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All Journal International Journal of Evaluation and Research in Education (IJERE) ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika JOIN (Jurnal Online Informatika) AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Sisfokom (Sistem Informasi dan Komputer) J-SAKTI (Jurnal Sains Komputer dan Informatika) TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi, Kendali, Komputer, Elektrik, dan Elektronika J-SAKTI (Jurnal Sains Komputer dan Informatika) eProceedings of Engineering Jurnal INFOTEL Jurnal Informatika: Jurnal Pengembangan IT Intechno Journal : Information Technology Journal
Nuha, Hilal H
Fakultas Informatika, Universitas Telkom
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Social Sciences

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Journal : JOIN (Jurnal Online Informatika)

 1 
Lossless Text Image Compression using Two Dimensional Run Length Encoding Nuha, Hilal H
JOIN (Jurnal Online Informatika) Vol 4 No 2 (2019)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v4i2.330

Abstract

Text images are used in many types of conventional data communication where texts are not directly represented by digital character such as ASCII but represented by an image, for instance facsimile file or scanned documents. We propose a combination of Run Length Encoding (RLE) and Huffman coding for two dimensional binary image compression namely 2DRLE. Firstly, each row in an image is read sequentially. Each consecutive recurring row is kept once and the number of occurrences is stored. Secondly, the same procedure is performed column-wise to the image produced by the first stage to obtain an image without consecutive recurring row and column. The image from the last stage is then compressed using Huffman coding. The experiment shows that the 2DRLE achieves a higher compression ratio than conventional Huffman coding for image by achieving more than 8:1 of compression ratio without any distortion.
Data Visualization of COVID-19 Vaccination Progress and Prediction Using Linear Regression Nuha, Hilal H; Absa, Ahmad Abo
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.736

Abstract

This paper provides a data visualization and analysis of the COVID-19 vaccination program. Important information such as which countries have the highest vaccination rates and numbers. In addition to the types of vaccines used and used by countries in the world, an infographic on the geographic distribution of vaccine use is also shown. To model the obtained data, daily vaccination rates were modeled by linear regression in which five sample countries with different vaccination ranges were processed using data science approach, namely, linear regression. The modeling results show a gradient coefficient that represents an increase in vaccine rates. The prediction results showed that the highest rate of increase in daily vaccination was 1,826,126 additional vaccines per day.
Co-Authors Absa, Ahmad Abo Adin, Nur Adrian, Muhammad Kholilul Aji Gautama Putrada AULIA ARIF WARDANA Danuwijaya, Edghar Dita Oktaria Doan Perdana Endro Ariyanto Fajrin, Alvin Nur Favian Dewanta Ikke Dian Oktaviani Maisyadiva, Rafli Maman Abdurohman Maslin Masrom Mufidah, Nada Fajri Muhammad Al Makky Novian Anggis Suwastika Nurhalim, Rifqy Parman Sukarno Prajna Deshanta Ibnugraha Putra, Yohanes Armenian Qonita, Qori Rahmat Yasirandi Rio Guntur Utomo Salsabila, Balqis Hasna Suryahadi, Daniel Putra