OPTIMASI TEKNIK PRAPEMROSESAN PADA RESPON LUARAN SENSOR UNTUK PENINGKATAN KLASIFIKASI PORTABLE ELECTRONIC NOSE: UJI COBA DISKRIMINASI JAMU - , Dyah Kurniawati Agustika; , Dr.Eng. Kuwat Triyana ([Yogyakarta] : Universitas Gadjah Mada, 2012)
Portable electronic nose 4th generation (PEN4) had been developed in Universitas Gadjah Mada Material Physics and Electronics Instrumentation Laboratory. This PEN4 has had hardware part and data acquisition system, but not equipped with pattern recognition system yet. This research was focused on how to build a pattern recognition and classification system based on Principal Component Analysis (PCA) with preprocessing technique to equip PEN4. PEN4 then used to classify three kinds of herbal drink (kunir asem, beras kencur and temulawak). The optimization of preprocessing technique was done to produce the maximum classification result. From the optimization of three kinds preprocessing technique (baseline manipulation, Discrete Wavelet Transform (DWT), normalization), the DWT method of coif1 wavelet type in fourth, fifth and sixth level produced the highest first and second principal component. Cumulative percent of first and second principal component for fourth and fifth level reached 96%, level six reached 97%. Using this configuration, PEN4 was then used to classify the spoilage degree of the herbal drinks. The Total Plate Count as a method for counting the number of bacteria colony was used as a positive correlation probability confirmation of the existing bacteria in the drinks with the PCA result. The PCA patterns during 5 days of each herbal drink indicates that its aroma changed by time as a result of the spoilage process due to microorganisms. Therefore, the PEN4 may hold a promise as a herbal drinks spoilage degree assessments.