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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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Front Matter Vol 3 No 1 2020 Hasih Pratiwi
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.v3i1.43192

Abstract

Front Matter Vol 1 No 1 Hasih Pratiwi
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.v1i1.24684

Abstract

Faktor-Faktor yang Mempengaruhi Kriminalitas di Indonesia Tahun 2011-2016 dengan Regresi Data Panel Kosmaryati Kosmaryati; Chandra Arinda Handayani; Refinanda Nur Isfahani; 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.v2i1.27932

Abstract

Criminality in Indonesia is increasing every year, therefore an effort is needed to reduce criminality in Indonesia, one of which can be used by knowing which factors influence the increase of criminality. This paper discusses the factors that influence criminality by using panel data regression analysis. Unemployment, domestic violence cases, narcotics cases, embezzlement cases, and fraud cases have positive effect on the amount of criminality with R2 of 0,85823 or 85,823%.Keywords : panel regression analysis, crime, Indonesia
Analisis Situasi Pembangunan Manusia di Jawa Tengah Laeli Sugiyono
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.v3i1.39910

Abstract

This study aims to analyze the disclosure distribution of the position regency/city in Central Java based on the linkage of Economic Growth (EG) and Human Development Index (HDI). The study uses secondary data in the form of cross-sectional regional regency/city based on EG and HDI components. Data analysis uses regency/city distribution plot diagram based on EG and HDI components in the Cartesian diagram which divides the space into 4 Quadrants, namely: Quadrant I of the regency/city distribution plots with high EG and HDI, Quadrant II of the regency/city distribution plots with low EG and high HDI, Quadrant III of the regency/city distribution plots with high EG and low HDI, and Quadrant IV of the regency/city distribution plots with low EG and HDI. This study concludes that the position of cities in Central Java in general is in line with the Quadrant I group, the HDI of regency/city in the area of the ex-Semarang and ex-Surakarta residency is in Quadrant I. Other regencies/cities are spread in Quadrant II, III, and IV.Keywords : human development index, economic growth, Central Java, distribution plot 
Deteksi Krisis Keuangan di Indonesia Berdasarkan Indikator Nilai Tukar Riil Menggunakan Model SWARCH (2,3) Sugiyanto Sugiyanto; Etik Zukhronah; Dewi Retnosari
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.v1i1.24082

Abstract

The financial crisis that hit Asia in mid-1997 began with the financial crisis in Thailand which then spread to Indonesia. The impact of the financial crisis in Indonesia is so severe that a crisis detection system is needed. The financial crisis detection system can be done by simple monitoring of macroeconomic indicators such as real exchange rate. Excessive real exchange rate is predicted to have a great chance of crisis.The result shows that the real exchange rate from January 1990 to June 2013 has heteroscedasticity effect and there are structural changes so it can be modeled using SWARCH model (2,3) with ARMA (1.0) as conditional average model and ARCH (3) as model conditional variance. The inferred probabilities value of the SWARCH (2,3) model in February 1998 of 1 and July 1998 of 0.9968 over 0.5 indicates that the period is in a high volatile condition indicating a crisis. The SWARCH model (2.3) based on the real exchange rate indicator was able to capture the high volatile conditions in February 1998 and July 1998 as the impact of the 1997 Asian financial crisis.Keywords : Deteksi, krisis keuangan, nilai tukar riil, SWARCH
Perbandingan Model Cox Proportional Hazard dan Regresi Weibull untuk Menganalisis Ketahanan Bank Syariah Yusrillah Ihza Zianita Afni; Mohamad Fatekurohman; Dian Anggraeni
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.v2i2.33082

Abstract

On July 1, 2014 Financial Services Authority (OJK) issued a new regulation number 8/PJOK.13/2014 concerning the health of general sharia banks that can be valued from several aspects including credit risk, liquidity risk, Return on Asset (ROA), Net of Margin (NOM) and Capital Adequacy Ratio (CAR). The purpose of this study is to compare the models of Cox proportional hazard and Weibull regression for the resistance of sharia bank in 2017-2018 for 24 data. The data were analyzed by describing each variable and modeling in each method. Comparison result shows that Weibull regression model is better than the Cox proportional hazard model because it has smaller AIC and MSE.Keywords : Sharia Bank, Survival Analysis, AIC, MSE
Implementasi Text Mining Pada Analisis Sentimen Pengguna Twitter Terhadap Marketplace di Indonesia Menggunakan Algoritma Support Vector Machine Dyah Auliya Agustina; Sri Subanti; Etik Zukhronah
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.v3i2.44337

Abstract

In this digital era, technology development has changed the behavior of society from buy offline to online. One of this behavioral changes is marked by the growth of global marketplace including in Indonesia. The big marketplaces in Indonesia that have received a lot of public response on social media are Tokopedia, Shopee, and Bukalapak. This research determines the public sentiment toward both the service and issues surrounding these three marketplaces on media social especially Twitter. Public opinion is classified into a positive or negative sentiment. The data used in this study is obtained from Twitter API (Application Programming Interface) using keyword Shopee, Tokopedia, and Bukalapak. Preprocessing texts are divided into five steps: cleansing, case folding, stemming, stopwords, and tokenizing. Training and testing data are divided using k-fold cross validation method, while visualization the characteristic of text is using word cloud. Research shows that public are posting tweet more positive sentiment than negative one. The perfomance of classification shows that the best G-mean and AUC value for Bukalapak testing data are 0.85 and 0.86 in the first fold. While the best G-mean and AUC value for Shopee testing data are 0.76 and 0.77 in the seventh fold and the best G-mean and AUC value for Tokopedia testing data are 0.82 and 0.83 in the sixth fold.Keywords : sentiment analysis, marketplace, support vector machine, twitter
Penerapan Generalized Cross Validation dalam Model Regresi Smoothing Spline pada Produksi Ubi Jalar di Jawa Tengah Trionika Dian Wahyuningsih; Sri Sulistijowati Handajani; Diari Indriati
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.v1i2.26250

Abstract

Sweet Potato is a useful plant as a source carbohydrates, proteins, and is used as an animal feed and ingredient industry. Based on data from the Badan Pusat Statistik (BPS), the production fluctuations of the sweet potato in Central Java from year to year are caused by many factor. The production of sweet potato and the factors that affected it if they are described into a pattern of relationships then they do not have a specific pattern and do not follow a particular distribution, such as harvest area, the allocation of subsidized urea fertilizer, and the allocation of subsidized organic fertilizer. Therefore, the production model of sweet potato could be applied into nonparametric regression model. The approach used for nonparametric regression in this study is smoothing spline regression. The method used in regression smoothing spline is generalized cross validation (GCV). The value of the smoothing parameter (λ) is chosen from the minimum GCV value. The results of the study show that the optimum λ value for the factors of harvest area, urea fertilizer and organic fertilizer are 5.57905e-14, 2.51426e-06, and 3.227217e-13 that they result a minimum GCV i.e 2.29272e-21, 1.38391e-16, and 3.46813e-24. Keywords: Sweet potato; nonparametric; smoothing spline; generalized cross validation.
Back Matter Vol 2 No 1 Hasih 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

Abstract

Back Matter Vol 3 No 1 2020 Hasih Pratiwi
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.v3i1.43193

Abstract

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