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INDONESIA
Jurnal RESISTOR (Rekayasa Sistem Komputer)
Published by STMIK STIKOM Indonesia
ISSN : 25987542     EISSN : 25989650     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Energy Engineering
Jurnal RESISTOR merupakan jurnal yang diterbitkan oleh Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK STIKOM Indonesia, dengan P-ISSN 2598-7542 dan E-ISSN 2598-9650. Jurnal RESISTOR diterbitkan pertama kali pada bulan Oktober 2017 dan memiliki periode penerbitan sebanyak dua kali dalam setahun, yaitu pada bulan April dan Oktober.
Arjuna Subject : -
Articles 8 Documents
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Search results for , issue "Vol. 2 No. 2 (2019): Jurnal RESISTOR Edisi Oktober 2019" : 8 Documents clear
SIMULASI NDN MENGGUNAKAN NDNSIM PADA JARINGAN INTRANET KAMPUS TEKNOLOGI INFORMASI FAKULTAS TEKNIK UNIVERSITAS UDAYANA I Putu Agus Eka Pratama; Mohammad Ernico Suryo Wicaksono
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 2 No. 2 (2019): Jurnal RESISTOR Edisi Oktober 2019
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v2i2.330

Abstract

NDN (Named Data Networking) is one of today's internet technologies with identifier of the packet is given in the form of a content name, not a source or destination address. Such properties make NDN have a new forwarding mechanism and different from host to host (IP-based) network architecture. Utilization of this new technology is usually incomplete or there is a need for simulations for initial testing and testing. This paper will discuss about NDN simulation. The simulation will be done using ndnSIM, an open source simulator and testing was performed at Information Technology Campus, Faculty of Engineering, Udayana University’s intranet.
ANALISIS JARINGAN SYARAF TIRUAN METODE BACKPROPOGATION DALAM MEMPREDIKSI KETERSEDIAAN KOMODITAS BERAS BERDASARKAN PROVINSI DI INDONESIA Abdullah Ahmad; Pipit Mutiara Putri; Winanda Alifah; Solikhun Solikhun
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 2 No. 2 (2019): Jurnal RESISTOR Edisi Oktober 2019
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v2i2.358

Abstract

Food is a major human need that must be completed at any time. This right is one of human rights, stated in article 27 of the 1945 Constitution and in the Rome Declaration (1996). These considerations underlie the issuance of Law No. 7/1996 concerning Food. With these considerations, the Government always considers increasing food security related to increasing domestic production. This research is expected to contribute to the government in order to predict the contribution of rice by province in Indonesia. The data used is data from the National Statistics Agency through the website www.bps.go.id. The data is data on rice / rice production based on provinces in Indonesia in the period of 2010 to 2015. The algorithm used in this study is Artificial Neural Networks with the Backpropagation method. The input (input) variables used are data for 2010 (X1), data for 2011 (X2), data for 2012 (X3), data for 2013 (X4), data for 2014 (X5) and data for 2015 as targets with models training and testing architecture of 4 architectures namely 4-4-1, 4-8-1, 4-16-1, 4-32-1. The resulting output is the best pattern of ANN architecture. The best architectural model is 4-4-1 with 218 days, MSE 0.012728078 and an accuracy rate of 97%. From this model obtained from estimates obtained from provinces in Indonesia.
RANCANG BANGUN ALAT KONVEYOR UNTUK SISTEM SOLTIR BARANG BERBASIS MIKROKONTROLER ARDUINO UNO I Made Niki Arijaya
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 2 No. 2 (2019): Jurnal RESISTOR Edisi Oktober 2019
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v2i2.363

Abstract

Expedition delivery of goods very much Prepared by the people of Indonesia. in freight forwarding services in Indonesia has several expeditions in existence. One of them expedition TIKI, on TIKI expedition do sorting of goods which will be thrown to courier by way of worker will estimate width, height and weight of the goods. In this study made Conveyor Tool For System Sort Item that use arduino uno with load cell sensor and utrasonik sensor. On wide readings using two ultrasonic sensors that are placed on the outside of the place. And using one ultrasonic sensor measuring height and one heavy cell sensor load. At the same time in places where the sensor will read and afterwards the items will be brought by the conveyor and bar to the specified place. From the results of the study of goods in the pilah and take appropriate kereteria in the set.
MODEL ALGORITMA RESILIENT BACKPROPAGATION DALAM MEMPREDIKSI EKSPOR BIJIH COKLAT MENURUT NEGARA TUJUAN UTAMA DALAM MENDORONG LAJU PERTUMBUHAN EKONOMI Sundari Retno Andani Neno; Rafiqa Dewi Rafiqa; Solikhun Lihun
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 2 No. 2 (2019): Jurnal RESISTOR Edisi Oktober 2019
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v2i2.383

Abstract

The purpose of this study predicts the export of brown ore according to the country the main objective in driving the pace of economic growth. Cocoa beans including plantation products are exported and are very profitable for Indonesia. However, the quality of cocoa beans exported by Indonesia is known to be low. The low quality of Indonesian cocoa is due to several reasons, including rare Indonesian cocoa beans which are fermented first. Indonesia is an exporter of cocoa beans. The government must be able to predict brown ore exports in the future so that the government can take steps or policies on how to make reliable strategies in an effort to increase the export of brown ore in the future. Backpropagation is one of the ANN models that has the ability to get a balance between the ability of the network to recognize patterns used during training and the ability of the network to respond correctly to input patterns that are similar (but not the same) to the patterns used during training. After a training experiment and testing of architectural models 12-4-1, 12-8-1, 8-12-1, and 8-16-1, the best architectural model was 12-12-1 with 100% accuracy.
PENERAPAN DATA MINING PADA JUMLAH PELANGGAN PERUSAHAAN AIR BERSIH MENURUT PROVINSI MENGGUNAKAN METODE K-MEANS CLUSTERING Lestari Sinaga; Abdullah Ahmad; Muhammad Safii
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 2 No. 2 (2019): Jurnal RESISTOR Edisi Oktober 2019
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v2i2.418

Abstract

Water is one of the primary needs for humans so that everyone has the right to get clean water for their daily needs. Along with increasing population, the need for water will increase. So with that the PDAM must sell clean / decent water to its customers, clean water becomes the focus of attention and has the greatest power compared to other problems. Because water is a basic necessity, most of the companies impose rates that can be reached by the community and prices are adjusted to the growth in demand. The purpose of this research is to get a grouping of the number of customers of clean water companies in all provinces using the K-Means Algorithm, K-Means is a method for grouping data into a cluster by calculating the closest distance from a data to a centroid point. Clusters used are high level clusters (C1), medium level clusters (C2), and for low level clusters (C3). Centroid data obtained is for high-level clusters (C1) which are as many as 7710154, for medium-level clusters as much as 929586, and for low-level clusters as much as 112462. Based on the calculated data obtained high-level results, namely the province of Indonesia, for the medium level namely province North Sumatra, DKI Jakarta, West Java, Central Java and East Java, and other provinces are low levels. So that this result can be a support for the company in order to increase water needs.
PENANGANAN DATA MISSING VALUE PADA KUALITAS PRODUKSI JAGUNG DENGAN MENGGUNAKAN METODE K-NN IMPUTATION PADA ALGORITMA C4.5 Moch. Lutfi; Mochamad Hasyim
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 2 No. 2 (2019): Jurnal RESISTOR Edisi Oktober 2019
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v2i2.427

Abstract

Corn is a staple crop for Indonesian people because most of his life is from the agriculture sector. To increase the productivity of corn, another thing to be aware of is looking at the quality of the corn products. Through empirical observation and observation, research explores and extracts data through the concept of data mining so that neglected data becomes useful. Thus determining the quality of corn production is an important task to help the farmers in determining the classification process. Missing value is a problem in maintaining a quality data. Missing value can be caused by several things, one of which is caused by an error at the time of data entry. Missing value will be a problem when the amount of data in large quantities, so it is very influential in the survey results. Therefore on this research proposed K-NN imputation method to handle missing value data. The results showed the accuracy of the C 4.5 algorithm classification process on the corn production dataset that experienced a missing value accuracy value of 92.90%. Whereas if done with special handling using the method K-NN imputation on the handling process missing value best value at k = 5 of 94.50% with this that the proposed method increases significantly.
ANALISA MANAGEMENT SISTEM PADA UNIVERSITAS MENGGUNAKAN COBIT Rizky Aditya Nugroho
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 2 No. 2 (2019): Jurnal RESISTOR Edisi Oktober 2019
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v2i2.433

Abstract

In an environment where improvement initiatives are commonly run out simultaneously in all different parts of the system, many applied sciences are employed to address organizational problems. This results in competition between various departments within the same organization for infrastructure support, compliance needs, resource requirements, etc., and an inevitable waste of costs occur due to overlapping efforts, eroding the main objective of most organizations, namely cost reduction. This trouble can be abridged if the section works together to handle the landscape when it comes to implementing several technologies and processing models simultaneously. Furthermore, systems are required to possess a thoroughgoing discernment of the chosen IT framework and best exercises for carrying out this framework simultaneously. A common idea in all case studies is the behavioral challenges regarding resistance from employees. It has handled by appropriate change management. Another typical behavior is that all organizations only implement features of the IT framework that they consider more important rather than performing an IT framework holistically. Recommendations based on these key findings have been included in the mix of existing best practices meant to lead to the academic community.
KLASIFIKASI PENGENALAN BUAH MENGGUNAKAN ALGORITMA NAIVE BAIYES Arif Saputra
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 2 No. 2 (2019): Jurnal RESISTOR Edisi Oktober 2019
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v2i2.434

Abstract

Manually sorting varieties of apples result in high costs, subjectivity, boredom, and inconsistencies associated with humans. A means is needed to distinguish between types of apples and, therefore, some reliable techniques are necessary to identify varieties quickly and without damage. The purpose of conducting research is to investigate the application and performance for Naive Bayes algorithm for apple varieties. This software methodology involves image acquisition, preprocessing, segmentation and analysis classification varieties for apple. The prototype of Apple's classification system was built using the MATLAB R2017 development platform environment. The results in this study indicate that the estimated average accuracy, sensitivity, precision, and specificity are 81%, 73%, 100%, and 70%, respectively. MLP-Neural shows that performance of the Naive Bayes technique is consistent with Principal, Fuzzy Logic, and Neural analysis with 89%, 91%, 87%, and 82% respectively in terms of accuracy. This study shows that Naif Bayes has excellent potential for identifying nondestructive and accurate apple varieties.

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