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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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ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI BANYAKNYA KLAIM ASURANSI KENDARAAAN BERMOTOR MENGGUNAKAN MODEL REGRESI ZERO-INFLATED POISSON (Studi Kasus di PT. Asuransi Sinar Mas Cabang Semarang Tahun 2010) Taufan, Muhammad; Suparti, Suparti; Rusgiyono, Agus
MEDIA STATISTIKA Vol 5, No 1 (2012): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (569.023 KB) | DOI: 10.14710/medstat.5.1.49-62

Abstract

Poisson regression is one of model that is often used to model the relationship between response variables in the form of discrete data with a set of predictor variables in the form of continuous, discrete, category, or mixture data. In Poisson regression assumes that the mean of the response variable equal to the variance (equidispersion). But in reality, sometimes found a condition called overdispersion, that the variance value is greater than the mean. One of the cause of overdispersion is excess zero in the response variable. One of model that can be used to overcome this overdispersion problem is Zero-Inflated Poisson (ZIP) regression  model. This model is applied on a case study of motor vehicle insurance in the branch of PT. Asuransi Sinar Mas in Semarang in 2010 to determine the effect of age of car and types of coverage to number of claims filed by the policyholder to the branch of PT. Asuransi Sinar Mas in Semarang. In this case, the occurrence of zeros due to many policyholders did not file a claim to the branch of PT. Asuransi Sinar Mas in Semarang. From the analytical result obtained the conclution that the age of car and types of coverage affect number of claims filed by the policyholder to the branch of PT. Asuransi Sinar Mas in Semarang in 2010.   Keywords: Poisson Regression, Overdispersion, Zero-Inflated Poisson (ZIP) Regression
MODEL CURAH HUJAN EKSTREM DI KOTA SEMARANG MENGGUNAKAN ESTIMASI MOMENT PROBABILITAS TERBOBOTI Rusgiyono, Agus; Wuryandari, Triastuti; Rahmawati, Annisa
MEDIA STATISTIKA Vol 8, No 1 (2015): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (451.893 KB) | DOI: 10.14710/medstat.8.1.13-22

Abstract

The methods is used to analyze extreme rainfall is the Extreme Value Theory (EVT). One of the approaches of EVT is the Block Maxima (BM) which it follows the distribution of Generalized Extreme Value (GEV). In this study, the dasarian rainfall data of 1990-2013 in the Semarang City is divided based on block monthly and examined in October, November, December, January, February, March and April. The resulted blocks are 24 with 3 observations each block. Parameter shape, location and scale are estimated  Probability Weight Moments (PWM) methodes The result of this study are January has the greatest occurrence chance of extreme value, estimated of parameter shape 0,3840564, location 138,8152989 and scale 68,6067117. In addition, the alleged maximum value of dasarian rainfall obtained in a period of 2, 3, 4, 5 and 6 years are 243,45753 mm, 308,23559 mm, 357,26996 mm, 397,96557 mm and 433,28889 mm respectively. Keywords: Rainfall, Extreme Value Theory, Block Maxima, Generalized Extreme Value, Probability Weight Moments
PENGELOMPOKAN KABUPATEN/KOTA BERDASARKAN KOMODITAS PERTANIAN MENGGUNAKAN METODE K MEDOIDS Wuryandari, Triastuti; Rusgiyono, Agus; Setyowati, Etik
MEDIA STATISTIKA Vol 9, No 1 (2016): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (293.687 KB) | DOI: 10.14710/medstat.9.1.41-49

Abstract

The land in Central Java have a lot of nutrients, so considered suitable for agriculture. North Central Java and some areas in Central Java suitable agriculture for food crops of rice and other crops such as corn, soybeans, peanuts, sweet potatoes and cassava. With the diversity of agricultural production of food crops in Central Java it is necessary to facilitate the grouping of government in determining the specific policy in agriculture in order to achieve national food security. These grouping using cluster analysis with non hierarchical partitioning methode k medoids. The cluster using a point value from the agricultural commodity crops, thereby reducing the sensitivity of the data outliers. Keywords: Central Java, Agricultural Commodities, Cluster Analysis, Non-Hierarchical,     k Medoids, Outlier
APLIKASI METODE BESARAN PIVOTAL DALAM PENENTUAN SELANG KEYAKINAN TAKSIRAN PARAMETER POPULASI. Rusgiyono, Agus
MATEMATIKA Vol 4, No 3 (2001): Jurnal Matematika
Publisher : MATEMATIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (61.498 KB)

Abstract

Diberikan populasi dengan densitas  dengan  parameter , dan dari padanya  diambil sample acak . Selanjutnya taksiran titik  adalah suatu fungsi  dari   bernilai riil . Interval taksiran terhadap  berdasarkan taraf keyakinan , dengan  , ditentukan berdasarkan bantuan besaran pivotal  yang mempunyai distribusi tidak bergantung pada . Diketahui  dan  adalah dua statistik yang memenuhi  untuk mana  dengan  tidak bergantung pada ,  maka interval acak adalah interval keyakinan untuk .
UJI KOMPARATIF TERHADAP DUA STATISTIK UJI TYPE KOLMOGOROV SMIRNOV Rusgiyono, Agus
MATEMATIKA Vol 12, No 2 (2009): JURNAL MATEMATIKA
Publisher : MATEMATIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (30.249 KB)

Abstract

In several statistics handbooks of statistics gave the following formula for the computation of the Kolmogorov goodness of fit statistic is    . And the alternative formula test statistic  to  measure  distance for two distribution functions is used   For actual data, the difference is likely to be less than the upper bound. This form makes it clear that an upper bound on the difference between these two formulas is  For example, for N = 20, the upper bound on the difference between these two formulas is 0.05  For N = 100, the upper bound is 0.01. In practice, to large sample sizes (say N ≥ 50), these formulas are essentially equivalent.
KLASIFIKASI INTERAKSI GELOMBANG PERMUKAAN BERTIPE DUA SOLITON sutimin, Sutimin; Rusgiyono, Agus
MATEMATIKA Vol 4, No 1 (2001): JURNAL MATEMATIKA
Publisher : MATEMATIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (45.963 KB)

Abstract

Pada tulisan ini diselidiki, masalah klasifikasi interaksi gelombang bertipe dua soliton Kadomtsev-Petviashvilli (KP). Disini dianalisis berdasarkan parameter interaksi dua solusi soliton baik melalui harga eksak maupun proses pelimitan. Proses pelimitan ini dilakukan untuk mengetahui resonansi diantara dua soliton. Selanjutnya  resonansi soliton ini dikaji untuk mendapatkan soliton yang baru.
ESTIMASI REGRESI WAVELET THRESHOLDING DENGAN METODE BOOTSTRAP Suparti, Suparti; Mustofa, Achmad; Rusgiyono, Agus
MATEMATIKA Vol 10, No 2 (2007): JURNAL MATEMATIKA
Publisher : MATEMATIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (109.952 KB)

Abstract

Wavelet is a function that has the certainly characteristic for example, it oscillate about zero point ascillating, localized in the time and frequency domain and construct the orthogonal bases in  L2(R) space. On of the wavelet application is to estimate non parametric regression function. There are two kinds of wavelet estimator, i.e., linear and non linear wavelet estimator. The non linear wavelet estimator is called a thresholding wavelet rstimator. The application of the bootstrap methode in the thresholding wavelet function estimation is resample the wavelet coefficient of residual. The best of the thresholding wavelet estimator with bootstrap method has minimal of mean square error (MSE). The minimal MSE depend from the number of replication.  
Identifikasi Faktor-Faktor Penyebab Kejadian Diare Di Kota Semarang Dengan Pendekatan Geographically Weighted Poisson Regression Yasin, Hasbi; Rusgiyono, Agus
JURNAL SAINS DAN MATEMATIKA Volume 21 Issue 3 Year 2013
Publisher : JURNAL SAINS DAN MATEMATIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (5013.469 KB)

Abstract

The percentage of people affected by diarrheal diseases are still quite high, reaching 5.2%. Therefore we need an effort to identify the factors that cause diarrhea efforts of the government in order to reduce morbidity of diarrhea optimally. Such efforts include reviewing of the factors causing the incidence of diarrhea by focusing on linkages between regions or spatial aspects. Spatial aspect is considered important to study because between regions must have different characteristics. One approach that can be used is a spatial model Geographically Weighted Poisson Regression (GWPR) which is a local form of the Poisson Regression. This research was conducted in Semarang city with the unit of observation is the 16 districts in Semarang city. The results showed that the locally influential variable is the number of protected drinking water facilities and the number of medical personnel available. This model has a level of accuracy of 84.33%.
ANALISIS FAKTOR-FAKTOR TINGKAT KEMISKINAN DI KABUPATEN WONOSOBO DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED REGRESSION Permana, Maulana Taufan; Yasin, Hasbi; Rusgiyono, Agus
Jurnal Gaussian Vol 2, No 1 (2013): 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 (649.886 KB) | DOI: 10.14710/j.gauss.v2i1.2744

Abstract

Poverty reduction is the main priority in development strategies in Indonesia, but during this computation is modeled as a function of the poor global regression. That is, the value of the regression coefficient applies to all geographic regions. In reality each region has different characteristics according to the geographical location, therefore Geographically Weighted Regression models are developed (GWR). GWR model is used to consider the element of geography or location as the weighting in estimating the model parameters. In the model GWR model parameter estimation is obtained by using Weighted Least Square (WLS) is to give a different weighting at each location. This study discusses the factors that affect the level of poverty in the District Wonosobo. The results of testing the suitability of the model shows that there is no spatial factors influence the level of poverty in the District Wonosobo. Based on research, there are 3 variables thought to affect the level of household poverty in Wonosobo district, percentage of the number of families that have slums, percentage number of families severely malnourished, percentage of the number of families who have agricultural land. These variables have a similar effect in each district.Keywords: Poverty, Geographically Weighted Regression, Weighted Least Square, Wonosobo
MODEL KOMBINASI ARIMA DALAM PERAMALAN HARGA MINYAK MENTAH DUNIA Setiyowati, Eka; Rusgiyono, Agus; Tarno, Tarno
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 (455.014 KB) | DOI: 10.14710/j.gauss.v7i1.26635

Abstract

Oil is the most important commodity in everyday life, because oil is one of the main sources of energy that is needed for other people. Changes in crude oil prices greatly affect the economic conditions of a country.  Therefore, the aim of this study is develop an appropriate model for forecasting crude oil price based on the ARIMA and its ensembles. In this study, ensemble method uses some ARIMA models to create ensemble members which are then combined with averaging and stacking techniques. The data used are the price of world crude oil period 2003-2017. The results showed that ARIMA (1,1,0) model produces the smallest RMSE values for forecasting the next thirty six months. Keywords: Ensemble, ARIMA, Averaging, Stacking, Crude Oil Price
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 Bagus Arya Saputra 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'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 Nur Walidaini 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 Sudarno Sudarno Sugito - Sugito Sugito Sugito Sugito Suparti Suparti Suparti Suparti Susi Ekawati sutimin sutimin Tarno Tarno Tarno Tarno Tarno Tarno Tatik Widiharih 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 Winastiti, Lugas Putranti Yogi Isna Hartanto Yuciana Wilandari Yuciana Wilandari Yuciana Wilandari