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RECOGNITION OF LOCAL CAPITAL USING SYMMETRIC TWO-DIMENSIONAL LINEAR DISCRIMINANT ANALYSIS Rina Widya Sari; Ismail Husein
ZERO: Jurnal Sains, Matematika dan Terapan Vol 1, No 2 (2017): July - December
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (768.588 KB) | DOI: 10.30829/zero.v1i2.1463

Abstract

Statistical pattern recognition is a system that aims to classify a number of objects to a number of categories or classes. Given a data matrix A, A = {Π1, Π2,…, Πk} where Πi consist of ni point data of ith class then patterns in each classes can classify and separate distance of within and between-class in datasets. In this paper, Symmetric Two-Dimensional Linear Discriminant Analysis proposed to maximize the between-class scatter matrices (Sb) and minimize the within-class scatter matrices (Sw), and can recognition the symmetric capital letter by hand writing such as A, B, C, D, E, H, I, K, M, O, S, U, V, W and Y by using ADL2-D algorithm.
Estimated North Sumatra Province Poor Population Percentage Using Penalized Spline Semiparametric Approach and Small Area Estimation Jihan Adelia Nasution; Rina Widya Sari; Ismail Husein
ZERO: Jurnal Sains, Matematika dan Terapan Vol 6, No 2 (2022): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v6i2.19265

Abstract

Poverty is one of the many problems that have not been completely resolved by the government in Indonesia, one of which is poverty in the province of North Sumatra. To estimate the percentage of poor people, data is needed in each area using the Small Area Estimation method. Small Area Estimation is used to estimate the parameters of a subpopulation that has a small scope. However, to get a better estimate, you can use an indirect estimation method, one of which is the semiparametric Penalized Spline approach. This method can be used in conjunction with small area estimation because it can connect the two components in the model between the response variable and the predictor variable which is linear and the relationship between the response variable and the predictor variable is non-linear. Based on the small area estimation model with a semiparametric penalized spline approach, the best is found in model 4 with a coefficient of determination value of 0.645 where the value is close to 1, which means the results are good to use. The average poor population in North Sumatra province is estimated at 15.38%, the highest poor population is in Pakpak Bharat at 22.66% and the lowest estimated poor population is in Deli Serdang at 7.51%.