumarno; Zulaini Masruro Nasution
Journal of Computer System and Informatics (JoSYC) Vol 2 No 3 (2021): Mei 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

Oil palm is a tropical plant of the Indonesian natural palmae group which has a tropical climate. The growth and harvest of oil palm also depends on fertilizers and the rainfall that falls every day. To get good production results it requires high ability and a lot of labor. Each production result certainly does not always increase, there must be a time when the production will decrease, therefore an algorithm is needed to predict it so that companies can find out the development of palm oil production in the future. In this study, researchers used the Backpropagation Algorithm. The Backpropagation Algorithm is an algorithm that functions to reduce the error rate by adjusting the weight based on the desired output and target, there are 5 training and data testing architectural models, namely 2-21-1, 2-22-1, 2-24-1, 2-26 -1 and 2-28-1. From the results of testing data on oil palm production, the best architectural model is obtained, namely 2-22-1 which shows that the target is reduced by the output that SSE is 0.35206024, from the data obtained, the performance of the calculation of artificial neural networks with the Backpropagation Algorithm gets an accuracy of 83.3%. . So that it can be used as a benchmark in predicting palm oil production, seen from the comparison of the desired target with the predicted target
Rancang Bangun Inverter Mengubah Arus Listrik DC ke AC Berbasis Arduino Uno Risky Binsar Pandapotan Simanjuntak; M Safii; Fitri Anggraini; Sumarno Sumarno; Indra Gunawan
Journal of Computer System and Informatics (JoSYC) Vol 2 No 4 (2021): Agustus 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v2i4.838

Abstract

At this time electrical energy is needed in terms of helping humans in carrying out their activities both in doing their daily work. In this case, it is impossible for there to be problems in periodic blackouts to save electricity resources carried out by PLN and to disrupt all human activities starting from the tools that require electrical energy. For this reason, it is necessary to anticipate by making an inverter which aims to make all the activities they do using electrical energy are not disturbed. This tool is assisted by using Arduino Uno as the main ingredient which later DC electrical energy, namely the battery, will convert electrical energy that we usually use AC electrical energy
Co-Authors Afriandi Afriandi Agung Bimantoro Alan Boy Sandy Damanik Alvin Fuadi Angga Sihasani Bahrudi Efendi Damanik Bahrudi Efendi Damanik Bil Klinton Sihotang Dedy Hartama Dedy Hartama Ferdinal Rahmat Gea Fitri Anggraini Handri Al Fani Heru Satria Tambunan Iin Parlina Ika Okta Kirana Indra Gunawan Jalaluddin Jalaluddin Jalaluddin Jalaluddin M Safii MARIA BINTANG Mhd Ridho Azhar Muhammad Afifuddin Javan Muhammad Aliyul Amri Muhammad Fajar Rahmat W Sembiring Risky Binsar Pandapotan Simanjuntak Rizki Ananda Ruri Eka Pranata Solikhun Solikhun Sunil Setti Venny Vidya utari Wanto, Anjar Zulaini Masruro Nasution Zulaini Masruro Nasution