Feature Extraction Technique Using Weighted Histogram Analysis Method (WHAM) for Herbs Discrimination Based on Gas Chromatography Signal

Herbs discrimination by investigating volatile compound using Gas Chromatography Mass Spectrometry (GCMS) is a common method adopted botanists and scientists. Based on this method, usually scientists would only focus the major in order to determine species of herbs. However, it difficult differentiate herbs same family group based pattern chromatography signal since they may have almost similar physical features, characteristics, aroma. In case, minor needs be considered analysis. This study proposes adoption Weighted Histogram Analysis Method (WHAM) that utilizes combination histogram between two single feature histograms peak area height data extract new features (chemical properties) derived from patterns. From results, found WHAM technique results better classification compared without application for extraction. The improvement reducing overlap clustering can result as will increase accuracy.