ANALYSIS OF EGG KNOCKING SOUND FEATURES FOR CHICKEN EGG QUALITY IDENTIFICATION USING PRINCIPAL COMPONENT ANALYSIS (PCA): ANALISIS FITUR SUARA KETUKAN TELUR UNTUK IDENTIFIKASI KUALITAS TELUR AYAM MENGGUNAKAN METODE PRINCIPAL COMPONENT ANALYSIS (PCA) - Delila Septiani Dwi Putri; Bambang Heru Iswanto; Haris Suhendar (Joint Prosiding IPS dan Seminar Nasional Fisika, 2025)
The selection of quality chicken eggs is crucial before they are consumed by the public. The problem is that chicken eggs are easily perishable products due to various factors, resulting in consumers often encountering eggs of inadequate quality. In this study, the quality of chicken eggs is identified based on audio features extracted from the sound of egg tapping in both the time and frequency domains. The extracted features include energy, entropy, Zero Crossing Rate (ZCR), spectral centroid, and MFCC. The experiment was conducted using a sample of 100 chicken eggs, consisting of eggs suitable and unsuitable for consumption. Sound data was obtained by tapping the eggs vertically and horizontally. The data was analyzed using Principal Component Analysis (PCA). The results of the PCA visualization indicate that in both horizontal and vertical tapping positions, the differences in audio features between the two types of eggs can be identified, even though the distance between groups is relatively close and there is overlap in the horizontal tapping. The variance values for horizontal tapping in PCA1 and PCA2 are 51.69% and 19.43%, respectively. Meanwhile, for vertical tapping the values are 50.28% for PCA1 and 26.73% for PCA2. This research demonstrates that the sound of egg tapping can be utilized for egg quality identification and further developed for chicken egg quality classification.