Identifikasi Kualitas Kesegaran Susu Sapi Melalui Pengolahan Sinyal Digital Berdasarkan Metode Gabor Wavelet Dan Klasifikasi Support Vector Machine

Anissa Widya Devianti, Bambang Hidayat, Sjafril Darana

Abstract

Abstrak Susu merupakan cairan bergizi yang dihasilkan dari ambing sapi yang memiliki banyak manfaat serta dapat membantu pertumbuhan dan daya tahan tubuh pada manusia. Seiring berjalan waktu, demi mendapat keuntungan besar, banyak penjual susu yang menurunkan kualitasnya melalui pencampuran air. Guna mengetahui kondisi susu segar dan murni, maka dapat dilihat berdasarkan warna, rasa, baud an tingkat keasamannya. Semakin berkembangnya teknologi, dibutuhkan teknologi yang dapat memudahkan konsumen mengukur kemurnian susu. Pada penelitian ini dilakukan identifikasi kualitas susu sapi melalui pengolahan sinyal digital dengan menggunakan metode Gabor Wavelet dan klasifikasi Support Vector Machine (SVM).Pemilihan metode Gabor Wavelet merupakan filter detektpr yang baik dan memungkinkan algoritma yang efektif dan adaptif. Klasifikasi Support Vector Machine (SVM) dipilih karena dapat meminimalisasi kesalahan dalam pengklasifikasian. Pengambilan data dilakukan dengan mengambil beberapa sampel susu murni asli dan susu murni yang telah dicampur air dengan jumlah 120 citra susu sapi. Dalam penelitian identifikasi kualitas kesegaran susu ini telah mencapai tingkat akurasi tertinggi sebesar 95% dan waktu komputasi 4.0110 detik. Kata Kunci : Susu Sapi, Gabor Wavelet, Support Vector Machine Abstract Milk is a nutritious liquid produced by the mammary glands of a female mammals, such as cow. As time goes on, many milk seller reduce the quality of the milk to increase the profit. The quality of the milk is decreased as it is exposed by the air. The purity and the freshness level of the milk can be known from its color, taste, smell, and the acidity level. In this era of globalization, the consumer needs a technology which can help them to measure the purity level of the milk. In this final project, the quality of cow's milk has been identified by processing the digital signal, using Gabor Wavelet method with Support Vector Machine (SVM) classification process. The Gabor Wavelet method selection is a good detector filter and enables an effective and adaptive algorithm. The Support Vector Machine (SVM) classification is chosen cause it can minimize errors in classification. The data of this final project is obtained by sampling some of pure milk and some of impure milk which has been mixed with water the amount of 120 images of cow's milk. The highest accuracy rate of this final project reaches 95% and computing time 4.0110 seconds. Keywords : Cow Milk, Gabor Wavelet, Support Vector Machine (SVM)

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