THE DESIGN OF COCONUT MATURITY PREDICTION DEVICE WITH ACOUSTIC FREQUENCY DETECTION USING NAIVE BAYES METHOD BASED MICROCONTROLLER
DOI:
https://doi.org/10.26905/jeemecs.v2i1.2806Keywords:
IIR elliptic filter, Naive Bayes, MAX9814 sensor.Abstract
The level of coconut maturity can be determined by not only observing its shell color but also by applying audio recognition approach from knocking on coconut shell. This knocking sound distinguishes young, fairly mature, and mature coconut. Recognizing the sound characteristic of knocking on coconut is usually performed by the skilled ones who are having extensive experiences and sound sensitiveness of coconut knocking. In order to substitute the skilled ones, the design of coconut maturity prediction device with acoustic frequency detection is invented. The coconut sound signal is tapped by stethoscope which is connected to MAX9814 noise sensor. Arduino Due micro-controller is used to process the signal. The process in processing the signal consists of: conversing analog signal to digital, screening the signal, and finding the average value of sound signal frequency spectrum. The signal screening uses bandpass digital filter, type IIR (Infinite Impulse Response) Elliptic order 7. This filter is utilized in order that the signal that is being processed is not some noise but the signal of knocking sound on coconut. The calculation of average value of sound signal frequency spectrum uses FFT (Fast Fourier Transform) analysis. The maturity prediction is carried out using the classification method of Naive Bayes. The input is three average value of knocking sound frequency and coconut size, and the output is classification of coconut maturity. From this research, it is generated 80% of system success rate.
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2019-02-28
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