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All Journal Media Statistika MATEMATIKA SAINS DAN MATEMATIKA Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang
Agus Rusgiyono
Departemen Statistika, Fakultas Sains Dan Matematika, Universitas Diponegoro
Decision Sciences, Operations Research & Management Mathematics Other

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GEOGRAPHICALLY WEIGHTED PANEL REGRESSION WITH FIXED EFFECT FOR MODELING THE NUMBER OF INFANT MORTALITY IN CENTRAL JAVA, INDONESIA Rusgiyono, Agus; Prahutama, Alan
MEDIA STATISTIKA Vol 14, No 1 (2021): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.14.1.10-20

Abstract

One of the regression methods used to model by region is Geographically Weighted Regression (GWR). The GWR model developed to model panel data is Geographically Weighted Panel Regression (GWPR). Panel data has several advantages compared to cross-section or time-series data. The development of the GWPR model in this study uses the Fixed Effect model. It is used to model the number of infant mortality in Central Java. In this study, the weighting used by the fixed bisquare kernel resulted in a significant variable percentage of clean and healthy households. The value of R-square is 67.6%. Also in this paper completed by spread map base on GWPR model.
PEMODELAN VECTOR AUTOREGRESIVE EXOGENOUS (VARX) PADA NILAI INFLASI TERHADAP PDRB DI JAWA TENGAH Alan Prahutama; Agus Rusgiyono; Tiani Wahyu Utami
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 7, No 2 (2019): Jurnal Statistika
Publisher : Program Studi Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Muham

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (636.067 KB) | DOI: 10.26714/jsunimus.7.2.2019.%p

Abstract

Analisis time series dapat dilakukan secara univariat maupun multivariat. Pemodelan time series univariat menggunakan model ARIMA (Autoregressive Integrated Moving Average), sedangkan pemodelan multivariat dapat menggunakan VAR (Vector Autoregressive). Baik model ARIMA ataupun VAR memiliki prosedur yang mirip antaralain stasioneritas data, penentuan orde dari model, checking diagnostic. Model VAR merupakan pengembangan dari model AR (Autoregressive). apabila model univariat time series dipengaruhi oleh variabel eksogen dapat dimodelkan menggunakan ARIMAX, sedangkan time series multivariate dapat dimodelkan menggunakan VARX.Pada penelitian ini dimodelkan nilai inflasi di kota Semarang, kota Surakarta dan kota Purwokerto berdasarkan nilai PDRB Jawa Tengah. Berdasarkan hasil analisis yang didapat, nilai inflasi setiap wilayah dipengaruhi lag ke-(t-1) dengan wilayahnya sendiri ataupun dengan wilayah yang lain. Nilai PDRB tdak signifikan hanya di wilayah Surakarta, tetapi di wilayah lainnya signifikan. Nilai AIC model mencapai 976.876.Kata kunci : VARX, inflasi, PDRB
PEMODELAN REGRESI ROBUST M-ESTIMATOR DALAM MENANGANI PENCILAN (STUDI KASUS PEMODELAN JUMLAH KEMATIAN IBU NIFAS DI JAWA TENGAH Alan Prahutama; Agus Rusgiyono; Dwi Ispriyanti; Tiani Wahyu Utami
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 9, No 1 (2021): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.9.1.2021.35-39

Abstract

Regression analysis is statistical method that used to model between predictor variables and response variables. In the regression model, the residual assumed normal distribution, non-autocorrelation, and homoscedasticity. When the assumptions doesn’t fulfilled, then the measurement of goodness not well enough. One of the causes may be outlier of data. Handling the outlier can be used robust regression, which one of method is robust M-estimator.   In this article, we purposed modelling the number of maternal postpartum in Central Java province with predictor variables are the percentage of pregnant who consumed Fe tablet (X1), the percentage of household whom applied clean and health lifestyle(X2), and the percentage of pregnant who First visited to midwife of doctor (K1) (X3).  In the multiple regression only X3 was significantly with R-square was 14.25209%, and Mean Square Error (MSE) was 20.4177. Moreover, in outlier detection, there were two outlier in the data, then modelled with Robust M-estimator. The measurement of goodness used R-square of regression robust M-estimator was 21.74% with MSE was 15.02766. Robust M-estimator regression resulted better model than multiple regression to model the number of maternal postpartum in Central Java Province.
METODE SERVQUAL, KUADRAN IPA, DAN INDEKS PGCV UNTUK MENGANALISIS KUALITAS PELAYANAN RUMAH SAKIT X Ulfi Nur Alifah; Alan Prahutama; Agus Rusgiyono
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 8, No 2 (2020): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.8.2.2020.144-151

Abstract

The quality of service provided by the hospital is very important because it can be used as a reference in determining customer satisfaction. Service quality can be perceived as good and successful if the customer is satisfied with the services and suitable with what customers expect. However, if the services are not suitable with customer expectations, the service quality will be perceived as bad. This study aims to analyze the service quality of X Hospital based on five dimensions of service quality. The data was collected by distributing questionnaires to 64 selected respondents who were patients from Hospital X. Then, the data were calculated the value of the gap between customer expectations and perceptions. Then analyzed using the Importance Performance Analysis method and the Potential Gain Customer Value Index to determine the priority of service quality improvement. Based on the research results, there are only 5 indicators that have a positive gap score, which means that the service quality is suitable with customer expectations. From the Importance Performance Analysis quadrant, the indicators of service quality are spread across four quadrants. From the PGCV index, the indicator of service quality that becomes the first priority for improvement is the ease of access to purchase necessities for patients.
ANALISIS KETAHANAN HIDUP MENGGUNAKAN METODE PERLUASAN REGRESI COX DENGAN VARIABEL BERGANTUNG WAKTU Nabila Chairunnisa; Agus Rusgiyono; Puspita Kartikasari
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 9, No 1 (2021): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.9.1.2021.40-46

Abstract

Extension of the cox proportional hazards model for time dependent variables is an alternative method used if the PH assumption is not satisfied for one or more of the predictors in the model. The step of this method are testing the PH assumption, interacting the time independent variable not satisfying the PH assumption with function of time (linear, logarithm and the combination), testing the parameters using the Likelihood Ratio test and the Wald test, determine the better model of both models by the AIC values, calculating the hazard ratio of each variable that significantly affected ASD. Based on the smallest AIC values, a better model is the extension of the cox proportional hazards model for time dependent variables interacted with logarithm time function. From the better model obtained the variables that affect the recurrence time ASD is patient with heart beat, noisy heart, blood pressure, body mass index, and treatment with catheter.
ANALISIS KOMODITAS UNGGULAN PERIKANAN BUDIDAYA PROVINSI JAWA TENGAH TAHUN 2012-2016 MENGGUNAKAN METODE LOCATION QUOTIENT DAN SHIFT SHARE Dian Mariana L Manullang; Agus Rusgiyono; Budi Warsito
Jurnal Gaussian Vol 7, No 1 (2018): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (564.844 KB) | DOI: 10.14710/j.gauss.v7i1.26630

Abstract

Condition of capture fisheries is currently stagnating, even tended to decline, which is indicated by the decrease of production in some fishery development areas in Indonesia. Aquaculture is one solution that can be done. Central Java Province is a province that has a large aquaculture potential, therefore of course Central Java province has leading commodities that become the sector of regional economic development. This research discusses about the potential location for the development of each leading commodities in Central Java Province as a recommendation related to the centre of fisheries production. Analytical methods in this research are Location Quotient (LQ) dan Shift share. It used to see how big these locations have a potential in the development of aquaculture production and to identify spatial autocorrelation in the amount of aquaculture production using Moran’s index. The analysis of LQ and shift share shows that each district has a different potential in the development of leading commodities production. The value of the Moran’s index obtained equal to -0.1381, that is in the range of -1 <I ≤ 0, indicating that the presence of spatial autocorrelation is negative but small because of near to zero. It can be concluded that there is no similarity of the values between the districts or indicate that amount of aquaculture production among the districts in Central Java are not correlated.Keywords: Leading Commodities, Location Quotient (LQ), Shift Share, Moran’s  Index
ANALISIS GRAFIK PENGENDALI NONPARAMETRIK DENGAN ESTIMASI FUNGSI DENSITAS KERNEL PADA KASUS WAKTU PELOROTAN BATIK TULIS Hana Hayati; Rukun Santoso; Agus Rusgiyono
Jurnal Gaussian Vol 3, No 1 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (489.819 KB) | DOI: 10.14710/j.gauss.v3i1.4778

Abstract

The quality of the product becomes one of the basic factors in the decisions of consumers in selecting products. A companny needs a quality control for keeping the consistency of product quality. One of statistic tools which can be used in quality control is a control chart. If  the obtained data do not have  a specific distribution assumption, it is needs to use nonparametric control chart as the solution. One of ways to describe the nonparametric control chart is a kernel density estimation. The most important point in the kernel density estimation is optimal bandwidth selection and one of the method that can be used is Least Squares Cross Validation. In this case, will be described a nonparametric control chart to data of vanishing candle at batik in Pekalongan using Rectangular, Triangular, Biweight and Epanechnikov kernel density estimation. Based on the data processing using R.2.14, the result was obtained that from the four kernel estimatios which were used, the obtained control chart by the Rectangular kernel density estimation which have the largest value of variance. It shows that the control chart by the Rectangular kernel density estimation is the widest control chart. While, the obtained control chart by the Epanechnikov kernel density estimation which have the smallest value of variance. It shows that the control chart by the Epanechnikov kernel density estimation is the narrowest control chart
ROBUST GEOGRAPHICALLY WEIGHTED REGRESSION DENGAN METODE MUTLAK SIMPANGAN TERKECIL PADA PEMODELAN KEJADIAN DIARE DI KOTA SEMARANG Ika Chandra Nurhayati; Agus Rusgiyono; Hasbi Yasin
Jurnal Gaussian Vol 7, No 2 (2018): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (411.2 KB) | DOI: 10.14710/j.gauss.v7i2.26646

Abstract

Diarrhea is one of many health issues in developing country like Indonesia, because the sickness and the death number are still high. According to health profile of Semarang City, the people who suffer from diarrhea from 2010-2015 are decreasing. The lowest point happened at the year 2013 with the total case of 38.001, however there are an increasing number from 2014-2015. The distribution data of diarrhea is a spatial data. The differences between environment and sanitation could cause spatial heterogeneity. The spatial heterogeneity could cause the produced variant value no longer constant, but instead it is different on each region. Therefore, regression model that involves the effects of spatial heterogeneity is needed, which are Geographically Weighted Regression (GWR) that is built by Weighted Least Square (WLS) adjuster. Although, GWR parameter adjuster that used WLS is very sensitive with the existence of outliers. The existence of the outlier in the data will create a huge residual. Thus, more robust method is needed, which is Least Absolute Deviation (LAD) methods in order to estimate the parameter on model GWR. This model is called Robust GWR (RGWR). The result shows that the model events of diarrhea on each region in Semarang City are different. Furthermore, the model events of diarrhea with RGWR model generate MAPE 16,3396% which means the performance of RGWR is formed well. Keyword: Diarrhea, Robust, Geographically Weighted Regression, Least Absolute Deviation
ANALISIS NILAI RISIKO (VALUE AT RISK) MENGGUNAKAN UJI KEJADIAN BERNOULLI (BERNOULLI COVERAGE TEST) (Studi Kasus pada Indeks Harga Saham Gabungan) Iwan Ali Sofwan; Agus Rusgiyono; Suparti Suparti
Jurnal Gaussian Vol 3, No 2 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (470.078 KB) | DOI: 10.14710/j.gauss.v3i2.5912

Abstract

Risk management is a systematic procedure to decrease the risk of an asset. Risk must be calculated in order to determine the best strategy in investing. Value at Risk (VaR) is a measure of risk that can be used. VaR measures the worst loss that can be happen in the future at a certain confidence level. There are many method to compute VaR. However, the methods are useful if it can predict future risks accurately. Therefore, the methods should be evaluate with a backtesting procedure. This research analyze the two methods of computing VaR, Historical Simulation and Johnson  transformation approach, that estimate the risk of Jakarta Composite Index and backtest the methods use Bernoulli Coverage Test. The result, if using the relative VaR to forecast the risk of Jakarta Composite Index, the historical simulation approach can be used if the expected probability of violation is . Whereas the  Johnson  transformation approach can be used if the expected probability of violation is . If using the absolute VaR to forecast the risk of Jakarta Composite Index, the historical simulation approach can be used if the expected probability of violation is . Whereas the  Johnson  transformation approach can be used if the expected probability of violation is .
APLIKASI METODE MOMEN PROBABILITAS TERBOBOTI UNTUK ESTIMASI PARAMETER DISTRIBUSI PARETO TERAMPAT PADA DATA CURAH HUJAN (Studi Kasus : Data Curah Hujan di Kota Semarang Tahun 2004-2013) Rengganis Purwakinanti; Agus Rusgiyono; Alan Prahutama
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (637.586 KB) | DOI: 10.14710/j.gauss.v3i4.8093

Abstract

The method used to analyze the extreme rainfall is Extreme Value Theory (EVT). One of the approaches in the EVT is Peak Over Threshold (POT) which follows the Generalized Pareto Distribution (GPD). The shape and scale parameter estimates obtained using the method of probability weighted moment. The results of this research were presumptive maximum value within a period of 1 year to the period 2004 to 2013 showed that year 2009/2010 has the possibility of extreme value compared with other years. Also obtained Mean Absolute Percentage Error values ( MAPE ) of 33.19 %. This result is a big difference because the MAPE values above 10 %, thus allowing the emergence of extreme values. Keywords: Rainfall, Extreme Value Theory, Peak Over Threshold, Generalized Pareto Distribution, Probability Weighted Moment
Co-Authors Abdul Hoyi Abdul Hoyyi Agustina Sunarwatiningsih Alan Prahutama Alan Prahutama Andreanto Andreanto Anggita, Esta Dewi Anifa Anifa Anindita Nur Safira ANNISA RAHMAWATI Annisa Rahmawati Arief Rachman Hakim Aulia Putri Andana Aulia Rahmatun Nisa Bayu Heryadi Wicaksono Bellina Ayu Rinni Besya Salsabilla Azani Arif Bramaditya Swarasmaradhana Budi Warsito Dede Zumrohtuliyosi Dermawanti Dermawanti Desy Tresnowati Hardi Di Asih I Maruddani Diah Safitri Diah Safitri Dian Mariana L Manullang Dini Anggreani Diyah Rahayu Ningsih Dwi Asti Rakhmawati Dwi Ispriyansti Dwi Ispriyanti Eis Kartika Dewi Ely Fitria Rifkhatussa&#039;diyah Enggar Nur Sasongko Etik Setyowati Etik Setyowati, Etik Farisiyah Fitriani fatimah Fatimah Febriana Sulistya Pratiwi Feby Kurniawati Heru Prabowo Fitriani Fitriani Hana Hayati Hanik Malikhatin Hanik Rosyidah, Hanik Hasbi Yasin Hasbi Yasin Hildawati Hildawati Hindun Habibatul Mubaroroh Ika Chandra Nurhayati Ilham Muhammad Imam Desla Siena Inas Husna Diarsih Iwan Ali Sofwan Kevin Togos Parningotan Marpaung Listifadah Listifadah M. Afif Amirillah M. Atma Adhyaksa Marthin Nosry Mooy Maryam Jamilah An Hasibuan Maulana Taufan Permana Merlia Yustiti Moch. Abdul Mukid Moch. Abdul Mukid Muhammad Rizki Muhammad Taufan Mustafid Mustafid Mustafid Mustafid Mustofa, Achmad Nabila Chairunnisa Nor Hamidah Noveda Mulya Wibowo Novie Eriska Aritonang Nur Khofifah Octafinnanda Ummu Fairuzdhiya Puji Retnowati Puspita Kartikasari Putri Fajar Utami Rengganis Purwakinanti Revaldo Mario Ria Sulistyo Yuliani Riana Ikadianti Riszki Bella Primasari Rita Rahmawati Rita Rahmawati Rizal Yunianto Ghofar Rizky Aditya Akbar Rosita Wahyuningtyas Rukun Santoso Salsabila Rizkia Gusman Setiyowati, Eka Shella Faiz Rohmana Siti Lis Ina Atul Hidayah Sudargo Sudargo Sudarno Sudarno Sudarno Sudarno Sudarno Sudarno Sugito - Sugito Sugito Sugito Sugito Suparti Suparti Suparti Suparti Susi Ekawati sutimin sutimin Tarno Tarno Tarno Tarno Tarno Tarno Tatik Widiharih Tiani Wahyu Utami Tika Dhiyani Mirawati Tika Nur Resa Utami, Tika Nur Resa Titis Nur Utami Tri Ernayanti Tri Yani Elisabeth Nababan Triastuti Wuryandari Triastuti Wuryandari Tyas Ayu Prasanti Tyas Estiningrum Ulfi Nur Alifah Ungu Siwi Maharunti Uswatun Hasanah Vierga Dea Margaretha Sinaga Viliyan Indaka Ardhi Walidaini, Nur Winastiti, Lugas Putranti Yogi Isna Hartanto Yuciana Wilandari Yuciana Wilandari Yuciana Wilandari