PERANCANGAN DAN IMPLEMENTASI ALGORITMA ELIAS GAMMA CODE UNTUK MENGKOMPRESI RECORD DATABASE PADA APLIKASI RANGKUMAN PENGETAHUAN UMUM LENGKAP

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Hikka Sartika ◽  
Taronisokhi Zebua
Keyword(s):  
Compression Ratio ◽  
General Public ◽  
Storage Capacity ◽  
Storage Space ◽  
File Size ◽  
Compression Technique ◽  
Code Algorithm ◽  
Database File ◽  
Large File

Storage space required by an application is one of the problems on smartphones. This problem can result in a waste of storage space because not all smartphones have a very large storage capacity. One application that has a large file size is the RPUL application and this application is widely accessed by students and the general public. Large file size is what often causes this application can not run effectively on smartphones. One solution that can be used to solve this problem is to compress the application file, so that the size of the storage space needed in the smartphone is much smaller. This study describes how the application of the elias gamma code algorithm as one of the compression technique algorithms to compress the RPUL application database file. This is done so that the RPUL application can run effectively on a smartphone after it is installed. Based on trials conducted on 64 bit of text as samples in this research it was found that compression based on the elias gamma code algorithm is able to compress text from a database file with a ratio of compression is 2 bits, compression ratio is 50% with a redundancy is 50%. Keywords: Compression, RPUL, Smartphone, Elias Gamma Code

IMPLEMENTASI ALGORITMA LEVENSTEIN DALAM MENGKOMPRESI TEKS PADA APLIKASI RANGKUMAN PENGETAHUAN ALAM LENGKAP

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Winda Winda ◽  
Taronisokhi Zebua
Keyword(s):  
Compression Ratio ◽  
Mobile Application ◽  
Storage Space ◽  
Compression Technique ◽  
The Public ◽  
Natural Knowledge ◽  
Database Size ◽  
Text Database

The size of the data that is owned by an application today is very influential on the amount of space in the memory needed one of which is a mobile-based application. One mobile application that is widely used by students and the public at this time is the Complete Natural Knowledge Summary (Rangkuman Pengetahuan Alam Lengkap or RPAL) application. The RPAL application requires a large amount of material storage space in the mobile memory after it has been installed, so it can cause this application to be ineffective (slow). Compression of data can be used as a solution to reduce the size of the data so as to minimize the need for space in memory. The levestein algorithm is a compression technique algorithm that can be used to compress material stored in the RPAL application database, so that the database size is small. This study describes how to compress the RPAL application database records, so as to minimize the space needed on memory. Based on tests conducted on 128 characters of data (200 bits), the compression results obtained of 136 bits (17 characters) with a compression ratio is 68% and redundancy is 32%.Keywords: compression, levestein, aplication, RPAL, text, database, mobile

scholarly journals IMPLEMENTASI ALGORITMA SUBEXPONENTIAL CODE UNTUK KOMPRESI FILE GAMBAR

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Amir Maniur Silitonga ◽  
Surya Darma Nasution ◽  
Putri Ramadhani
Keyword(s):  
Transfer Process ◽  
Storage Space ◽  
File Size ◽  
K Value ◽  
Image File ◽  
Code Algorithm ◽  
And Storage

Image file size is sometimes relatively large where the better the quality of the image produced, the pixel shape needed to record the image is bigger. With a very large image file size, at the time of the transfer process the transfer process could fail because the storage space media exceeds its limit. As for the Solution in this problem is how the image file can be compressed in order to accelerate the transfer and storage of image files. compression on image files is done by reducing the shape of the image file by reducing the bit in the image file, but does not eliminate the information data in it. By running compression, large files will shrink in size so that it can save storage space. In this study, the algorithm used is Subexponential Code, by using this method, the compression results from the k value have different results from each value, and the compression results will be advantageous in sending, and transferring image files will be easier.Keywords: image file compression, subexponential code algorithm

IMPEMENTASI ALGORITMA LEMPEL ZIV STORER SZYMANSKI (LZSS) PADA APLIKASI BACAAN SHALAT BERBASIS ANDROID

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
M. Edo Chandra
Keyword(s):  
Implementation Process ◽  
Original Text ◽  
Storage Space ◽  
Text File ◽  
File Size ◽  
Java Programming ◽  
File Storage ◽  
Large Size ◽  
Storage Area ◽  
Large File

Compression is a way to compress or modify data so that the required storage space is smaller and more efficient. In this study, the large file size in the prayer reading application makes the document storage space requires a lot of storage space due to the large file size. Due to the large size of the file that is currently making a large and inefficient file storage area and the larger size of a file makes the smartphone slow due to the file. The purpose of this study is to design an android-based prayer reading application by implementing the Szymanski Ziv Storer Lempel algorithm (LZSS). And designing a compression application using the Java programming language and database used is SQLite The results of the study show that after carrying out the implementation process with the LZSS algorithm on Reading Prayers, the decompression test results are known to be compressed text files that can be compressed and the size of the decompressed text file is the same as the original text file before it is compressed.Keywords: Implementation, compression, algorithm Lempel Ziv Storer Szymanski (LZSS).

scholarly journals PENERAPAN ALGORITMA INTERPOLATIVE CODING UNTUK KOMPRESI FILE AUDIO

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Riyo Oktavianty Finola
Keyword(s):  
Compression Ratio ◽  
Storage Space ◽  
Input File ◽  
Compression Method ◽  
File Size ◽  
Compression Process ◽  
Audio File ◽  
Audio Files

The size of the audio file can affect the time of sending data to be long and can cause waste of storage space. Therefore, compression is performed to compress the contents of the audio file into smaller ones. One of the compression techniques is lossless technique, which is a compression method where the compressed audio file can be returned to the file before it is compressed without losing information on the previous data. This study uses the Interpolative coding algorithm on mp3 audio files. Interpolative coding algorithm is an innovative way to assign dynamic code to data symbols. This method is different from other compression methods, because the code it provides for individual symbols is not static. The design of this system consists of 2 main processes namely the compression process and the decompression process and the process of calculating the performance of Compression Ratio (CR) and Redundancy. The resulting compression results in a new file with the * .ipc extension containing the compressed bit string which can then be decompressed. Application designed only one form, where in the form there is a process for compression and decompression, while the process of compressing the input file has the extension *. MP3 and produces output with the extension * IPC, and the size of the compressed audio file is smaller than the previous file size .Keywords: Compression, Audio File, Interpolative coding algorithm

scholarly journals Design and Development of a Very Large Scale Integrated Circuit Architecture for a Digital Image Compression and Realization on Field Programmable Gate Array

2020 ◽  
Vol 9 (3) ◽  
pp. 3510-3516
Keyword(s):  
Image Compression ◽  
Compression Ratio ◽  
Integrated Circuit ◽  
Large Scale ◽  
Image Data ◽  
High Compression Ratio ◽  
Compression Technique ◽  
Research Challenges ◽  
High Compression ◽  
Image Pixels

The domain of image signal processing, image compression is the significant technique, which is mainly invented to reduce the redundancy of image data in order to able to transmit the image pixels with high quality resolution. The standard image compression techniques like losseless and lossy compression technique generates high compression ratio image with efficient storage and transmission requirement respectively. There are many image compression technique are available for example JPEG, DWT and DCT based compression algorithms which provides effective results in terms of high compression ratio with clear quality image transformation. But they have more computational complexities in terms of processing, encoding, energy consumption and hardware design. Thus, bringing out these challenges, the proposed paper considers the most prominent research papers and discuses FPGA architecture design and future scope in the state of art of image compression technique. The primary aim to investigate the research challenges toward VLSI designing and image compression. The core section of the proposed study includes three folds viz standard architecture designs, related work and open research challenges in the domain of image compression.

scholarly journals CitySAC: A Query-Able CityGML Compression System

Smart Cities ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 106-117
Author(s):  
Chengxi Siew ◽  
Pankaj Kumar
Keyword(s):  
Data Storage ◽  
Spatial Data ◽  
City Planning ◽  
Data Transfer ◽  
Original Data ◽  
File Size ◽  
Compression Technique ◽  
3D Data ◽  
Data Infrastructures ◽  
Data Efficiency

Spatial Data Infrastructures (SDIs) are frequently used to exchange 2D & 3D data, in areas such as city planning, disaster management, urban navigation and many more. City Geography Mark-up Language (CityGML), an Open Geospatial Consortium (OGC) standard has been developed for the storage and exchange of 3D city models. Due to its encoding in XML based format, the data transfer efficiency is reduced which leads to data storage issues. The use of CityGML for analysis purposes is limited due to its inefficiency in terms of file size and bandwidth consumption. This paper introduces XML based compression technique and elaborates how data efficiency can be achieved with the use of schema-aware encoder. We particularly present CityGML Schema Aware Compressor (CitySAC), which is a compression approach for CityGML data transaction within SDI framework. Our test results show that the encoding system produces smaller file size in comparison with existing state-of-the-art compression methods. The encoding process significantly reduces the file size up to 7–10% of the original data.

Quantization Encoding Algorithm Based Satellite Image Compression

2017 ◽  
Vol 8 (3) ◽  
pp. 740
Author(s):  
Anand M ◽  
V. Mathivananr
Keyword(s):  
Image Compression ◽  
Satellite Images ◽  
Satellite Image ◽  
Region Of Interest ◽  
Digital Data ◽  
Storage Space ◽  
Compression Process ◽  
Compression Technique ◽  
Transmission Bandwidth ◽  
Image Technique

In the field of digital data there is a demand in bandwidth for the transmission of the videos and images all over the worlds. So in order to reduce the storage space in the field of image applications there is need for the image compression process with lesser transmission bandwidth. So in this paper we are proposing a new image compression technique for the compression of the satellite images by using the Region of Interest (ROI) based on the lossy image technique called the Quantization encoding algorithm for the compression. The performance of our method can be evaluated and analyzing the PSNR values of the output images.

A Computationally Efficient Switching Based Lossless Compression Algorithm for Natural Images

2012 ◽  
Vol 433-440 ◽  
pp. 6540-6545
Author(s):  
Vineet Khanna ◽  
Hari Singh Choudhary ◽  
Prakrati Trivedi
Keyword(s):  
Computational Complexity ◽  
Compression Ratio ◽  
Lossless Compression ◽  
Adaptive Threshold ◽  
Least Square ◽  
Natural Images ◽  
Prediction Algorithm ◽  
Computationally Efficient ◽  
Compression Technique ◽  
Hybrid Combination

This paper presents a new image lossless compression technique for natural images. The proposed algorithm uses the switching of existing Edge Directed Prediction algorithm and gradient Adaptive Predictor (GAP ) methods. The proposed algorithm is a switching based algorithm and the criteria of switching are based upon the adaptive threshold. We know that EDP has higher computational complexity due to the estimation of LS (Least Square ) based paramter whereas GAP has relatively lower computational complexity. So, in order to reduce the computational complexity we had made a hybrid combination of EDP and GAP Method which the proposed algorithm is a generic algorithm and it produces the best results in different varieties of images in terms of both compression ratio and computational complexity.

scholarly journals Analysis of Even-Rodeh Code For Text Compression

2020 ◽  
Vol 4 (1) ◽  
pp. 1
Author(s):  
Rian Syahputra
Keyword(s):  
Lossless Compression ◽  
Compression Algorithm ◽  
Text Compression ◽  
Storage Space ◽  
Code Algorithm

Text compression is used to reduce the repetition of letters so that the storage space used becomes smaller and transmission becomes faster. Techniques in text compression that can be used are using lossless compression. Lossless compression is a type of compression where when the decompression process occurs no data is lost. The Even-Rodeh Code algorithm is a lossless type of compression algorithm that replaces the initial bit code of the data with a code from the Even-Rodeh Code algorithm so that it can produce smaller data sizes

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