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Hasih Pratiwi
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hpratiwi@mipa.uns.ac.id
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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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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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Peramalan Banyak Pengunjung Pantai Pandasimo Bantul Menggunakan Regresi Runtun Waktu dan Seasonal Autoregressive Integrated Moving Average Exogenous Tito Tatag Prakoso; Etik Zukhronah; Hasih Pratiwi
Indonesian Journal of Applied Statistics Vol 4, No 1 (2021)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v4i1.45795

Abstract

Forecasting is a ways to predict what will happen in the future based on the data in the past. Data on the number of visitors in Pandansimo beach are time series data. The pattern of the number of visitors in Pandansimo beach is influenced by holidays, so it looks like having a seasonal pattern. The majority of Indonesian citizens are Muslim who celebrate Eid Al-Fitr in every year. The determination of Eid Al-Fitr does not follow the Gregorian calendar, but based on the Lunar calendar. The variation of the calendar is about the determination of Eid Al-Fitr which usually changed in the Gregorian calendar, because in the Gregorian calendar, Eid Al-Fitr day will advance one month in every three years. Data that contain seasonal and calendar variations can be analyzed using time series regression and Seasonal Autoregressive Integrated Moving Average Exogenous  (SARIMAX) models. The aims of this study are to obtain a better model between time series regression and SARIMAX and to forecast the number of Pandansimo beach visitors using a better model. The result of this study indicates that the time series regression model is a better model. The forecasting from January to December 2018 in succession are 13255, 6674, 8643, 7639, 13255, 8713, 22635, 13255, 13255, 9590, 8549, 13255 visitors.Keywords: time series regression, seasonal, calendar variations, SARIMAX, forecasting
Structural Equation Modeling (SEM) untuk Mengukur Pengaruh Pelayanan, Harga, dan Keselamatan terhadap Tingkat Kepuasan Pengguna Jasa Angkutan Umum Selama Pandemi Covid-19 di Kota Ambon Zakheus Putlely; Yopi Andry Lesnussa; Abraham Z Wattimena; Muhammad Yahya Matdoan
Indonesian Journal of Applied Statistics Vol 4, No 1 (2021)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v4i1.45784

Abstract

Structural Equation Modeling (SEM) is a statistical analysis technique used to build and test statistical models in the form of causal models. Large-Scale Social Restrictions (PSBB) are government policies to break the chain of spreading the corona virus (Covid-19). This policy certainly has an impact on drivers of public transport services. This research shows that the passengers are very satisfied with the travel safety factor. Meanwhile, service factors and passenger public transport fares are in the satisfied category. Furthermore, the variable service quality (MP), the price of public transportation (H), and passenger safety (KP) have an influence on passenger satisfaction. Because the t-value is greater than 1.96 (for the real level of 5%). The influence of service quality, price and safety variables on passenger satisfaction is 78.1%, the remaining 21.9% is influenced by other variables outside the research.Keywords: covid-19, structural equation modeling, satisfaction.
Front Matter Vol 4 No 1 Hasih Pratiwi
Indonesian Journal of Applied Statistics Vol 4, No 1 (2021)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v4i1.51602

Abstract

Comparison of Random Forest, Logistic Regression, and MultilayerPerceptron Methods on Classification of Bank Customer Account Closure Husna Afanyn Khoirunissa; Amanda Rizky Widyaningrum; Annisa Priliya Ayu Maharani
Indonesian Journal of Applied Statistics Vol 4, No 1 (2021)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v4i1.41461

Abstract

The Bank is a business entity that is dealing with money, accepting deposits from customers, providing funds for each withdrawal, billing checks on the customer's orders, giving credit and or embedding the excess deposits until required for repayment. The purpose of this research is to determine the influence of age, gender, country, customer credit score, number of bank products used by the customer, and the activation of the bank members in the decision to choose to continue using the bank account that he has retained or closed the bank account. The data in this research used 10,000 respondents originating from France, Spain, and Germany. The method used is data mining with early stage preprocessing to clean data from outlier and missing value and feature selection to select important attributes. Then perform the classification using three methods, which are Random Forest, Logistic Regression, and Multilayer Perceptron. The results of this research showed that the model with Multilayer Perceptron method with 10 folds Cross Validation is the best model with 85.5373% accuracy.Keywords: bank customer, random forest, logistic regression, multilayer perceptron
Front Matter Vol 4 No 2 2021 Hasih Pratiwi
Indonesian Journal of Applied Statistics Vol 4, No 2 (2021)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v4i2.56839

Abstract

Pemodelan Determinan Pernikahan Dini di Daerah Pedesaan dengan Pendekatan Regresi Logistik Biner Aloysius Bela Boro; Siskarossa Ika Oktora
Indonesian Journal of Applied Statistics Vol 4, No 2 (2021)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v4i2.46865

Abstract

Abstract. The behavior of early marriage in Indonesia is still high and most prevalent in rural areas. In addition to violating the law, a marriage performed before reaching 19 years also has many negative effects. One of them is the death of the mother and the baby. Using data from the Demographic and Health Survey 2017, this study aims to analyze the determinants of early marriages in rural areas in Indonesia. The response variable used is binary categorical data, namely the status of early marriage and not early marriage, so we use a binary logistic regression. The steps performed on this model include estimates of parameters, parameter testing either simultaneously or partially, and a test of the goodness of fit. The results show that the variables of education level, internet access, and wealth index significantly affected early marriage status in rural areas in Indonesia in 2017. Based on the goodness of fit result, this model is proper for modeling early marriage behavior in Indonesia. The study results can be used as a reference for the government in formulating policies to overcome the problem of early marriage in rural areas in Indonesia. Keywords: early marriage, rural area, categorical response variable, binary logistic regression
Back Matter Vol 4 No 2 2021 Hasih Pratiwi
Indonesian Journal of Applied Statistics Vol 4, No 2 (2021)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v4i2.56840

Abstract

Peramalan Data Inflow dan Outflow Uang Kartal Bank Indonesia Provinsi DKI Jakarta Menggunakan Model ARIMAX dan SARIMAX Atika Amalia; Etik Zukhronah; Sri Subanti
Indonesian Journal of Applied Statistics Vol 4, No 2 (2021)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v4i2.45673

Abstract

Abstract. DKI Jakarta Province plays a crucial role as the center of government and economy in Indonesia. The description of currency inflows and outflows is highly required before Bank Indonesia formulates the appropriate policies to control the circulation of money. The monthly data of currency inflow and outflow of Bank Indonesia of DKI Jakarta show a significant increase in each year particularly before, during, and after Eid al-Fitr. The determination of Eid al-Fitr does not follow the Gregorian calendar but based on the Islamic calendar. The difference in the use of the Gregorian and Islamic calendars in a time series causes a calendar variation. Thus, the determination of Eid al-Fitr in the Gregorian calendar changes as it goes forward eleven days each year or one month every three years. This study aims to obtain the best model and forecast currency inflows and outflows of Bank Indonesia DKI Jakarta using the ARIMAX and SARIMAX models. The study used in-sample data from January 2009 to December 2018 and out-sample data from January to October 2019. The best model was selected based on the smallest out-sample MAPE value. The result showed that the best forecasting model of inflow was ARIMAX (1,0,1). Meanwhile, the best forecasting model for outflow was SARIMAX (2,0,1)(0,0,1)12.Keywords: ARIMAX, calendar variation, forecasting, SARIMAX
Application of Analytic Hierarchy Process and Weighted Product Methods in Determining the Best Employees Sri Harjanto; Setiyowati Setiyowati; Retno Tri Vulandari
Indonesian Journal of Applied Statistics Vol 4, No 2 (2021)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v4i2.44059

Abstract

Abstract. Employees are one of the company's assets that must be managed properly. Therefore the selection of the best employees is now needed. The problem faced in determining the best and qualified employees is that there are still no standards in assessing only one person subjectively in determining the best employee, which consequently lacks appropriate or objective results. To provide rewards for the best employees, we need a system to support the decisions of the best employees who deserve to receive rewards to be on target. The purpose of this research is to design and build a decision support system application in determining the best employees using the analytic hierarchy process and weighted product methods. Stages of software development of the Software Development Life Cycle (SDLC) uses a waterfall, that is data analysis, system design, construction, coding, testing and implementation. The results of this process are in the form of calculation applications that have been obtained from the analytic hierarchy process and weighted product methods in determining the best employee. The result gives an accuracy rate of 82.3%.Keywords: analytic hierarchy process, weighted product, decision support system, employees
Early Detection of South Korean Financial Crisis using MS-GARCH Based on Term of Trade Indicator Husna Afanyn Khoirunissa; Sugiyanto Sugiyanto; Sri Subanti
Indonesian Journal of Applied Statistics Vol 4, No 2 (2021)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v4i2.49169

Abstract

Abstract. The 1997 Asian financial crisis, which occurred until 1998, had a significant impact on the economies of Asian countries, including South Korea. The crisis brought down the South Korean currency quickly and sent the economy into sudden decline. Because the impact of the financial crisis was severe and sudden, South Korean requires a system which able to sight crisis signals, therefore that, the crisis will be fended off. One in all the indicators that can detect the financial crisis signals is that the term of trade indicator which has high fluctuation and change in the exchange rate regime. The mixture of Markov Switching and volatility models, Generalized Autoregressive Conditional Heteroscedasticity (GARCH), or MS-GARCH could explain the crisis. The MS-GARCH model was built using data from the South Korean term of trade indicator during January 1990 until March 2020. The findings obtained in this research can be inferred that the best model of the term of trade is MS-GARCH (2,1,1). Term of trade indicator on that model could explain the Asian monetary crisis in 1997 and also the global monetary crisis in 2008. The smoothed probability of term of trade indicators predicts in April till December 2020 period, there will be no signs of the monetary crisis in South Korea.Keywords: financial crisis, MS-GARCH, South Korea, term of trade indicator

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