<![CDATA[Abstract— The rapid development of digital technology has increased the need for efficient storage and transmission of digital images. Large image file sizes can affect storage efficiency and data transfer processes, making image compression techniques necessary to reduce file size without significantly decreasing visual quality. This research aims to implement a web-based digital image compression system using a combination of Discrete Cosine Transform (DCT), quantization, Run Length Encoding (RLE), and Huffman Coding methods. The system was developed using the Laravel framework with support from HTML, CSS, and JavaScript, while image processing was performed using the canvas element in the browser. The compression process consists of RGB splitting, 8×8 blocking, DCT transformation, quantization, zigzag scanning, RLE, and Huffman Coding. The system also provides a before-after slider feature and evaluation parameters including Compression Ratio, Mean Squared Error (MSE), and Peak Signal-to-Noise Ratio (PSNR). Based on testing results using several JPG/JPEG images, the system achieved compression ratio values ranging from 79% to 97% with PSNR values between 31 dB and 38 dB. These results indicate that the proposed methods are capable of significantly reducing image file size while maintaining good visual quality.]]>
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