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Contact Name
Hasih Pratiwi
Contact Email
hpratiwi@mipa.uns.ac.id
Phone
-
Journal Mail Official
ijas@mipa.uns.ac.id
Editorial Address
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Location
Kota surakarta,
Jawa tengah
INDONESIA
Indonesian Journal of Applied Statistics
ISSN : 2621086X     EISSN : -     DOI : -
Indonesian Journal of Applied Statistics (IJAS) is a journal published by 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 : -
Articles 15 Documents
Penerapan Generalized Cross Validation dalam Model Regresi Smoothing Spline pada Produksi Ubi Jalar di Jawa Tengah Wahyuningsih, Trionika Dian; Handajani, Sri Sulistijowati; Indriati, Diari
Indonesian Journal of Applied Statistics Vol 1, No 2 (2018)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (627.672 KB) | 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.
Pendekatan Regresi Data Panel untuk Pemodelan Jumlah Angkatan Kerja dan Penanaman Modal Luar Negeri terhadap PDRB Provinsi di Indonesia Syukron, Muhammad; Fahri, Hafidz Muhammad
Indonesian Journal of Applied Statistics Vol 1, No 2 (2018)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (775.163 KB) | DOI: 10.13057/ijas.v1i2.26172

Abstract

Indonesia is a country with great economic potency. Indonesia has a vast area and abundant natural products, but until now Indonesia is still a developing country. The Indonesian economy is defeated by other countries such as Japan, China and South Korea even by the neighboring country, Singapore. Increasing the national economy can be started from improving the regional economy which can be measured by gross regional domestic product (GRDP). Indonesia will experience a demographic bonus in 2045 so that the population of productive age is expected to contribute a lot to economic growth. The large number of productive age population must be balanced with the availability of jobs so that this momentum can be fully utilized. Foreign investment can be a solution when domestic capital is insufficient in financing economic activities. In addressing this phenomenon, a statistical analysis of panel data regression was conducted to see the relationship between independent variables, namely the number of labor force and realization of foreign investment, and a dependent variable, namely GRDP at constant prices in 2010 for every province in Indonesia. We use time series data in 2015-2017 and cross-sectional data of 34 provinces in Indonesia taken from BPS official website. The estimation result shows that both independent variables partially and fully have a significant effect on the GRDP with an adjusted R2 of 99.86%. Keywords: Labor force; regression; panel data; foreign capital; GRDP.
Back Matter Pratiwi, Hasih
Indonesian Journal of Applied Statistics Vol 1, No 2 (2018)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (117.599 KB) | DOI: 10.13057/ijas.v1i2.28570

Abstract

Analisis Premi Asuransi Jiwa Menggunakan Model Cox Proportional Hazard Fajarini, Firda Anisa; Fatekurohman, Mohamat
Indonesian Journal of Applied Statistics Vol 1, No 2 (2018)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (939.954 KB) | DOI: 10.13057/ijas.v1i2.25280

Abstract

Cox proportional hazard model is a regression model that is used to see the factors that cause an event. The survival analysis used in this research is the period of time the client is able to pay the life insurance premium using Cox proportional hazard model with Breslow method.The purpose of this research is to know how sex, age, insured money, job, method of payment of premium, premium, and type of product can influence the level of ability of client to make payment of life insurance premium based on customer data from PT. BRI Life Insurance Branch of Jember in 2007.The result of this research is the final model of Cox proportional hazard obtained from several variables which have significant influence with simultaneous and partial significance test is the variable of insured money (X3), variable of payment method of premium (X5), premium variable (X6) , and insurance product variable (X7) . The four variables are said to have a significant effect on the model, so that the final model of Cox proportional hazard is obtained that consists of the parameter estimation (β) value of each variable Keywords : survival analysis; cox proportional hazard model; breslow method; life insurance.
Peramalan Banyaknya Pengunjung Pantai Glagah Menggunakan Metode Autoregressive Integrated Moving Average Exogenous (ARIMAX) dengan Efek Variasi Kalender Intan, Solikhah Novita; Zukhronah, Etik; Wibowo, Supriyadi
Indonesian Journal of Applied Statistics Vol 1, No 2 (2018)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (856.699 KB) | DOI: 10.13057/ijas.v1i2.26298

Abstract

Glagah Beach is one of the tourist destinations in Kulon Progo Regency, Yogyakarta which is the most visited by tourists. Glagah Beach visitors data show  that in the month of Eid Al-Fitr there was a significant increase. This shows that there is an effect of the calendar variation of Eid al-Fitr. Therefore, it is needed a method that can be used to analyze time series data which contains effects of calendar variations, that is ARIMAX method. The aim of this study are to find the best ARIMAX model and to predict the number of visitors to Glagah Beach in the future. The result shows that the best ARIMAX model was ARIMAX([24],0,0). Forecasting from January to September 2016 are 37211, 21306, 26247, 24148, 28402, 29309, 81724, 26029, and 23688 visitors. Keywords: Glagah Beach; variation of calendar; Eid al-Fitr; ARIMAX.
Front Matter Pratiwi, Hasih
Indonesian Journal of Applied Statistics Vol 1, No 2 (2018)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (124.001 KB) | DOI: 10.13057/ijas.v1i2.28568

Abstract

Analisis Ketahanan Hidup Pasien Kanker Paru Menggunakan Regresi Weibull Solehah, Arivatus; Fatekurohman, Mohamat
Indonesian Journal of Applied Statistics Vol 1, No 2 (2018)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (657.934 KB) | 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
Uji Asumsi Proportional Hazard pada Faktor yang Mempengaruhi Waktu Tahan Hidup Pasien Kanker Paru Aditya, Elnatan Dimas; Handajani, Sri Sulistijowati; Setiyowati, Ririn
Indonesian Journal of Applied Statistics Vol 1, No 2 (2018)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (458.292 KB) | DOI: 10.13057/ijas.v1i2.26496

Abstract

Lung cancer is the disease that its death risk always increase, because of that the survival time of its patient is interesting to be researched. One of the method that can be used to research survival time of lung cancer patient is Cox regression. It has an assumption that called proportional hazard assumption. Proportional hazard assumption can be tested by graph method that is log-log graph, but the result is only used as temporary suspicion. For a better result, the goodness of fit test can be used by calculate the correlation between rank of survival time and schoenfeld residual. The result is age variabel doesn’t satisfy proportional hazard assumption. Keywords : cox regression; proportional hazard assumption; log-log graph; goodness of fit test.
Deteksi Krisis Keuangan di Indonesia Berdasarkan Indikator Nilai Tukar Riil Menggunakan Model SWARCH (2,3) Sugiyanto, Sugiyanto; Zukhronah, Etik; Retnosari, Dewi
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
Back Matter Vol 1 No 1 Pratiwi, Hasih
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.v1i1.24686

Abstract

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