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All Journal ESTIMASI: Journal of Statistics and Its Application
Anisa Anisa
Hasanuddin University
Mathematics

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Penggunaan Regresi Kuantil Multivariat pada Perubahan Trombosit Pasien Demam Berdarah Dengue Widya Nauli Amalia Puteri; Anna Islamiyati; Anisa Anisa
ESTIMASI: Journal of Statistics and Its Application Vol. 1, No. 1, Januari, 2020 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (603.895 KB) | DOI: 10.20956/ejsa.v1i1.9224

Abstract

Quantile regression is an extension of the regression model of conditional quantile where the distribution is derived from the response variable expressed as a co-variate function. Quantile regression can model data that contain outliers. Patterns of platelet change in DHF patients based on body temperature and white blood cells were analyzed by quantile regression using θ = 0,25; 0,50, and 0,75. Based on the parameter estimation results, the quantile θ = 0,25 and 0,75 obtained variables that affect the platelets of DHF patients are white blood cells. Significant differences from the variables in each quantile occur because of the possibility of other factors that influence the platelets of DHF patients that are not contained in the model. The difference in the influence of factors on each quantile requires an appropriate adjustment of medical measures so that efficiency can be obtained in handling DHF patients.
Estimasi Model Regresi Kuantil Spline Kuadratik pada Data Trombosit dan Hematokrit Pasien DBD Bunga Aprilia; Anna Islamiyati; Anisa Anisa; Nirwan Ilyas
ESTIMASI: Journal of Statistics and Its Application Vol. 1, No. 2, Juli, 2020 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (497.693 KB) | DOI: 10.20956/ejsa.v1i2.9264

Abstract

Nonparametric quantile regression is used to estimate the regression function when assumptions about the shape of the regression curve are unknown. It is only assumed to be subtle by involving quantile values. One estimator in nonparametric regression is spline. The segmented properties of the spline provide more flexibility than ordinary polynomials. Therefore, the nature of the spline makes it possible to adapt more effectively to the local characteristics of a function or data. This study proposes to get the results of the estimation platelet count model to the hematocrit value of DHF. The optimal model obtained from the estimation of quadratic spline quantile regression is at quantile 0.5 with one knot and the GCV value is 41.5. The results of the estimation show that there is a decrease in platelet counts as the percentage of hematocrit increase.
Pengelompokkan Tingkat Kriminalitas di Indonesia Menggunakan Algoritma Average Linkage Azman Azman; Anisa Anisa
ESTIMASI: Journal of Statistics and Its Application Vol. 2, No. 2, Juli, 2021 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v2i2.10749

Abstract

Crime needs to be analyzed and grouped so that the act does not cause harm either ecologically or psychologically. The statistical method that can be used to classify crime is the Average Linkage Algorithm. The study aims to group and analyze the characteristics of criminal cases in Indonesia. From the results of the analysis, 3 clusters were formed based on the average of each cluster. Cluster 1 consists of Aceh, West Sumatra, Riau, Jambi, South Sumatra, Bengkulu, Lampung, Kep. Bangka Belitung, Kep. Riau, West Java, Central Java, DI Yogyakarta, East Java, Banten, Bali, West Nusa Tenggara, East Nusa Tenggara, West Kalimantan, Central Kalimantan, South Kalimantan, East Kalimantan, North Sulawesi, Central Sulawesi, South Sulawesi, Southeast Sulawesi, Gorontalo, Maluku, North Maluku and Papua. Cluster 2 consists of North Sumatra while Cluster 3 consists of Metro Jaya. The grouping results are the basis of the government, apparatus, and the community in implementing the handling of criminal acts that occur in each cluster area so that prevention can minimize the losses caused by these crimes.
Co-Authors Anna Islamiyati Azman Azman Bunga Aprilia Nirwan Ilyas Widya Nauli Amalia Puteri