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yelly y nabuasa
ilmu komputer
Computer Science & IT

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ANALISIS METODE CYCLE CROSSOVER (CX) DAN METODE PARTIAL MAPPED CROSSOVER (PMX) PADA PENYELESAIAN KASUS TRAVELING SALESMAN PROBLEM (TSP) Theresia Kolo; Adriana Fanggidae; yelly y nabuasa
J-Icon : Jurnal Komputer dan Informatika Vol 7 No 1 (2019): Maret 2019
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v7i1.882

Abstract

Travelling Salesman Problem (TSP) is a form of a problem in optimizing the search for the shortest route by passing through every city in exactly one time. The problem of searching the shortest route of a location can be solved by using many other optimizing algorithms. In this research, genetics algorithm was used by using two crossover methods namely cycle crossover and partial-mapped crossover. The parameters used were crossover probability and mutation probability, the sum of the city, maximum generation, the sum of the population and also threshold. In this research two testing models were used. In the first one, in order to get the generation and the best fitness it used the 80% consistency stopping criteria, and in the second one, in order to get the best testing time, it used the 100 and 500 maximum generation stopping criteria. The result of the first test showed that PMX method is better than the CX one. This was shown through the 8 times of testing which the result was the best PMX generation was 104,0469 and the CX was 350,4563. The second test resulted that the best testing time of the PMX time was 1,1035 second and the CX method was 2,2374 second, thus, it can be concluded that the solution brought by the PMX method is considered better than the CX.
PENGOLAHAN CITRA DIGITAL PERBANDINGAN METODE HISTOGRAM EQUALIZATION DAN SPESIFICATION PADA CITRA ABU-ABU yelly y nabuasa
J-Icon : Jurnal Komputer dan Informatika Vol 7 No 1 (2019): Maret 2019
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v7i1.889

Abstract

A digital image processing software has been successfully constructed. The software can increase image contrast using the histogram equalization method. The results given by the equalizaton histogram method can improve image quality, so that the information in the image is more clearly seen. But not all digital images have a visual display that satisfies the human eye. Dissatisfaction can arise due to noise, the lighting quality in digital images that are too dark or too bright. So that a method is needed to improve the quality of the digital image. To improve image quality in terms of color contrast, we can give treatment to the histogram. The treatment referred to in this article is an equalization histogram on grayscale images. Image histogram is said to be good if it is able to involve all possible levels or levels at the gray level. Of course the goal is to be able to display details on the image so that it is easy to observe. The process of segmenting and repairing digital images is done using MATLAB.
Co-Authors Adriana Fanggidae Adriana Fanggidae Theresia Kolo