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Yani Puspita Kristiani, Yani Puspita
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KLASIFIKASI KELOMPOK RUMAH TANGGA DI KABUPATEN BLORA MENGGUNAKAN MULTIVARIATE ADAPTIVE REGRESSION SPLINE (MARS) DAN FUZZY K-NEAREST NEIGHBOR (FK-NN) Kristiani, Yani Puspita; Safitri, Diah; Ispriyanti, Dwi
Jurnal Gaussian Vol 4, No 4 (2015): Wisuda periode Oktober 2015
Publisher : Jurusan Statistika UNDIP

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (479.943 KB)

Abstract

Good classification method will result on less classification error. Classification method developed rapidly. Two of the existing classification methods are Multivariate Adaptive Regression Spline (MARS) and Fuzzy K-Nearest Neighbor (FK-NN). This research aims to compare the classification of poor household and prosperous household based on per capita income which has been converted according to the poverty line between MARS and FK-NN method. This research used secondary data in the form of result of National Economy and Social Survey (SUSENAS) in Blora subdistrict in 2014. The result of the classification was evaluated using APER. The best classification result using MARS method is by using the combination of BF= 76, MI= 3, MO= 1 because it will result on the smallest Generalized Cross Validation (GCV) and the APER is 10,119 %. The best classification result using FK-NN method is by using K=9 because it will result on the smallest error and the APER is 9,523 %. The APER calculation shows that the classification of household in Blora subdistrict using FK-NN method is better than using MARS method. Keywords: Classification, MARS, FK-NN, APER, SUSENAS, Blora
KLASIFIKASI KELOMPOK RUMAH TANGGA DI KABUPATEN BLORA MENGGUNAKAN MULTIVARIATE ADAPTIVE REGRESSION SPLINE (MARS) DAN FUZZY K-NEAREST NEIGHBOR (FK-NN) Kristiani, Yani Puspita; Safitri, Diah; Ispriyanti, Dwi
Jurnal Gaussian Vol 4, No 4 (2015): Wisuda periode Oktober 2015
Publisher : Departemen Statistika FSM Undip

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (479.943 KB)

Abstract

Good classification method will result on less classification error. Classification method developed rapidly. Two of the existing classification methods are Multivariate Adaptive Regression Spline (MARS) and Fuzzy K-Nearest Neighbor (FK-NN). This research aims to compare the classification of poor household and prosperous household based on per capita income which has been converted according to the poverty line between MARS and FK-NN method. This research used secondary data in the form of result of National Economy and Social Survey (SUSENAS) in Blora subdistrict in 2014. The result of the classification was evaluated using APER. The best classification result using MARS method is by using the combination of BF= 76, MI= 3, MO= 1 because it will result on the smallest Generalized Cross Validation (GCV) and the APER is 10,119 %. The best classification result using FK-NN method is by using K=9 because it will result on the smallest error and the APER is 9,523 %. The APER calculation shows that the classification of household in Blora subdistrict using FK-NN method is better than using MARS method. Keywords: Classification, MARS, FK-NN, APER, SUSENAS, Blora