Articles

REGRESI TERBOBOTI GEOGRAFIS DENGAN PEMBOBOT KERNEL KUADRAT GANDA UNTUK DATA KEMISKINAN DI KABUPATEN JEMBER Rahmawati, Rita; Djuraidah, Anik
FORUM STATISTIKA DAN KOMPUTASI Vol. 15 No. 2 (2010)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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Abstract

The determination of whether  rural areas are considered  poor or no are usually based on  the average cost per capita with a global analysis that needs independent observations and the results are applied to all villages. But it is very likely that poverty would be influenced by space and neighboring areas, so the data between observations are rarely independent. One of the statistical analysis that encounters this spatial problem is Geographically Weighted Regression (GWR), which  gives different weights to each geographical observation. In this paper, the weighting used for the GWR model is kernel bi-square, with its bandwidth values respectively. Optimal bandwidth can be obtained by minimizing the value of cross validation coefficient (CV). The results showed that the GWR model is more effective than the regression to analyze the data on average expenditure per capita in Jember.
ANALISIS SPASIAL PENGARUH TINGKAT PENGANGGURAN TERHADAP KEMISKINAN DI INDONESIA (STUDI KASUS PROVINSI JAWA TENGAH) Rahmawati, Rita; Safitri, Diah; Fairuzdhiya, Octafinnanda Ummu
MEDIA STATISTIKA Vol 8, No 1 (2015): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

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Abstract

Poverty is still being one of big problems in Indonesia. Any efforts are done to find a solution for this problem. Poverty itself can be caused of the high unemployment that occurs. With a number of unemployment, it will be lower income thus reducing also purchasing power and the ability to meet the needs of life thus causing poverty. This study analyzed the impact of unemployment to the poverty as involving spatial factors, using spatial regression analysis. Used data on poverty and unemployment in each regency in the central java, the analysis shows that based on likelihood ratio test, obtained LR test value 6,038 or p-value 0,014001 which means there is a spatial correlation. By testing model simultaneously nor individually using Breusch-Pagan test and Wald test, it show that both are significant, with BP = 6,7094; df = 1; p-value = 0,009591 and Wald statistic = 7,0238; p-value = 0,0080434. The results means there are spatial element in the relations between unemployment and poverty in central java so that SEM is more proper used than ordinary linear regression. Keywords: Spatial Error Model (SEM), Spatial Autocorrelation, Spatial Heterogeneity
ANALISIS FAKTOR-FAKTOR PRODUKSI PERIKANAN TANGKAP PERAIRAN UMUM DARATAN DI JAWA TENGAH MENGGUNAKAN REGRESI BERGANDA DAN MODEL DURBIN SPASIAL Retnowati, Puji; Rahmawati, Rita; Rusgiyono, Agus
Jurnal Gaussian Vol 6, No 1 (2017): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Abstract

Indonesia?s inland openwater is the second largest in Asia after China. It?s estimated  Indonesia?s inland openwater capture fisheries potential reached 3.034.934 tons per year. Central Java is one of the provinces that have great potential in the field of fisheries. In this study will be discussed about the factors suspected to affect inland openwater capture fisheries production. The method used are multiple regression analysis with maximum likelihood estimation and spatial durbin models. Spatial durbin models is the development of linear regression which location factors are also considered. The results of spatial dependences shows there is spatial dependence in the inland openwater capture fisheries production variable, fisheries establishments variables and the number of boats variable. So spatial durbin models can be used for analysis. In spatial durbin models, variables that significantly influence inland openwater capture fisheries production is the number of fishing gear, the number of boats, and the number of fishing trip with coefficient of determination (R2) of 0,9054. While in the multiple regression analysis showed that the only number of fishing trip variable that significantly, where the value of the coefficient of determination (R2) is 0,857. Thus better spatial durbin models used to analyze inland openwater capture fisheries production, in addition more significant variables also have the coefficient of determination (R2) that is greater than the multiple regression analysis.Keywords: inland openwater capture fisheries production, maximum likelihood, spatial durbin model.
PERAMALAN LAJU INFLASI DAN NILAI TUKAR RUPIAH TERHADAP DOLAR AMERIKA MENGGUNAKAN MODEL VECTOR AUTOREGRESSIVE (VAR) Ichsandi, Fitrian Fariz; Rahmawati, Rita; Wilandari, Yuciana
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Abstract

Vector Autoregressive Method (VAR) is a simultaneous equation model has several endogeneous variables. In the VAR Model each variable endogeneous is explained by lag from own value and lag from the other variable. Equation of VAR generally use to forecast. In this final task VAR model was applied to find the forecasting value of inflation rate in Indonesia and the US dollar exchange rates. Testing in VAR models includes stationarity test, granger causality test and white noise test. Based on the analysis showed that inflation variable and US dollar exchange rates variable are both experiencing differencing first lag so as mentions for both variables become d_inflasi and d_kurs. The best lag for VAR model is lag 3 for each model. Forecasting for 5 periods refers to indicate that inflation rate fluctuated is stable at the average rate 0,33% while the US dollar exchange rates tended to decrease on 4 periode and increase on periode to 5 with an average exchange rate is Rp. 10.018,76.Keywords: inflation, US dollar exchange rates, VAR
PEMODELAN TINGKAT PENGANGGURAN TERBUKA DI JAWA TENGAH MENGGUNAKAN REGRESI SPLINE Utama, Seta Satria; Suparti, Suparti; Rahmawati, Rita
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Abstract

Unemployment is one of the employment problems facing Indonesia. Central Java Province is one of the provinces with a high enough unemployment. The main indicators used to measure the unemployment rate in the labor force that is unemployed. Based on research Arianie (2012) labor force participation rate significantly affect the unemployment rate and based on research Sari (2012) the gross enrollment ratio significantly affects the rate of open unemployment. Therefore, in this study using the two predictor variables with the labor force participation rate as X1 and gross enrollment rate as X2. This study aimed to explore the model of open unemployment rate in the Province of Central Java. The method used is the method of spline regression. Spline regression has the ability to adapt more effectively to the data patterns up or down dramatically with the help of dots knots. Determination of the optimal point knots are very influential in determining the best spline models. The best spline models are models that have a minimum GCV (Generalized Cross Validation) Value. Best spline models for the analysis of the data rate of unemployment in Central Java Province is the spline regression model when order X1 is 2 and order X2 is 4 and large number of knots in the X1 is 1 knot at the point 68.02394 and X2 is 3 knots at the point 82.13, 87.19, and 87.65 with GCV value of 1.732746. Keywords: Rate of  Open Unemployment, Spline Regression, GCV
PEMODELAN VECTOR AUTOREGRESSIVE X (VARX) UNTUK MERAMALKAN JUMLAH UANG BEREDAR DI INDONESIA Rosyidah, Haniatur; Rahmawati, Rita; Prahutama, Alan
Jurnal Gaussian Vol 6, No 3 (2017): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Abstract

The economic stability of a country can be seen from the value of inflation. The money supply in a country will affect the value of inflation, so it is necessary to control the money supply. The money supply in Indonesia consists of currency, quasi money, and securities other than shares. One of the factors affecting the amount of currency, quasi money, and securities other than shares is the SBI interest rate. Time series data from the money supply components are correlated. To explain multiple time series data variables that are correlated we can use the VAR approach. VAR model with the addition of an exogenous variable is called VARX. The purpose of this study is to obtain models to predict the amount of currency, quasi money, securities other than shares using the VARX approach with the SBI interest rate as an exogenous variable. The results of data analysis in this study, the model obtained is VARX (1,1). Based on t test with 5% significance level, SBI interest rate variable has no significant effect to variable of currency amount, amount of quasi money, or amount of securities other than shares. Residual model VARX (1,1) satisfies the white noise assumption, while the normal multivariate assumption is not satisfied. The value of MAPE for currency variables (7,53969%), quasi money (0,49036%), and securities other than shares (9,64245%) indicates that the VARX (1,1) model has excellent forecasting ability that can be used for forecasting future periods. Forecasting results indicate an increase in the amount of currency, quasi money, or securities other than shares in each period..Keywords : Amount of currency, amount of quasi money, amount of securities other than shares, SBI interest rate, VARX, MAPE
ANALISIS INTERVENSI KENAIKAN HARGA BBM TERHADAP PERMINTAAN BBM BERSUBSIDI PADA SPBU SULTAN AGUNG SEMARANG JAWA TENGAH Ahmad, Fandi; Rahmawati, Rita; Safitri, Diah
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Abstract

Fuel consumption is always interesting to study, in addition to the use of which is used by all the community but also because of the critical role of fuel as an indicator to determine the price of other staples. Not surprisingly, changes in fuel prices polemical definitely interesting to study. In this subject specifically on the impact of the fuel price hike subsidized fuel demand. Changes in fuel price (hike) will have an impact on people's behavior in anticipation of the event. Most people will take the step to buy fuel in bulk prior to the date of determination of the increase in fuel prices, resulting in a surge in demand for fuel. Intervention model is a time series model that can be used to model and predict the data containing the intervention of external factors. In the intervention model, there are two functions, namely the step and pulse functions. Step function is a form of intervention that occurs within a long period of time while the pulse function is a form of intervention that occurs only within a certain time. Based on the analysis suggests that the impact of the use of gasoline and diesel at the pump Sultan Agung Semarang wear both pulse function because the impact was immediate and occur only in a short time                                                                                                                                      Keywords: subsidized BBM, time series, intervention models, pulse function, step function
PEMODELAN JUMLAH UANG BEREDAR MENGGUNAKAN PARTIAL LEAST SQUARES REGRESSION (PLSR) DENGAN ALGORITMA NIPALS (NONLINEAR ITERATIVE PARTIAL LEAST SQUARES) Ikadianti, Riana; Rahmawati, Rita; Rusgiyono, Agus
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Abstract

Money supply has a tendency to increase or decrease the price level. Because of it, it is important to do a restraint and control action on money supply through its affecting factors include net foreign assets, net claims on central government, claims on region government, claims on the other finances institution, claims on nonfinances enterprise of state-owned corporation, and claims on private sector. In this study, a model has done between money supply and its affecting factors using Partial Least Squares Regression (PLSR) with NIPALS (Nonlinear Iterative Partial Least Squares) algorithm because the affecting factors of money supply data is detected multicollinearity. In the PLSR, regression coefficient is obtained iteratively. Three stage iteration process in PLSR produce weight vector, loading vector, and parameter estimation that produce PRESS and R2 values later. Based on the analysis, PLSR model to the money supply data in July 2012 until December 2014 is obtained at the fourth iteration with minimum PRESS value as 2,10815x1010. That PLSR model has R2 value as 99,47%, so it is very good for explaining the money supply. By means of bootstrap technique, concluded that all of the affecting factors of money supply on PLSR model influence money supply significantly. Keywords: money supply, multicollinearity, PLSR, NIPALS
PERBANDINGAN REGRESI KOMPONEN UTAMA DENGAN REGRESI KUADRAT TERKECIL PARSIAL PADA INDEKS PEMBANGUNAN MANUSIA PROVINSI JAWA TIMUR Sinaga, Vetranella .T.R.A.; Safitri, Diah; Rahmawati, Rita
Jurnal Gaussian Vol 8, No 4 (2019): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Abstract

The multiple regression classic assumptions are used to give linear unbiased and minimum variance estimator. In Human Development Index (HDI) and influencing factors in East Java, there are two variables with VIF more than 10 so the assumption of non-multicollinearity is not fulfilled. Principal component regression (PCR) and partial least squares regression (PLS-R) can solve this problem. By doing principal component analysis, there are two linear combinations to take as the new   independent variables which are free from collinearity. In the PLS-R, NIPALS algorithm is used to calculate the components and other structures and to estimate the parameter. While in PCR all independent variables are significant, the percentage of households with drinking water is feasibles is not significant in the model. PLS-R?s  is 95,85% is greater than PCR?s  = 93,42%. PCR?s PRESS = 81,78 is greater than PLS-R?s PRESS = 61,0595.Keywords: Human Development Index (HDI), Multicollinearity, Principal Component Regression, Partial Least Squares Regression, , PRESS
PEMODELAN INDEKS HARGA SAHAM GABUNGAN MENGGUNAKAN REGRESI SPLINE MULTIVARIABEL Afa, Ihdayani Banun; Suparti, Suparti; Rahmawati, Rita
Jurnal Gaussian Vol 7, No 3 (2018): Jurnal Gaussian
Publisher : Departemen Statistika FSM Undip

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Abstract

The Composite Stock Price Index (CSPI) is a composite index of all types of shares listed on the stock exchange and their movements indicate the conditions occurring in the stock market. CSPI movement is an important indicator for investors to determine whether they will sell, hold, or buy a stock. One of the factors that influence the movement of CSPI is Inflation (X1), Exchange Rate (X2) and SBI rate (X3). This study aims to obtain the best CSPI model using a multivariable nonparametric spline regression approach. The approach is done by nonparametric regression because the regression curve obtained does not show a certain relationship pattern. Spline is very dependent on the order and location of the knot point. The best spline model is the model that has the minimum MSE (Mean Square Error) value. In this study, the best spline regression model is when X1 is 4 order, X2 is 2 order and X3 is 2 order. The number of knots on X1 is 1 knot at 8.22, X2 is 2 knots at 13066.82 and 13781.75 While X3 is 2 knots at 6.6 and 6.67 with value of MSE equal to 6686.85.Keywords: Composite Stock Price Index, Multivariable Spline Regression, MSE
Co-Authors - Siswandari Abd. Rahman, Ika Marlina Abdul Hoyyi Abdur Rofiq, Abdur Afa, Ihdayani Banun Agung Santoso, Agung Agus Rusgiyono Agus Setiawan Agustifa Zea Tazliqoh Agustini Agustini, Agustini Alan Prahutama Aldila Abid Awali Alfahari Anggoro, Alfahari Allima Stefiana Insani Amri, Chairul Amri, Chairul Anggita Puri Savitri, Anggita Puri Anggraini Susanti Kusumawardani Anik Djuraidah Anton Suhartono, Anton Apriliyani, Neng Virly Apriliyani, Neng Virly Asep Yoyo Wardaya Asmuni Hayat Aulia Ikhsan Betha Noranita Bhinekawati, Henny Budi Warsito Chrysmandini Pulung Gumauti, Chrysmandini Pulung Chusen, Muchammad Aziz Chyntia Arum Widyastusti, Chyntia Arum Daniyati, Dian Dedy Douglas Harianja, Dedy Douglas Denny Hernawan, Denny Destiyani, Eka Dewi, Amalina Sari Di Asih I Maruddani Diah Safitri Dian E Idris Gentini Dina Rosmalia Listya Utami Dudung Darusman Dwi Ispriyanti Ebeit Devita Simatupang Eka Lestari Eko Adi Sarwoko Elvia Ivada Erfan Sofha, Erfan Esti Zaduqisti Fajar Heru Setiawan, Fajar Heru Fandi Ahmad Fathia, Annisa Nur Fikri, Aan Maudlihul Firda Megawati, Firda Firmansyah, Rafiek Firmansyah, Rafiek Fitrian Fariz Ichsandi Ginung Pratidina Gustomi, Mono Pratiko Hafii Risalam, Hafii Halawi, Dea Hilmiah Halawi, Dea Hilmiah Hanien Nia H Shega Hasbi Yasin Husen, Sadam Husen, Sadam Ikha Rizky Ramadani Indra Rukmana, Indra Indria Tsani Hazhiah Kartono Kartono Kristina, Lulu Kristina, Lulu Lesmana, Wira Lesmana, Wira Lies Kurnia Irwanti Luthfie, Muhammad M. Muslih Husein Maharani Febriana Putri, Maharani Febriana Marinda. W, Vuvud Marinda. W, Vuvud Maslachah, Maslachah Maulana, Irvan Maulana, Irvan Mega Susilowati, Mega Melati Puspa Nur Fadlilah, Melati Puspa Nur Moch. Abdul Mukid Mohammad Yahya Mooy, Marthin Nosry Muhammad Abid Muhyidin Muhammad Hilman Rizki Abdullah, Muhammad Hilman Rizki Muhammad Yusuf Muhimmi, Aliyatul Mumaiyizah, Mumaiyizah Munispa, Siti Munispa, Siti Mustafid Mustafid Mutiara Ardin Rifkiani, Mutiara Ardin Nabila, Eva Salsa Nariswari Diwangkari, Nariswari Nerustia, Arinda Novpika Nerustia, Arinda Novpika Niken Anggraini Dewi Novian Trianggara, Novian Novie Eriska Aritonang, Novie Eriska Nurhikmah Megawati Nuril Faiz Nurmila, Samhatul Nurmila, Samhatul Octafinnanda Ummu Fairuzdhiya Onny Kartika Hitasari, Onny Kartika Pangestikasari, Merinda Pitaloka, Riski Arum Pratama Ganang Widayaka, Pratama Ganang Purnamasari, Irma Purnamasari, Irma Rahayu Ningtyas Ramadhani, Alika Retnowati, Puji Riana Ikadianti, Riana Rifki Adi Pamungkas, Rifki Adi Rindayati, Rindayati Riyan Eko Putri Rizki Taher Dwi Kurniawati, Rizki Taher Dwi Robertus Heri Sulistyo Roestamy, Martin Rohalidyawati, Windy Rohimat, Dadan Rohimat, Dadan Ronny Gusnadi, Ronny Rosyadi, Hanang Rosyidah, Haniatur Rukun Santoso Sa'adah, Farda Nur Sabhariyah, Riesmiati Salbiah, Euis Salbiah, Euis Santoso2, Rukun Sektiono, Djoyo Sensiani, Sensiani Seran, G. Goris Seran, G. Goris seran, goris seran, M.YGG Seran, M.YGG Seta Satria Utama Shinta Dewi Rismawati Siburian, Jeffri Nelwin J. O. Sinaga, Vetranella .T.R.A. Sirojuddin, Wawan Siti Nur Qomariah, Siti Nur Sudarno Sudarno Sugito Sugito Suhartini, Arianti Suherman, Fitria Aprilia Suherman, Fitria Aprilia Sukanianto, Eko Adyan Sukarelawati, Sukarelawati Sukarelawati, Sukarelawati Suparti Suparti Susanti, Mey Suwanto Suwanto Syah, Hengky Firman Syaiful, Yuanita Tarno Tarno Tatik Widiharih Tri W., Vian Sigit Triana Sofiani Triastuti Wuryandari Tyas, Mutik Dian Prabaning Ula, Fashihatul Utami, Irenda Putri Utami, Irenda Putri Vica Nurani, Vica Wigati, Ekky Rosita Singgih Wilis Ardiana Pradana, Wilis Ardiana Yohanes Mote Yuciana Wilandari Yunisa Ratna Resti, Yunisa Ratna Zahroh, Roihatul