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Journal : Journal of Intelligent Computing and Health Informatics (JICHI)

Time Optimization of Watermark Image Quality Using Run Length Encoding Compression Mahiruna, Adiyah; Rachmawanto, Eko Hari; Istiawan, Deden
Journal of Intelligent Computing & Health Informatics Vol 4, No 2 (2023): September
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v4i2.12058

Abstract

Internet technology continues to have a significant impact on digital media, such as text, images, audio, and video. One effect is the ease of exchange, distribution, and duplication of digital data; on the other hand, this ease raises the problem of digital data being protected by copyright or digital data confidentiality. Watermarking is a way to protect digital data rights. Extensive research on watermarking has been conducted, including a hybrid DWT-DCT-SVD approach. Several studies have found weaknesses in the message insertion process; for example, the time required to insert a watermark image is relatively long, particularly for large images. To address the problem of long message insertion times, this study applies a compression process to the original image before the watermark image insertion process. The original image to be inserted into the watermark image is compressed using the run-length encoding (RLE) algorithm. The results of RLE compression demonstrate that image file size is reduced significantly, which optimizes the watermarking process. The experimental results demonstrate that watermarked images with RLE compression preprocessing exhibit better imperceptibility and comparable or improved PSNR values. Specifically, the image "Elaine" showed a PSNR improvement from 28.7541 to 31.4502 with RLE compression. These findingsĀ demonstrate that combining DWT-DCT-SVD with RLE compression not only reduces watermarking time but also maintains or enhances image quality, providing a robust solution for digital copyright protection.
Mapping Religious Harmony in the Special Capital Region Jakarta using K-Means Algorithm Istiawan, Deden; Sulistijanti, Wellie; Santoso, Arif Gunawan; Ustyannie, Windyaning
Journal of Intelligent Computing & Health Informatics Vol 4, No 1 (2023): March
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v4i1.11715

Abstract

D.K.I Jakarta is often called the window of Indonesia. As one of the largest cities in Indonesia, D.K.I Jakarta has various kinds of complex social problems. This research tries to identify and explore conditions of religious harmony in DKI Jakarta. In previous studies of religious harmony, the use of the index in assessing religious harmony could only describe the condition of religious harmony in general without indicating which factor was in measuring the level of religious harmony. This Research uses a clustering approach to analyse religious harmony in DKI Jakarta. The study found that cluster 0 has major problems that affect religious harmony compared to other clusters. Therefore, local government policies related to increasing religious harmony can be focused more on cluster 0, especially on variables that are shown to be low, namely empathy, non-violence, national commitment, and adaptability to local culture.
Poverty Mapping in Central Java Province Using K-Means Algorithm Istiawan, Deden
Journal of Intelligent Computing & Health Informatics Vol 1, No 1 (2020): March
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v1i1.5380

Abstract

Prosperity has a relative, dynamic, and quantitative meaning. Until now, the formula is not finished because it will continue to grow along with the times. Public welfare is a condition where all citizens are always in a condition that is completely adequate in all their needs. Poverty in Central Java Province is still above national poverty. Poverty grouping is one way to focus on the people's budget in each region so that they can take development policies and strategies that are right on target and effective. In this study, the proposed K-means algorithm for classifying poverty in Central Java is based on poverty indicators. The results of the first cluster study consisted of 22 districts / cities with the category of not poor, the second cluster consisted of 13 districts / cities that were categorized as poor.