Pengenalan Pola Tulisan Tangan Suku Kata Aksara Sasak Menggunakan Metode Moment Invariant dan Support Vector Machine - Riska Yulianti; I Gede Pasek Suta Wijaya; Fitri Bimantoro (Journal of Computer Science and Informatics Engineering (J-Cosine), 2019)
The research of Javanese and Balinese ancient script have been done by some researches. However, the researches still have problems, such as image scaling, noise reduction and image transformation. This research implemented moment invariant and support vector machine to solve these problems especially on Sasak ancient script. The input data used in this research was 2700 handwritten Sasak ancient script. The testing was done to know the effect of thinning and the number of feature by using zoning on the classification performance. Accuracy is used as performance indicator. The highest average accuracy is 89.76%, on the second scenario, the average accuracy obtained is 92.52%.