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Contact Name
Yuhefizar
Contact Email
jurnal.resti@gmail.com
Phone
+628126777956
Journal Mail Official
ephi.lintau@gmail.com
Editorial Address
Politeknik Negeri Padang, Kampus Limau Manis, Padang, Indonesia.
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INDONESIA
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
ISSN : 25800760     EISSN : 25800760     DOI : https://doi.org/10.29207/resti.v2i3.606
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) dimaksudkan sebagai media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai penelitian Rekayasa Sistem, Teknik Informatika/Teknologi Informasi, Manajemen Informatika dan Sistem Informasi. Sebagai bagian dari semangat menyebarluaskan ilmu pengetahuan hasil dari penelitian dan pemikiran untuk pengabdian pada Masyarakat luas dan sebagai sumber referensi akademisi di bidang Teknologi dan Informasi. Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) menerima artikel ilmiah dengan lingkup penelitian pada: Rekayasa Perangkat Lunak Rekayasa Perangkat Keras Keamanan Informasi Rekayasa Sistem Sistem Pakar Sistem Penunjang Keputusan Data Mining Sistem Kecerdasan Buatan/Artificial Intelligent System Jaringan Komputer Teknik Komputer Pengolahan Citra Algoritma Genetik Sistem Informasi Business Intelligence and Knowledge Management Database System Big Data Internet of Things Enterprise Computing Machine Learning Topik kajian lainnya yang relevan
Articles 14 Documents
Search results for , issue "Vol 3 No 1 (2019): April 2019" : 14 Documents clear
Analisis Perbandingan Perbaikan Kualitas Citra Pada Motif Batik Dengan Konsep Deteksi Tepi Robert, Sobel, Canny Menggunakan Metode Morfologi Muhammad Abrar Masril; Yuhandri; Jufriadif Na’am
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 3 No 1 (2019): April 2019
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (769.362 KB) | DOI: 10.29207/resti.v3i1.821

Abstract

Image results from quality edge detection are not optimal. From these problems a method is needed to improve the image quality of edge detection. The method used is Dilation Morphology on the results of edge detection of batik patterns. The results of testing the improved image quality of edge detection 10 batik patterns using Dilation Morphology show that Canny operators are able to produce very high accuracy from operators Robert and Sobel, with the percentage of Canny operators is 80%. While Robert operators with a percentage of 40% and Sobel operators 60%. The application of Dilation Morphology to operators Robert, Sobel and Canny can improve image quality of edge detection and improve accuracy in batik patterns.
Metode Weighted Product dalam Pemilihan Penerima Beasiswa Bagi Peserta Didik Roni Roni; Sumijan Sumijan; Julius Santony
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 3 No 1 (2019): April 2019
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (717.74 KB) | DOI: 10.29207/resti.v3i1.834

Abstract

Scholarships are one of the factors that can increase learning motivation for students. This scholarship is one of the school programs to help parents of students to ease the burden of education costs of the students. In determining the scholarship recipients who meet the requirements and eligibility at the MA Raudlatul Ulum a decision support system is using the Weighted Product method. Decision making in the Weighted Product method is done by multiplication to connect the rating of each attribute, where the rating of each attribute must be raised by the weight of the attribute in question. In this study there are several criteria used in decision making, namely Average Value, Behavior, Extracurricular, Parent Income, and Dependents of Parents. The research carried out begins with determining the weight of each criterion, then the ranking process is carried out which will produce the most optimal alternative. Based on the results of testing that has been done, it can be concluded that the system is able to provide accuracy of 90% if compared with the results of testing manually.
Sistem Tutorial Berbasis Kecerdasan Buatan Pada Proses Pengambilan Keputusan Perawatan dan Perbaikan Gitar Agusta Rakhmat Taufani; Harits Ar Ar Rosyid
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 3 No 1 (2019): April 2019
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1074.35 KB) | DOI: 10.29207/resti.v3i1.842

Abstract

Guitar is a popular musical instrument in the world and is a metronome for every use in various music events and its correlation. As a metronome, the guitar must be well standardized on the quality of each part so that sound that comes in line with the user's expectations in this case is the guitarist. Damage to the guitar is something normal because of its intense use so it needs proper handling in the repair process. The easiest thing is to bring a broken guitar to the experts, but when there are not many guitar service experts or a long enough distance to reach it, then guitar repairs need to be done immediately. Therefore, it is necessary to develop a system that can act as a tutor in the maintenance and repair of guitars by utilizing artificial intelligence embedded in the system. With the help of artificial intelligence, it is expected that the system can assist in the decision making of guitar technicians in the process of making guitar repair decisions based on the symptoms that occur. Decision making used uses the certainty factor method based on certainty factors. After going through the equivalence partitioning testing process, in general this system produces a total percentage of 100% on the success of the item test by experts in the testing process of the 25 items tested. Thus the application meets the requirements for making the program, which is readable and valid.
Credit Scoring Kelayakan Debitur Menggunakan Metode Hybrid ANN Backpropagation dan TOPSIS Susan Dwi Saputri; Ermatita Ermatita
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 3 No 1 (2019): April 2019
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (627.952 KB) | DOI: 10.29207/resti.v3i1.847

Abstract

Credit is one of the common practices that provide benefits for financial or non-financial institutions. However on the other hand, aid loans also have higher risks if the institutions give the wrong decision in giving a loan. Credit Scoring is one of techniques that can determine whether it is feasible to given a loan or not. The selection of a credit scoring model greatly determines the value in classifying credit that is feasible or not to giving a loan. Decision Support System (DSS) is one system that can be used to overcome this problem. The advantages of DSS are being able to overcome the problems that have semi-structured and unstructured data. In this study, DSS was supported by using Artificial Neural Network Backpropagation method and TOPSIS method to find the priority for seeking eligibility. Accuracy results obtained in this study reached 98,69% with the number of iteration is 300, the number of training data is 30, neuron hidden 12 and error tolerance is 0.001. TOPSIS method succeeded in ranking 185 data selected as recipients of credit. Keywords:Credit Scoring, Decision Support System (DSS), Artificial Neural Network (ANN), Backpropagation, TOPSIS.

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