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Journal : Jurnal RESISTOR (Rekayasa Sistem Komputer)

CONTENT BASED IMAGE RETRIEVAL DENGAN METODE COLOR MOMENT DAN K-MEANS Sukafona, I Made; Thalib, Emmy Febriani
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol 1 No 2 (2018): Jurnal RESISTOR Edisi Oktober 2018
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (629.15 KB) | DOI: 10.31598/jurnalresistor.v1i2.322

Abstract

Content Based Image Retrieval (CBIR) is a research cluster that is very important to overcome problems related to the image search process. The development of internet technology and data communication has caused the number of multimedia images currently circulating to be very high. This study took the Color Moment method to carry out the feature extraction process. Before the feature extraction process, a segmentation process was carried out to separate the background image and the foreground image. Next, each background and front image is stored in the database. Method performance measurement is done by calculating the value of precision and recall. The test image used is the Wang dataset consisting of ten image classes. The test results show the level of recall or completeness of the images that were found to have increased significantly after using the K-Means segmentation process. But a high enough recall value decreases the value of precision or the comparison of true images with the image found overall. Precision values ​​decrease when compared to the CBIR method without running the K-Means segmentation.
CONTENT BASED IMAGE RETRIEVAL DENGAN METODE COLOR MOMENT DAN K-MEANS I Made Sukafona; Emmy Febriani Thalib
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 1 No. 2 (2018): Jurnal RESISTOR Edisi Oktober 2018
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v1i2.322

Abstract

Content Based Image Retrieval (CBIR) is a research cluster that is very important to overcome problems related to the image search process. The development of internet technology and data communication has caused the number of multimedia images currently circulating to be very high. This study took the Color Moment method to carry out the feature extraction process. Before the feature extraction process, a segmentation process was carried out to separate the background image and the foreground image. Next, each background and front image is stored in the database. Method performance measurement is done by calculating the value of precision and recall. The test image used is the Wang dataset consisting of ten image classes. The test results show the level of recall or completeness of the images that were found to have increased significantly after using the K-Means segmentation process. But a high enough recall value decreases the value of precision or the comparison of true images with the image found overall. Precision values ​​decrease when compared to the CBIR method without running the K-Means segmentation.
KNOWLEDGE BASED SYSTEM UNTUK REKOMENDASI DEWASA PENGABENAN PADA DESA ADAT MAMBAL I Putu Arya Putra; Emmy Febriani Thalib; Ida Bagus Ary Indra Iswara
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 5 No. 1 (2022): Jurnal RESISTOR Edisi April 2022
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v5i1.1091

Abstract

Applications for a good day to carry out the pengabenan ceremony of the mambal traditional village often encounter obstacles, with a process that is still manual, it certainly has a fairly high risk of error because it is caused by physical factors from a bendesa as an expert, including fatigue and forgetfulness. In this study, we will provide solutions to problems or obstacles experienced by the bendesa as an expert by designing and building a system that can represent a bendesa in the dewasa pengabenan application process by adopting the mindset of a bendesa in recommending dewasa pengabenan. The parameters used in this system consist of 54 conditions with 20 conditions that must be avoided. The parameters used are sasih, tri wara, panca wara, sapta wara, penanggal, panglong and wuku. The system that was built provides output in the form of recommendations for dewasa pengabenan, which are web-based, using the PHP framework Laravel programming language, and the database is managed with mysql. This system has been tested by the Bendesa as an expert and several users, the results obtained from the test can be concluded that the function of the features in the system is in accordance with what is expected