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Hasih Pratiwi
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hpratiwi@mipa.uns.ac.id
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+6282134673512
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ijas@mipa.uns.ac.id
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Study Program of Statistics, Universitas Sebelas Maret, Surakarta 57126, Indonesia
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Kota surakarta,
Jawa tengah
INDONESIA
Indonesian Journal of Applied Statistics
Published by Universitas Sebelas Maret
ISSN : -     EISSN : 2621086X     DOI : https://doi.org/10.13057/ijas
Core Subject : Economy, Science, Agriculture, Social,
Agriculture, Biological Sciences & Forestry Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Environmental Science
Indonesian Journal of Applied Statistics (IJAS) is a journal published by Study Program of Statistics, Universitas Sebelas Maret, Surakarta, Indonesia. This journal is published twice every year, in May and November. The editors receive scientific papers on the results of research, scientific studies, and problem solving research using statistical method. Received papers will be reviewed to assess the substance of the material feasibility and technical writing.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 77 Documents
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Regresi Data Panel untuk Mengetahui Faktor-Faktor yang Mempengaruhi PDRB di Provinsi DIY Tahun 2011-2015 Dea Aulia Nandita; Lalu Bayu Alamsyah; Enggar Prima Jati; Edy Widodo
Indonesian Journal of Applied Statistics Vol 2, No 1 (2019)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v2i1.28950

Abstract

Population growth can encourage and hinder economic growth. This study aims to analyze the factors that influence gross domestic product (GDP) in Daerah Istimewa Yogyakarta (DIY) using panel data regression. This study uses three independent variables, namely number of population, number of poor population, and investment, while the dependent variable is GDP. We use secondary data obtained from Badan Pusat Statistik (BPS). The results obtained from the regression analysis of the data series time panel are generalized least square (GLS), while for the cross section data panel shows the REM model is more suitable than PLS and FEM. Based on the validity test of the influence or t-test, the variable that shows significant to the economic rate which is categorized as GRDP in the Daerah Istimewa Yogyakarta in 2011-2015 is the variable Total population and Investment which has a positive relationship.Keywords : economic growth rate, panel data regression, gross regional domestic product
Application of K-Means Clustering in Mapping of Central Java Crime Area Retno Tri Vulandari; Wawan Laksito Yuly Saptomo; Danar Wijaya Aditama
Indonesian Journal of Applied Statistics Vol 3, No 1 (2020)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v3i1.40984

Abstract

Crimes occur in many places and cause complex problems that have widespread impacts on all levels of society. Crime is related to several factors including crime index, the ratio of the number of police to the population, population density and poverty rates. In this study trying to develop an information system that is able to display and map crime-prone areas in Central Java. Based on these factors, it is used to classify regions in Central Java, namely the category of safe, quite vulnerable, vulnerable and very vulnerable. K-Means clustering method, is very suitable to be used in predicting and grouping which areas are included in the 4 categories. The formulation of the problem is to find out areas prone to crime in Central Java. Based on the results, there are 11 regions with safe categories, 4 areas with quite vulnerable categories, 13 regions with vulnerable categories and 6 regions with very vulnerable categories.Keywords : K-Means clustering, mapping, Central Java,  criminality, crime area.
A Robust Regression by Using Huber Estimator and Tukey Bisquare Estimator for Predicting Availability of Corn in Karanganyar Regency, Indonesia Hasih Pratiwi; Yuliana Susanti; Sri Sulistijowati Handajani
Indonesian Journal of Applied Statistics Vol 1, No 1 (2018)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v1i1.24090

Abstract

Linear least-squares estimates can behave badly when the error distribution is not normal, particularly when the errors are heavy-tailed. One remedy is to remove influential observations from the least-squares fit. Another approach, robust regression, is to use a fitting criterion that is not as vulnerable as least squares to unusual data. The most common general method of robust regression is M-estimation. This class of estimators can be regarded as a generalization of maximum-likelihood estimation. In this paper we discuss robust regression model for corn production by using two popular estimators; i.e. Huber estimator and Tukey bisquare estimator.Keywords : robust regression, M-estimation, Huber estimator, Tukey bisquare estimator
Front Matter Vol 2 No 2 Hasih Pratiwi
Indonesian Journal of Applied Statistics Vol 2, No 2 (2019)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v2i2.38495

Abstract

Front Matter Vol 3 No 2 2020 Hasih Pratiwi
Indonesian Journal of Applied Statistics Vol 3, No 2 (2020)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v3i2.48001

Abstract

Klasifikasi Jenis Pencabutan Layanan oleh Pelanggan Indihome Menggunakan Metode Chi-Square Automatic Interaction Detection Siti Khodijatunnuriyah; Hasih Pratiwi
Indonesian Journal of Applied Statistics Vol 2, No 2 (2019)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v2i2.34526

Abstract

Market segmentation is a classic topic in marketing which is never loss its attractiveness. In addition to market segmentation, customer satisfaction is important in the field of marketing. Customer satisfaction is a person's feelings after using goods or services produced by a company. High customer satisfaction shows a company's success in producing goods or services. Statistics provides many tools for segmentation research. One of statistical tool for segmentation research which takes the dependency method as an approach is Chi-Squared Automatic Interaction Detection (CHAID) analysis. CHAID analysis would provide decision tree like diagram which provide information about degree of association from dependent variable to the independent variables and the information about segments characteristic. In this case, the CHAID analysis is used to determine the type of service revocation segmentation by Indihome customers. Based on CHAID analysis, 25 segmentations were obtained, which consisted of revocation of the downgrade category of 45314 customers and the number of revocation of the Churn Out category by 11137 customers.Keywords : market segmentation, customer satisfaction, CHAID, Indihome
Estimator Nadaraya-Watson dengan Pendekatan Cross Validation dan Generalized Cross Validation untuk Mengestimasi Produksi Jagung Febriolah Lamusu; Tedy Machmud; Resmawan Resmawan
Indonesian Journal of Applied Statistics Vol 3, No 2 (2020)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v3i2.42125

Abstract

Nadaraya-Watson Estimator with kernel approach depends on two-parameter, those are kernel function and bandwidth choice. However, between the two of them, bandwidth choice gave a huge impact on the result of the estimation. By minimizing the value of Mean Square Error (MSE), Cross-Validation (CV) and Generalized Cross-Validation (GCV) gave the optimal bandwidth value. In this research, corn production was considered as the dependent variable, while the planted area, harvested area, and the fertilizer as the independent variable. The result of this research showed that Nadaraya-Watson Estimator with Generalized Cross-Validation gives a better corn production estimation with optimal bandwidth value 742392,2, with and  with MSE 202583,9.Keywords: kernel, estimator Nadaraya-Watson, cross validation, generalized cross validation.
Analisis Ketahanan Hidup Pasien Kanker Paru Menggunakan Regresi Weibull Arivatus Solehah; Mohamat Fatekurohman
Indonesian Journal of Applied Statistics Vol 1, No 2 (2018)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v1i2.25276

Abstract

Lung cancer is one of the diseases which difficult to detect because of uneasy symptoms detection till it develops being the risky one. But, if the disease has been found, it can spread fast and cause death. According to the data of WHO, the type of cancer which causes the most of death is lung cancer which reaches 1,3 milion death per year. Therefore, a survival analysis will be conducted to determine factors that affect the survival of lung cancer patient by using Weibull regression. The result shows some factors that significantly influence the survival of lung cancer patient are gender, erythrocyte, and general condition. Keywords : lung cancer; survival analysis; Weibull regression
Peramalan Tingkat Penghunian Tempat Tidur Hotel Bintang Tiga Kota Surakarta Menggunakan Metode Autoregressive Integrated Moving Average (ARIMA) Shindy Dwi Pratiwi
Indonesian Journal of Applied Statistics Vol 2, No 1 (2019)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v2i1.31428

Abstract

Surakarta is a cultural city that is now starting to attract domestic and foreign tourists. This makes many tourists visit the city of Surakarta so that it affects the occupancy rate of hotels in Surakarta. The occupancy rate of hotels in Surakarta has fluctuations from each year. The uncertainty of hotel occupancy rates in Surakarta will certainly affect investors to choose policies in the hotel industry so that hotel occupancy rates in Surakarta City need to be estimated for the next year. In this study, the Autoregressive Integrated Moving Average (ARIMA) method was used to forecast hotel occupancy rates in Surakarta from January to May 2018. By using the best model IMA (1.1), it was concluded that the occupancy rate of three-star Surakarta hotels increased every the month.Keywords : occupancy rate of hotel, forecasting, ARIMA.
Pemodelan Indeks Keparahan Kemiskinan di Indonesia Menggunakan Analisis Regresi Robust Melva Hilda Stephanie Situmorang; Yuliana Susanti
Indonesian Journal of Applied Statistics Vol 3, No 1 (2020)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v3i1.40838

Abstract

Poverty is one indicator to see the success of development in a country. The Poverty Severity Index can be used as one measure of the magnitude of poverty in an area. In the Poverty Severity Index data in Indonesia, in 2018 there were some outliers, so to analyze it used robust regression. The purpose of this study is to determine the significant factors on the Poverty Severity Index in Indonesia using robust regression with the M-estimation method. The results showed that the Poverty Severity Index model in Indonesia using robust regression was influenced by Gini Ratio, Percentage of Poor Population, and Pure Participation Rate with R-square = 94,8%.Keywords: Poverty Severity Index, robust regression.

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