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All Journal Jurnal Informatika dan Rekayasa Perangkat Lunak DEVICE Jurnal Sains Teknologi dan Sistem Informasi Journal of Economic, Business and Engineering (JEBE) STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Indonesian Journal of Multidisciplinary on Social and Technology Clean Energy and Smart Technology TECHNOMEDIA : Informatics and Computer Science
Nahar Mardiyantoro
Universitas Sains Al-Qur'an
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences

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Ekstraksi Palet Warna untuk Kompresi Gambar Digital menggunakan Algoritma K-Means Ahmad Ma'ruf; Hidayatus Sibyan; Nahar Mardiyantoro
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 7 No. 1 (2025): Maret
Publisher : Universitas Wahid Hasyim

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Abstract

The growing needs for efficient image data compression have been driven by rapid technological advancement. This study evaluates the effectiveness of the K-Means algorithm for digital image compression through dominant color palette extraction and subsequent color quantization for image reconstruction. The research investigates how the number of clusters (K) affects both compression ratio and Peak Signal to Noise Ratio (PSNR). An experimental approach was implemented, compressing 24-bit RGB images at various resolutions (VGA, SVGA, HD, FHD) using different cluster quantities (8, 16, 32, 64, 96, 128). Through descriptive and correlation analyses, relationships between cluster numbers, compression ratio, Mean Squared Error (MSE), PSNR values, and processing time were examined. Results demonstrate that the K-Means algorithm achieves effective image compression, with an average compression ratio of 67%, MSE of 0.00077, PSNR of 81.43 dB, and processing time of 0.73 seconds. Compression quality was strongly influenced by cluster quantity, with both PSNR values and compression ratios improving as cluster numbers increased. The research determined that 96 clusters represents the optimal configuration, delivering high-quality compression with reasonable computational efficiency
Co-Authors Ahmad Ma'ruf dimas prasetyo utomo Erna Dwi Astuti Feni Yulianti Harun Al Rosid Hidayat, Muslim Hidayatus Sibyan Ibnu Alif Utomo Ihsanuddin, Iman Ahmad Imam Subekti Mefa Listiani Muhamad Fuat Asnawi Muhammad Abqoriyyan Yalmak Muhammad Alif Muwafiq Baihaqy Muslim Hidayat Naufal Ammar Raihan Nulgafan Nulngafan Nulngafan Nulngafan Nulngafan Nur Hasanah Saifu Rohman Saromah Sukowiyono Suwondo, Adi Zaid Husni Abdillah Zulhilmi