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"Vol 13, No 1 (2020): Media Statistika"
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<![CDATA[ESTIMASI SELANG KEPERCAYAAN NILAI UJIAN NASIONAL BERBASIS KOMPETENSI BERDASARKAN MODEL REGRESI SEMIPARAMETRIK MULTIRESPON TRUNCATED SPLINE ]]>
<![CDATA[Lilik Hidayati]]>;
<![CDATA[Nur Chamidah]]>;
<![CDATA[I Nyoman Budiantara]]>
<![CDATA[ MEDIA STATISTIKA Vol 13, No 1 (2020): Media Statistika ]]>
Publisher : <![CDATA[Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro ]]>
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DOI: 10.14710/medstat.13.1.92-103
<![CDATA[Confidence interval estimation is important in statistical inference for the parameters of the regression model, but the theory of confidence interval estimation for multi-response semiparametric regression model parameters based on the truncated spline estimator has not been examined. In this study, we estimate the confidence interval of the multi-response semiparametric regression model based on the truncated spline estimator by using pivotal quantity method with the central limit theorem approach. This confidence interval theory is applied to data of competency-based national exam (UNBK) scores in West Nusa Tenggara Province where its UNBK in the lowest position among other provinces in Indonesia. The method used for estimating parameters is weighted least square. The best model is determined based on the Generalized Cross Validation (GCV) minimum value. Based on the estimated 95% confidence interval of parameters of the multi-response truncated spline semiparametric regression model, the results showed that the insignificant factors affecting the UNBK scores were gender and parental education duration while the report card of scores and USBK scores had a positive effect on the UNBK scores but only the UNBK scores of mathematics that report card of scores factor has a negative effect on it.]]>
<![CDATA[INTERPOLASI KRIGING DALAM PEMODELAN GSTAR-SUR DAN GSTARX-SUR PADA SERANGAN HAMA PENGGEREK BUAH KOPI ]]>
<![CDATA[Henny Pramoedyo]]>;
<![CDATA[Arif Ashari]]>;
<![CDATA[Alfi Fadliana]]>
<![CDATA[ MEDIA STATISTIKA Vol 13, No 1 (2020): Media Statistika ]]>
Publisher : <![CDATA[Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro ]]>
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DOI: 10.14710/medstat.13.1.25-35
<![CDATA[The GSTAR and GSTARX models with the SUR approach normally can only be used in forecasting an event in the future in locations where the data is indeed used in forming the model. The problem that sometimes occurs in some cases is that not all locations that want to be modeled do not have data, or if there is data, the data is not as complete as other locations. This study uses GSTAR and GSTARX modeling with the SUR approach and combines them with the kriging interpolation technique in forecasting in an unobserved location. The case study used in this research is PBKo attack forecasting in Probolinggo Regency, where it is simulated that Watupanjang Village is an unobserved location because the location of coffee plantations in the area is difficult to reach due to difficult terrain / access roads. The results showed that PBKo pest attacks in the Probolinggo Regency could be predicted using the GSTAR model (1, [1,12]) and the GSTARX model (1, [1.12]) (10,0,0). Both models, both GSTAR Kriging and GSTARX Kriging, can be relied upon as an alternative to predicting PBKo pests in unobserved locations or where insufficient data are available.]]>
<![CDATA[COMPARISON OF ARIMA, TRANSFER FUNCTION AND VAR MODELS FOR FORECASTING CPI, STOCK PRICES, AND INDONESIAN EXCHANGE RATE: ACCURACY VS. EXPLAINABILITY ]]>
<![CDATA[Taly Purwa]]>;
<![CDATA[Ulin Nafngiyana]]>;
<![CDATA[Suhartono Suhartono]]>
<![CDATA[ MEDIA STATISTIKA Vol 13, No 1 (2020): Media Statistika ]]>
Publisher : <![CDATA[Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro ]]>
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DOI: 10.14710/medstat.13.1.1-12
<![CDATA[The Consumer Price Index (CPI), stock prices and the rupiah exchange rate to the US dollar are important macroeconomic variables which their movements show the economic performance and can affect the monetary and fiscal policies of Indonesia. This makes forecasting effort of these variables become important for policy planning. While many previous studies only focus on examining the effect among macroeconomic variables, this study uses ARIMA (univariate method), transfer function and VAR (multivariate methods) to measure the forecasting accuracy and also observing the effect between these macroeconomic variables. The results showed that the multivariate methods gave better explanation about the relationship between variables than the simple one. Otherwise, the results of accuracy comparison showed that the multivariate methods did not always yield better forecast than the simple one, and these conditions in line with the results and conclusions of M3 and M4 competition.]]>
<![CDATA[PERSAMAAN DIFERENSIAL ORNSTEIN-UHLENBECK DALAM PERAMALAN HARGA SAHAM ]]>
<![CDATA[Amam Taufiq Hidayat]]>;
<![CDATA[Subanar Subanar]]>
<![CDATA[ MEDIA STATISTIKA Vol 13, No 1 (2020): Media Statistika ]]>
Publisher : <![CDATA[Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro ]]>
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DOI: 10.14710/medstat.13.1.60-67
<![CDATA[Geometric Brownian motion is one of the most widely used stock price model. One of the assumptions that is filled with stock return volatility is constant. Gamma Ornstein-Uhlenbeck process a model to describe volatility in finance. Additionally, Gamma Ornstein-Uhlenbeck process driven by Background Driving Levy Process (BDLP) compound Poisson process and the marginal law of volatility follows a Gamma distribution. Barndorff-Nielsen and Shepard (BNS) Gamma Ornstein-Uhlenbeck model can to sample the process for the stock price with volatility follows Gamma Ornstein-Uhlenbeck process. Based on these, the simulation result are compared BNS Gamma Ornstein-Uhlenbeck model with geometric Brown motion for Standard and Poor (SP) 500 stock data. Simulation result give BNS Gamma Ornstein-Uhlenbeck model and Geometric Brownian motion a Root Mean Square Error (RMSE) are 0,13 and 0,24 respectively. These result indicate that the BNS Gamma Ornstein-Uhlenbeck model gives a more accurate than Geometric Brownian motion]]>
<![CDATA[SPILLOVER EFFECT INFLASI DAGING SAPI ANTAR KOTA: APLIKASI METODE BEKK-GARCH UNTUK JAKARTA, SALATIGA, DAN SURABAYA ]]>
<![CDATA[Ribut Nurul Tri Wahyuni]]>;
<![CDATA[Nasrudin Nasrudin]]>
<![CDATA[ MEDIA STATISTIKA Vol 13, No 1 (2020): Media Statistika ]]>
Publisher : <![CDATA[Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro ]]>
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DOI: 10.14710/medstat.13.1.80-91
<![CDATA[Beef consumption in Indonesia tends to increase and its price fluctuates. In addition to internal factors, the volatility of beef inflation can also be influenced by other regions (spillover effect). Using BEKK-GARCH model, we try to show spillover effect the volatility of beef inflation in Jakarta, Salatiga, and Surabaya. The transmissions of news effects occur from Jakarta and Surabaya to Salatiga and from Jakarta and Salatiga to Surabaya. Transmission of two-way volatility occurs between Jakarta and Surabaya. Furthermore, the transmission of one-way volatility occurrs from Jakarta to Salatiga. Price fluctuation in consumer areas will be followed by price fluctuation in other consumer areas and producer areas. Therefore, controlling beef inflation should be began from consumer areas.]]>
<![CDATA[PENGELOMPOKAN RUMAH TANGGA DI INDONESIA BERDASARKAN PENDAPATAN PER KAPITA DENGAN MODEL FINITE MIXTURE ]]>
<![CDATA[Irwan Susanto]]>;
<![CDATA[Sri Sulistijowati Handajani]]>
<![CDATA[ MEDIA STATISTIKA Vol 13, No 1 (2020): Media Statistika ]]>
Publisher : <![CDATA[Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro ]]>
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DOI: 10.14710/medstat.13.1.13-24
<![CDATA[In the statistical modeling framework, the form of the income distribution can be approaching based on certain statistical distributions. The use of the finite mixture model is relatively flexible in the modeling of the income distribution that has a multimodal pattern. The multimodal pattern can be indicated as the existence of different cluster on the data. The different clusters which can reflect the economic homogeneity of income are represented by the mixture components of the finite mixture model. In this paper, the finite mixture model is implemented for modeling the distribution of household income per capita in Indonesia based on The Fifth Wave of the Indonesia Family Life Survey (IFLS5) 2014-2015. The mixture components of the finite mixture model have been build based on the heavy-tailed statistical distributions, i.e., gamma, lognormal, and Weibull distributions. The estimation of the fitting finite mixture model was conducted using the maximum-likelihood estimation method through the expectation-maximization (EM) algorithm. The suitable finite mixture models were verified with the bootstrap likelihood ratio statistics test, Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). Based on the results, the distribution of household income per capita in Indonesia can be modeled by the four components-lognormal mixture model.]]>
<![CDATA[APLIKASI ERROR CORRECTION MECHANISM DALAM ANALISIS DAMPAK PERTUMBUHAN EKONOMI, KONSUMSI ENERGI DAN PERDAGANGAN INTERNASIONAL TERHADAP EMISI CO2 DI INDONESIA ]]>
<![CDATA[Fitri Kartiasih]]>;
<![CDATA[Adi Setiawan]]>
<![CDATA[ MEDIA STATISTIKA Vol 13, No 1 (2020): Media Statistika ]]>
Publisher : <![CDATA[Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro ]]>
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DOI: 10.14710/medstat.13.1.104-115
<![CDATA[Economic development is an effort to improve people's lives. However, economic development has negative externalities. Emissions generated from economic activities can pollute the environment. This study purpose to determine the relationship between economic growth and CO2 emissions based on the Environment Kuznets Curve (EKC) hypothesis and analyze the influence of energy use, economic growth and international trade on CO2 emissions in Indonesia in the period 1977-2014 using Error Correction Mechanism (ECM) analysis. The results showed that the EKC hypothesis does not apply in Indonesia, meaning that economic development carried out during the research period still pursues increased income without regard to environmental quality so that increased per capita income is accompanied by increase in CO2 emissions. Based on econometric analysis of ECM, it shows that the variables of energy use, economic growth and international trade have a statistically significant effect on CO2 emissions in Indonesia in the long run. In the short term, economic growth, and error correction terms have a statistically significant effect while the variables of energy consumption and international trade do not have a statistical effect on CO2 emissions in Indonesia.]]>
<![CDATA[ANALISIS CURAH HUJAN BULANAN DI KOTA AMBON MENGGUNAKAN MODEL HETEROSKEDASTISITAS: SARIMA-GARCH ]]>
<![CDATA[Lexy Janzen Sinay]]>;
<![CDATA[Ferry Kondo Lembang]]>;
<![CDATA[Salmon Notje Aulele]]>;
<![CDATA[Dominique Mustamu]]>
<![CDATA[ MEDIA STATISTIKA Vol 13, No 1 (2020): Media Statistika ]]>
Publisher : <![CDATA[Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro ]]>
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DOI: 10.14710/medstat.13.1.68-79
<![CDATA[Non-linear characteritics in rainfall allow volatility clustering. This condition occurs in Ambon City with seasonal rainfall patterns. The aims of this research are to find the best model and to forecast monthly rainfall in Ambon City using heteroscedasticity model. This research examines secondary data from BMKG for monthly rainfall data in Ambon City from January 2005 – December 2018. The data is divided into two parts. First part, is called in-sample data, consist of data form January 2005 – December 2017. Second part, is called out-sample data, consist data from Januari 2018 – December 2018. The research used SARIMA–GARCH to model the data. The results are the is the best model and the residual model satisfied assumptions of normality, white noise, and there is no ARCH effect. The MAPE value in simulation using in-sample data is 0.73%. On the other side, the MAPE value of forecast results is 30%.]]>
<![CDATA[[RETRACTED] COMBINATION OF SYNTHETIC MINORITY OVERSAMPLING TECHNIQUE (SMOTE) AND BACKPROPAGATION NEURAL NETWORK TO CONTRACEPTIVE IUD PREDICTION ]]>
<![CDATA[Mustaqim Mustaqim]]>;
<![CDATA[Budi Warsito]]>;
<![CDATA[Bayu Surarso]]>
<![CDATA[ MEDIA STATISTIKA Vol 13, No 1 (2020): Media Statistika ]]>
Publisher : <![CDATA[Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro ]]>
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DOI: 10.14710/medstat.13.1.36-46
<![CDATA[[RETRACTED] Data imbalance occurs when the amount of data in a class is more than other data. The majority class is more data, while the minority class is fewer. Imbalance class will decrease the performance of the classification algorithm. Data on IUD contraceptive use is imbalanced data. National IUD failure in 2018 was 959 or 3.5% from 27.400 users. Synthetic minority oversampling technique (SMOTE) is used to balance data on IUD failure. Balanced data is then predicted with neural networks. The system is for predicting someone when using IUD whether they have a pregnancy or not. This study uses 250 data with 235 major data (not pregnant) and 15 minor data (pregnant). From 250 data divided into two parts, 225 training and 25 testing data. Minority class on training data will be duplicated to 1524%, so that the amount of minority data become balanced with the majority data. The results of predictive with an accuracy rate of 99.9% at 1000 epoch.]]>
<![CDATA[PERAMALAN LANGSUNG DAN TIDAK LANGSUNG MARKET SHARE MOBIL MENGGUNAKAN ARIMAX DENGAN EFEK VARIASI KALENDER ]]>
<![CDATA[Dea Astri Titi]]>;
<![CDATA[Heri Kuswanto]]>;
<![CDATA[Suhartono Suhartono]]>
<![CDATA[ MEDIA STATISTIKA Vol 13, No 1 (2020): Media Statistika ]]>
Publisher : <![CDATA[Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro ]]>
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DOI: 10.14710/medstat.13.1.47-59
<![CDATA[Based on BPS data, the transportation industry sector contributed to about 8.01% of Indonesia's economic growth. The rapid growth of the transportation industry is also followed by the development of the automotive industry in Indonesia. The Exclusive Lisencee Agent of the Astra International group won a market share of 57% in April 2017. PT. Astra Daihatsu Motor, which is one of its subsidiaries, has a very rapid sales increase of 15% every year until Daihatsu's market share rises to 17.3%. Data from the Gabungan Industri Kendaraan Bermotor Indonesia (Gaikindo) shows an upward trend in car sales a month before Idul Fitri. This study carried out Daihatsu's direct and indirect market share forecasting using ARIMAX with a variety of calendar effects consisting of trends, monthly seasonal effects and Idul Fitri effects. The results indicated that indirect forecasting through forecasting the car sales for each brand and total market using ARIMAX outperforms the others and is able to capture the pattern of the testing data. The resulting SMAPE value of ARIMAX is smaller than direct forecasting and indirect forecasting using ARIMA.]]>
