Open AccessMetode Pencocokan Bunyi Ketuk Buah dengan Kadar Kemanisan Menggunakan k-Nearest Neighbour
Author(s) -
Ranny Ranny,
Yustinus Eko Soelistio,
Ni Made Satvika
Publication year - 2017
Publication title -
ultimatics : jurnal ilmu teknik informatika/ultimatics : jurnal teknik informatika
Language(s) - English
Resource type - Journals
eISSN - 2581-186X
pISSN - 2085-4552
DOI - 10.31937/ti.v8i2.520
Subject(s) - sweetness , mathematics , fourier transform , artificial intelligence , food science , pattern recognition (psychology) , computer science , taste , chemistry , mathematical analysis
The development of fruit local industry is very high, but it less competitive than the imported fruit product. The kind of Indonesian fruit is very variative, but the support technology in this industry is stiil not implemented. This problem make the local fruit industry cannot compete with imported fruit. The purpose of the research is to develop a technology that can increase the using of technology on fruit industry. This research focus is fruit sweetness measeurment technology. This research the fruit tapping sound. Fast Fourier Transform is used as sound feature extraction method to get the feature. Based on the feature the fruit sweetness level can be predicted using the k Nearest Neighbour (kNN). The experiment on this research is divided into two parts. is using the training data to predict the sweetness levelof the fruits. The result of the research shows that the correlation between tapping sound and sweetness level can be used to predict the sweetness level of the fruit.
Index Terms—Sweetness Degree, Brix, k Nearest Neighbor, and Fast Fourier Transform.