Agus Rusgiyono
Departemen Statistika, Fakultas Sains Dan Matematika, Universitas Diponegoro

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Journal : Jurnal Gaussian

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
ANALISIS SEKTOR UNGGULAN MENGGUNAKAN DATA PDRB (Studi Kasus BPS Kabupaten Kendal Tahun 2006-2010) Rosita Wahyuningtyas; Agus Rusgiyono; Yuciana Wilandari
Jurnal Gaussian Vol 2, No 3 (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 (505.722 KB) | DOI: 10.14710/j.gauss.v2i3.3667

Abstract

Gross Domestic Regional Product (GDRP) is total numbers of added values who’s producting by effort unit in that domestic area’s. GDRP can be classified in two form, that is GRDP at Current Market Prices and GRDP at Constant Prices. GRDP at Current Market Prices is calculating with two approaches, those are approach production and approach income. GRDP at Constant Prices can be calculated using two methods, revaluation and deflation. By using GDRP data, then it can be known which sector is  prominent sector in that region. Some methods who using GDRP data as decisive prominent sector is method of Typology Klassen, LQ, MRP, Overlay and Shift Share. These methods classifying the economic sectors into four groups, they are prominent sector, growing sector, potential sector and under developed sector, based on large of contribution and rate of growth. By taking the study area Kendal Regency and reference area is province Central of Java, then by used that methods can be known which sector be prominent sector in Kendal Regency. Based on the result from analysis methods, they are same result about prominent sector: agriculture sector and mining and quarrying sector
PENENTUAN HARGA OPSI PUT DAN CALL TIPE EROPA TERHADAP SAHAM MENGGUNAKAN MODEL BLACK-SCHOLES Marthin Nosry Mooy; Agus Rusgiyono; Rita Rahmawati
Jurnal Gaussian Vol 6, No 3 (2017): 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 (422.448 KB) | DOI: 10.14710/j.gauss.v6i3.19344

Abstract

Option is a contract that gives the right, but not obligation, to individuals to buy (call) or sell (put) certain stocks by a certain price at a specified date. One method that can be used to estimate option price is by using Black-Scholes Model. This model is introduced by Fisher Black and Myron Scholes in 1973. Black-Scholes Model was derived in certain assumptions, such as no dividens, no transaction cost, free-risked interest rates, the option is “European”, and stock price follows a random walk in continuos time, thus the distribution of possible stock prices is lognormal. Application of Black-Scholes Model on Honda Motor Company, Ltd.’s stocks shows that investors can get profits by investing on certain contracts, which is call options with the price of 10,1 US$; 8,9 US$; and 1,15 US$, and also put option with the price of 6,12 US$, all with maturity date at January 20th 2017. Keywords: Option, call option, put option, stock, Black-Scholes model.
PEMODELAN LAJU KESEMBUHAN PASIEN RAWAT INAP TYPHUS ABDOMINALIS (DEMAM TIFOID) MENGGUNAKAN MODEL REGRESI KEGAGALAN PROPORSIONAL DARI COX (Studi Kasus di RSUD Kota Semarang) Bellina Ayu Rinni; Triastuti Wuryandari; 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 (594.229 KB) | DOI: 10.14710/j.gauss.v3i1.4773

Abstract

Typhus Abdominalis (typhoid fever) is a systemic infectious disease caused by Salmonella typhi and ranked 3rd of 10 major inpatient diseases in the hospitals of Indonesia based on Indonesia’s health profile data in 2010. It's important to know the factors that can affect the rate of recovery of hospitalized patients suffering from typhoid fever. One way is to use survival analysis that is a statistical method to analyze survival data. Cox proportional hazards regression is a model in survival analysis used to determine the relationship between one or more independent variables and the dependent variable. This model does not require information about the underlying distribution, but the hazard functions of different individuals assumed to be proportional. The Data used are from 45 patients of thypoid fever on RSUD Kota Semarang who have been medically recorded from  August 1st 2012 until November 30st 2012. Furthermore it is concluded that the factors that affect the rate of recovery of inpatients suffering from typhoid fever were age.
PENERAPAN METODE GENERALIZED STRUCTURED COMPONENT ANALYSIS PADA KEPUASAN KONSUMEN (Studi Kasus: Pasien Klinik Q) Farisiyah Fitriani; Agus Rusgiyono; Tatik Widiharih
Jurnal Gaussian Vol 9, No 4 (2020): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v9i4.29416

Abstract

Customer satisfaction is used by a company to evaluate products or services whether it is sufficient with customer’s expectations. Satisfaction is influenced by factors that cannot be measured directly are called latent variables and can be measured through indicators used to measure satisfaction with Structural Equation Modeling (SEM). Generalized Structured Component Analysis (GSCA) method is part of a SEM based on a variant that does not require the assumption of a multivariate normal distribution and has a measure overall goodness of fit. The parameters used are factor loading, coefficients parameter, and weight of indicators and estimated with alternating least square. The type of data used primary data from the results of the questionnaire with stratified proportional random sampling and number of samples 286. This research using indicators as measurable variables as many 32 indicators and 8 latent variable. Considering to the evaluation of the structural model, it is found there are 5 variables that influence satisfaction, they are prices, quality yield, cleanliness, doctor's services, and employee services with a large influence of 77.18% and the impact of satisfaction on loyalty is 48.63 %. For the overall goodness of fit measure, it is known that the FIT value is 63.75% and the adjusted FIT (AFIT) value is 63.47%. The goodness of fit (GFI) produced the value in the amount of 96.43%, indicating that the general model has the good level of compatibility.Keywords: Generalized Structured Component Analysis, Structural Equation Modeling, Overall goodness of fit, Alternating Least Square, Stratified Proportional Random Sampling
PENERAPAN ANALISIS KLASTER METODE WARD TERHADAP KABUPATEN/KOTA DI JAWA TENGAH BERDASARKAN PENGGUNA ALAT KONTRASEPSI Yogi Isna Hartanto; Agus Rusgiyono; Triastuti Wuryandari
Jurnal Gaussian Vol 6, No 4 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v6i4.30387

Abstract

The cluster analysis of the Ward method is a cluster forming method based on minimizing the loss of information due to the incorporation of objects into clusters. An Error Sum of Square (ESS) is used as an objective function. Two objects will be combined if they have the smallest objective function among possibilities. The similarity measure used is the Euclidean distance. In this experiment used data from the number of users of contraceptives in Central Java Province. Contraceptives that can be detected its use is IUD, MOW, MOP, condoms, implants, injections, and pills. The results of cluster analysis of Ward method were obtained as many as 3 clusters. First cluster consists of 9 districts/cities with the number of use of most contraceptives, namely Cilacap, Banyumas, Pati, Pemalang, Tegal, Jepara, Grobogan, Demak, and Semarang City. Second cluster consists of 21 districts/cities with the number of use of medium contraceptives, namely Purbalingga, Banjarnegara, Kendal, Wonogiri, Pekalongan, Blora, Brebes, Kebumen, Wonososbo, Boyolali, Karanganyar, Sragen, Magelang, Klaten, Semarang, Purworejo, Temanggung , Sukorejo, Rembang, Batang, and Kudus. Third cluster consists of 5 districts/cities with the number of use of contraceptives a little, namely Magelang City, Salatiga City, Surakarta City, Pekalongan City, and Tegal City. Keywords: Contraceptives, Cluster Analysis, Ward Methods, Euclidean Distance
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&#039;diyah Elyasa, Fatiya Rahmita 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 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