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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

Author-ID : 366013

Decision Sciences, Operations Research & Management Mathematics Other

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PENENTUAN VALUE AT RISK SAHAM KIMIA FARMA PUSAT MELALUI PENDEKATAN DISTRIBUSI PARETO TERAMPAT Dede Zumrohtuliyosi; Abdul Hoyyi; Agus Rusgiyono
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Each investment object being traded in the stock market will get return that it has risk potential. Return and risk has mutual correlation that equilibrium. If the risk is high, then it obtains high return and vice versa. Risk management is the desain and implementation procedure for controlling risk. Value at Risk (VaR) is instrument to analyze risk management. Financial time series data for return data is assumed that it has heavy tail distribution and heteroscedasticity case (volatility clustering). Time series model that used to modelling this condition are Autoregressive Conditional Heteroscedasticity (ARCH) and Generalized Autoregresive Conditional Heteroscedasticity (GARCH), while Value at Risk calculation is used Generalized Pareto Distribution (GPD) approach. This research uses return data from stock closing prices of Kimia Farma Pusat period October 2009 until September 2014. The best ARCH-GARCH model is ARIMA(0,1,1) GARCH(1,2) model because the parameters are significant and it has the smallest AIC value. Risk calculation that is gotten with GPD approach if invest in Kimia Farma Pusat with interval confidence 95% is 13.6928% rupiah from current asset. Keywords: Stock, Risk, Generalized Autoregressive Conditional Heteroscedasticity (GARCH), Generalized Pareto Distribution (GPD), Value at Risk (VaR)

PENGELOMPOKAN PROVINSI-PROVINSI DI INDONESIA MENGGUNAKAN METODE WARD (StudiKasus: Produksi Tanaman Pangan di Indonesia Tahun 2018) Besya Salsabilla Azani Arif; Agus Rusgiyono; Abdul Hoyyi
Jurnal Gaussian Vol 9, No 1 (2020): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Cluster analysis is a technique for grouping objects or observations into homogeneous groups. Cluster analysis is divided into two methods, namely hierarchy and non-hierarchy. The hierarchy method generally involves a series of n-1 decisions (n is the number of observations) that combine observations into a tree-like structure or dendogram. Hierarchy is divided into two methods, namely agglomerative (concentration) and splitting (distribution). For non-hierarchical methods, the number of clusters can be determined by the researcher. Ward method is a hierarchical cluster analysis method that can maximize homogeneity in the cluster. The Sum-of-Square (SSE) formula is used in this method to minimize variations in the clusters that are formed. In this research, squared euclid distance is used to measure the similarity between object pairs. The data used in this study are secondary data on food crop production, namely rice, corn, soybeans, peanuts, green beans, sweet potatoes, and cassava in Indonesia 2018. To determine the cluster, the elbow method is used to form optimal clusters using WSS formula. Based on the analysis results, it was found that the optimal cluster is four clusters. The first cluster consists of 9 Province, the second cluster consists of 20 Province, the third cluster consists of 1 Province, the fourth cluster consists of 2 Province, and the fifth cluster consists of 2 Province.Keywords: Food Crop, Cluster Analysis, Ward Method, Squared Euclid, Elbow Method

ANALISIS KORESPONDENSI UNTUK MENDAPATKAN PETA PERSEPSI DAN VARIABEL BAGI KEGIATAN USAHA (Studi Kasus Rumah Makan Spesial Sambal (SS) terhadap Pesaingnya) Susi Ekawati; Agus Rusgiyono; Triastuti Wuryandari
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Correspondence analysis is a technique for displaying the rows and columns of a data matrix primarily, a two-way contingency table as points in dual low-dimensional vector spaces. This technique is used to reduce the dimension of variables and describe the profile vector of rows and columns of the contingency table. This research aims to determine the position of the rivalry between the restaurants in Tembalang region based on consumer’s perceptions and to identify variables that distinguish it. The variables which used are including the price, taste, cleanliness, service, variety of food, and parking lots. Correspondence analysis is used to determine the variables that distinguish the 5th of the restaurant. The correspondence analysis produces a combined perceptual map with the satisfaction variables restaurant. From the analysis, it can be concluded that the perceptual map in the correspondence analysis shows the proximity between restaurant and satisfaction variables. Keywords : correspondence analysis, perceptual map, restaurant, satisfaction.

PENERAPAN k-MODES CLUSTERING DENGAN VALIDASI DUNN INDEX PADA PENGELOMPOKAN KARAKTERISTIK CALON TKI MENGGUNAKAN R-GUI Hanik Malikhatin; Agus Rusgiyono; Di Asih I Maruddani
Jurnal Gaussian Vol 10, No 3 (2021): 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.v10i3.32790

Prospective TKI workers who apply for passports at the Immigration Office Class I Non TPI Pati have countries destinations and choose different PPTKIS agencies. Therefore, the grouping of characteristics prospective TKI needed so that can be used as a reference for the government in an effort to improve the protection of TKI in destination countries and carry out stricter supervision of PPTKIS who manage TKI. The purpose of this research is to classify the characteristics of prospective TKI workers with the optimal number of clusters. The method used is k-Modes Clustering with values of k = 2, 3, 4, and 5. This method can agglomerate categorical data. The optimal number of clusters can be determined using the Dunn Index. For grouping data easily, then compiled a Graphical User Interface (GUI) based application with RStudio. Based on the analysis, the optimal number of clusters is two clusters with a Dunn Index value of 0,4. Cluster 1 consists of mostly male TKI workers (51,04%), aged ≥ 20 years old (91,93%), with the destination Malaysia country (47%), and choosing PPTKIS Surya Jaya Utama Abadi (37,51%), while cluster 2, mostly of male TKI workers (94,10%), aged ≥ 20 years old (82,31%), with the destination Korea Selatan country (77,95%), and choosing PPTKIS BNP2TKI (99,78%).

PEMODELAN PRODUK DOMESTIK REGIONAL BRUTO (PDRB) DI PROVINSI JAWA TENGAH MENGGUNAKAN BOOTSTRAP AGGREGATING MULTIVARIATE ADAPTIVE REGRESSION SPLINES (BAGGING MARS) Maryam Jamilah An Hasibuan; Agus Rusgiyono; Diah Safitri
Jurnal Gaussian Vol 8, No 1 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Increased economic improvement is one way to improve people's welfare in certain areas. Gross Regional Domestic Product (GRDP) is one of the macroeconomic indicators used to measure economic growth in a region. Related to the economy in Central Java Province increased from year to year. Increasing economic growth is inseparable from the contribution of factors that sufficiently contribute to the GRDP. Factors that are the cause of GRDP are Regional Original Income, Foreign Investment, and Domestic Investment. The method used to model the factors that influence Gross Regional Domestic Product is the Multivariate Adaptive Regression Spline (MARS) method and combine it with Bagging. MARS method is one method that uses nonparametric regression and high dimension data. The best model used is a model with a combination of BF = 6, MI = 1, MO = 0 with GCV of 5.667,6680. Then bagging is done on the initial data set with 10, 25, 35, 40, 55, 75, 85, 90 and 100 bootstrap replications. GCV produced in bagging MARS 2.258,6192. GCV valuesobtained from MARS bagging are smaller compared to the MARS method. This shows that bagging can reduce the value of GCV and increase accuracy, making this method can be used in this study. Keywords: GRDP, GCV, MARS, Bagging

ANALISIS BIPLOT KOMPONEN UTAMA PADA BANK UMUM (COMMERCIAL BANK) YANG BEROPERASI DI JAWA TENGAH Ely Fitria Rifkhatussa'diyah; Hasbi Yasin; Agus Rusgiyono
Jurnal Gaussian Vol 3, No 1 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Competition among banks in Indonesia nowadays are getting higher due to the good economic growth and increasing of middle social class in Indonesia. The number of banks cause high competition among banks and internal bank itselves. This high competition makes the management of the bank should think seriously to maintain its existence. In this case the assessment of the bank become very important in the banking business to survive in today's banking industry. This study was conducted to determine how competitive the Commercial Bank are operating in Central Java by a method of Principal Component Biplots. This analysis can be applied to find out information about the relative position, the similarity between objects and characteristic of variables in the three categories of commercial banks operating in Central Java based on their health aspects. The results of this study are the banks from each category have a distinct predominance in every aspect of health assessment variable. In addition, the biplots can give information on the variability more than 70% which means that principal component biplot explains the overall data well.

FAKTOR-FAKTOR YANG MEMPENGARUHI KRIMINALITAS DI KABUPATEN BATANG TAHUN 2013 DENGAN ANALISIS JALUR Dermawanti Dermawanti; Abdul Hoyyi; Agus Rusgiyono
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Crime or criminality in Indonesia is rampant both in print or television can be seen almost every day news about crime. Basically, each individual will be influenced by several factors, both internal and external causes a person to commit a criminal act, including population, education, morality, poverty, and unemployment. In this case will be studied in a statistical analysis that can detect the magnitude of these factors, either directly or indirectly to the level of criminality. One of the statistical analysis that can be used to analyze the causal relationship of the variables is the path analysis (path analysis) which is a direct development of multiple regression form with the aim to provide estimates of the level of interest (magnitude) and significance (significance) in a hypothetical causal link set variable. In this study showed that the factor that has the greatest positive effect on crime is unemployment factor of 0.395 with immediate effect. A factor which has the second largest positive effect of education is a factor of 0.222 to the direct effects and the indirect effect of 0.0818. Meanwhile, a factor that has a positive influence smallest is the moral factor to the effect of 0.180.Keywords : Criminality, Path Analysis

ANALISIS INTEGRASI PASAR BAWANG MERAH MENGGUNAKAN METODE VECTOR ERROR CORRECTION MODEL (VECM) (Studi Kasus: Harga Bawang Merah di Provinsi Jawa Tengah) Rizky Aditya Akbar; Agus Rusgiyono; Tarno Tarno
Jurnal Gaussian Vol 5, No 4 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Spatial market integration is the degree of closeness of relationship between the regional market with other regional market. Vertical market integration is the level of the relationship between a marketing agency with other marketing agencies in the marketing. Spatial market integration in onion prices at the wholesale level for the area of Brebes, Tegal, Pemalang, Semarang, Salatiga, Surakarta and can be analyzed using the Vector Error Correction Model (VECM) to see where the long-term relationship. Vertical market integration in onion prices in the wholesale and consumer levels for Tegal, Semarang and Surakarta can be analyzed using the Granger Causality. The data used are the monthly time series data from January 2010 until February 2016, where data must be stationary at the first difference. Based on Johansen cointegration test obtained their long-term relationship at all six of the region and can be used to analyze VECM method. Granger Causality used as a test of causality. From this study, it can be concluded the onion market in Central Java is not fully integrated spatial whereby if shocks in Brebes then be transmitted to the market in Pemalang, Semarang, Salatiga and Surakarta whereas if shocks occur in Tegal will be transmitted to Semarang, Salatiga and Surakarta. This occurs because Brebes as the central region producing onion and Tegal as many areas in need of onion. The existence of vertical integration only occurs in Semarang, although only one-way causality. Keywords: Market Integration, Johansen Cointegration Test, VECM, Granger Causality Test.

PERAMALAN HARGA CABAI MERAH MENGGUNAKAN MODEL VARIASI KALENDER REGARIMA DENGAN MOVING HOLIDAY EFFECT (STUDI KASUS: HARGA CABAI MERAH PERIODE JANUARI 2012 SAMPAI DENGAN DESEMBER 2019 DI PROVINSI JAWA BARAT) Aulia Rahmatun Nisa; Tarno Tarno; Agus Rusgiyono
Jurnal Gaussian Vol 9, No 2 (2020): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Chili is one of the vegetable commodities that has high economic value, because of it’s role is large enough to supply domestic needs as an export commodity in the food industry. The price of red chilliesalways increase in the month of Eid al-Fitr. This is due to the large number of people who use Red Chili as food they consume. Shifting the moon during the Eid al-Fitr will form a seasonal system with different periods, which became known as the Moving Holiday Effect. One of the calendar variation models used to eliminate the Moving Holiday Effect and has a simple processing flow is the RegARIMA model. The RegARIMA model is a combination of linear regression with ARIMA. In the regression model the weighting matrix is used as an independent variable and the price of red chili as the dependent variable. The weight value is obtained based on the number of days that affect Eid, which is 14 days. Based on the analysis the red chili price data in West Java Province with the period of January 2012 to December 2018, the RegARIMA model (1.0,0)(0,1,1) 12 is the best model because it has the smallest AIC. Forecasting results in 2020 showed an increase in the price of red chili in West Java occurred in May to coincide with the Eid al-Fitr holiday which fell on May 24, 2020, the sMAPE value obtained by 24.96%. It means, the forecast still in the level of reasonableness.

SIMULASI STOKASTIK MENGGUNAKAN ALGORITMA GIBBS SAMPLING Anifa Anifa; Moch. Abdul Mukid; Agus Rusgiyono
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

One way to get a random sample is using simulation. Simulation can be done directly or indirectly. Markov Chain Monte Carlo (MCMC) is an indirectly simulation method. MCMC method has some algorithms. In this thesis only discussed about Gibbs Sampling algorithm. Gibbs Sampling is introduced by Geman and Geman at 1984. This algorithm can be used if the conditional distribution of the target distribution is known. It has applied on two casses, these are generation of bivariate normal random data and parameters estimation using Bayesian method. The data used in this research are the death of pulmonary tuberculosis in ASEAN in 2007. The results obtained are and with standard error for and .

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 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

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