Implementasi Algoritma Machine Learning dalam Kompresi Citra Foto Sumbu Filosofi Yogyakarta
Implementation of Machine Learning Algorithm in Axis Photo Image Compression Yogyakarta Philosophy
Keywords:
K-Means, Kompresi, Machine Learning, Sumbu Filosofi JogjaAbstract
Proses kompresi citra merupakan salah satu teknik yang esensial dalam mengelola data visual, terutama dalam konteks pelestarian dan digitalisasi warisan budaya. Penelitian ini membahas penerapan algoritma K-means dalam kompresi citra foto Sumbu Filosofi Yogyakarta, yang meliputi kawasan-kawasan bersejarah dan simbolis dari Kraton Yogyakarta hingga Panggung Krapyak. Algoritma K-means digunakan untuk mengurangi jumlah warna dalam citra, yang bertujuan untuk mengurangi ukuran file tanpa mengorbankan kualitas visual yang signifikan. Hasil penelitian menunjukkan bahwa algoritma K-means efektif dalam kompresi citra dengan menghasilkan ukuran file yang lebih kecil dan tetap mempertahankan detail penting dari objek bersejarah. Studi ini juga menyoroti keuntungan dan keterbatasan dari metode kompresi ini dalam konteks pelestarian digital dan penyebaran informasi budaya. Dengan demikian, penggunaan algoritma K-means dapat menjadi solusi yang efisien untuk manajemen data visual dalam upaya konservasi dan promosi warisan budaya Yogyakarta.
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