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All Journal PROSIDING SEMINAR NASIONAL Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang

Alan Prahutama

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Author-ID : 452056

Decision Sciences, Operations Research & Management Education Other

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ANALISIS KINERJA PORTOFOLIO OPTIMAL DENGAN METODE MEAN-GINI Mega Susilowati; Rita Rahmawati; Alan Prahutama
Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Investments in financial assets has a special attraction that investors can form a portfolio. Portfolio is investment which comprised of various stocks from different companies. A common issue is the uncertainty when investors are faced with the need to choose stocks to be formed into a portfolio of his choice. A rational investor, would choose the optimal portfolio. Determination of the optimal portfolio can be performed by various methods, one of which is a method of Mean-Gini. Mean-Gini is the expected value of the portfolio return is the weight density function while the random variable is the average of the shares. Mean-Gini methods used to generate the greatest value of portfolio return expectations with the smallest risk. Mean-Gini does not require the assumption of normality on stock returns. Mean-Gini was first introduced by Shalit and Yitzhaki in 1984. This research uses data of closing prices stocks from January 2008 to December 2015. Measurement of portfolio performance with Mean-Gini performed using the Sharpe index. Based on Sharpe index, the optimal portfolio is second portfolio with three stocks portfolio and the proportion investments are 25.043% for SMGR, 68.148% for UNVR and 6.809% for BMRI. Keywords: Stock, Portfolio, Mean-Gini, Sharpe index.

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

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

PEMODELAN TINGKAT INFLASI INDONESIA MENGGUNAKAN MARKOV SWITCHING AUTOREGRESSIVE CONDITIONAL HETEROSKEDASTICITY Omy Wahyudi; Budi Warsito; Alan Prahutama
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The financial sector often under conditions of fluctuating due to changes in monetary policy, the political instability even just a rumor. The linear model cannot capture changes in these conditions, so the model used is Markov Switching Autoregressive Conditional Heteroskedasticity (SWARCH). This model produces value of transition probability and the duration of each state. Filtering and smoothing process performed to determine probability of the observation data in each state. Modeling about the inflation data in Indonesia was done. The model used is SWARCH (2.1) with 240 data. The probability of inflation rate switch from non crisis state to crisis state is 0.016621, while the probability of inflation rate switch from crisis state to non crisis state is 0.195719. Expectation value of the length time in non crisis state is 60.16 days and the crisis state is 5.11 days.Keywords : filtering, smoothing, transition probability, SWARCH

KLASIFIKASI DIAGNOSA PENYAKIT DEMAM BERDARAH DENGUE (DBD) MENGGUNAKAN SUPPORT VECTOR MACHINE (SVM) BERBASIS GUI MATLAB Chainur Arrasyid Hasibuan; Moch. Abdul Mukid; Alan Prahutama
Jurnal Gaussian Vol 6, No 2 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Dengue Hemorrhagic Fever (DHF) is a disease caused by the bite of infected Aedes mosquito by one of the four types of dengue virus with clinical manifestations of fever, muscle aches or joint pain which followed by leukopenia, rash, thrombocytopenia and hemorrhagic diathesis. There are six criteria for determining and catagorizing a positive or negative dengue patients, the variable gender of the patient, the patient's age, the increase in hemoglobin (Hb), increased hematocrit (Hct), the level of platelet and leukocyte levels.Based on these criteria, data of positive and negative catagorized patient will be classified by Support Vector Machine (SVM) using Matlab software. The concept of classification with SVM define as a search for the best hyperplane which serves as a divider of two classes of data in the input space. Kernel function is used to convert the data into a higher dimensional space to allow separation. In order to determine the best parameters of kernel function, hold-out method is used. In the classification by SVM method, 96.4286% obtained as the best accuracy value by using polynomial kernel function. Keywords: Dengue Hemorrhagic Fever (DHF), Classification, Support Vector Machine (SVM), hold-out, Kernel Function.

PEMILIHAN PENGRAJIN TERBAIK MENGGUNAKAN MULTI-ATTRIBUTE DECISION MAKING (MADM) TECHNIQUE FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS) (STUDI KASUS : PT. Sinjaraga Santika Sport, Majalengka) Fizry Listiyani Maulida; Tatik Widiharih; Alan Prahutama
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The human resources (HR) known as the employess are the successful of the company. PT. Sinjaraga Santika Sport (Triple’S) is a handmade football company by the craftsmen. Most of the craftsmen go to the rice fields on the growing season or the harvest season. So selection of the best craftsmen is needed in order to the production of the football don’t have problems. The selection uses TOPSIS method. TOPSIS is one of method that can be used to solve MADM problem. The steps of TOPSIS method are calculated the normalized decision matrix, determined the weight, calculated the weighted normalized decision matrix, determined the positif-ideal solutions and negatif-ideal solutions, calculated the separation measures, and calculated the preference value. There are 25 craftsmen and six criteria. The criteria are neatness of the ball, accurateness stitching of the ball, number of the ball, accurateness logo of the ball, cleanness of the ball, and defect proportion. The results in this reseach are the best carftsmen has 0,78861 of preference value and the worst craftsmen has 0,16642 of preference value. Preference value by manual calculate equal with preference value by GUI Matlab. Keywords : TOPSIS, MADM, carftsmen

PEMBENTUKAN MODEL SPASIAL DATA PANEL FIXED EFFECT MENGGUNAKAN GUI MATLAB (Studi Kasus : Kemiskinan di Jawa Tengah) Irawati Tamara; Dwi Ispriyanti; Alan Prahutama
Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Regression analysis is an analysis of the dependence of one dependent variable, on one or more independent variables. The spatial panel data model is regression models used to explain the effects of region's dependence (spatial effect) and the effect of time period (panel effect) on an observed variable. The establishment of spatial panel data models can be made by an application created using Matlab software called GUI (Graphical User Interface). This research is focus on creating GUI Matlab and the establishment of a spatial panel data model by fixed effects on the case of poverty in Central Java. The results of analysis by using GUI shows that the fixed effects spatial lag model and fixed effects spatial error model are significant. Based on the criteria of goodness of fit, it is known that the fixed effects spatial lag model has higher R2 value than the fixed effects spatial error model that is 0.9903, thus the model chosen as the model of the case of poverty in Central Java is the fixed effects spatial lag model by the spatial lag coefficient is 0.4060. Keywords : GUI, spatial, panel data, fixed effects, fixed effects spatial lag, fixed effects spatial error

METODE SERVQUAL-SIX SIGMA UNTUK PENINGKATAN KUALITAS PELAYANAN PUBLIK (Studi Kasus di Kantor Kecamatan Kedungbanteng, Purwokerto) Dian Andhika Prameswara; Mustafid Mustafid; Alan Prahutama
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Implementation public service is the fulfillment of civil rights that must be implemented by the government, so that its implementation must fit and be able to provide comfort and satisfaction for the society. Therefore, the performance of public services should be improved constantly and controlled so as to meet the needs of service users, because of the good and bad of a public service can be public benchmarks to assess the performance of the government. Measuring the quality of services is not as easy to measure the quality of the product, because the services are subjective. Therefore, the dimension of Servqual as a tool used to measure the performance of public services and Six Sigma to improve the performance of the public service. This study aims to apply the Servqual-Six Sigma methods with the aim to improve the performance of public services Kedungbanteng District Office. The results obtained in this study is that the dimensions of Servqual Six Sigma can be applied to improve the quality of public services.. As a whole, the results obtained indicate that the process of public service at the Kedungbanteng District Office not meet the standards of satisfaction targets 8. The process is based on the dimensions of Servqual is tangible, reliability, responsiveness, assurance, and empathy, respectively located in the sigma value 3,089; 3,102; 3,054; 3,195 and 3,219. This means, the number of mismatches that may arise from one million services performed for each dimension is respectively 5,61%; 5,46%; 6,01%; 4,5% and 4,28%. Keywords: Public service, Servqual, Six Sigma

PEMODELAN VARIABEL-VARIABEL PENGELUARAN RUMAH TANGGA UNTUK KONSUMSI TELUR ATAU SUSU DI KABUPATEN MAGELANG MENGGUNAKAN REGRESI TOBIT Viliyan Indaka Ardhi; Agus Rusgiyono; Alan Prahutama
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Censored data is the data on a dependent variable of which most of the observations are worth less than or equal to zero while others have a certain value or more than zero. Tobit regression model is a statistical model that can overcome the problems in which many independent variables is zero or called data censored. In this research, modeling eggs or milk consumption in Magelang is analyzed using tobit regression. The data used in this research is secondary data derived from Susenas Data Magelang regency 2013. The concluding results of the final modeling shows that the educational level of householder, the amount of expenditure for food in a month, the number of children in the household and the householder’s profession give significant effect on household expenditures for the consumption of eggs or milk with a coefficient determination of is 60,31%. While the remaining 39,69 % is effected by other variables is not examined in this study such as the appetite of consumers and health factors. Keywords: Consumption of Eggs or Milk, Tobit Regression, Censored Data

PEMBENTUKAN POHON KLASIFIKASI BINER DENGAN ALGORITMA QUEST (QUICK, UNBIASED, AND EFFICIENT STATISTICAL TREE) PADA DATA PASIEN LIVER Muhammad Rosyid Abdurrahman; Dwi Ispriyanti; Alan Prahutama
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In this modern era of fast food commonly found that sometimes have chemical substances and the increasing number of motor vehicles that cause the uncontrolled circulation of air pollution that can affect the health of the human liver. To assist in analyzing the presence of liver disorders in humans can be used QUEST (Quick, Unbiased, and Efficient Statistical Tree) algorithm to classify the characteristics of the patient's liver by liver function tests performed in clinical laboratories. QUEST construct rules to predict the class of an object from the values of predictor variables. The tree is constructed by partitioning the data by recuresively, where class and the values of the predictor variables of each observation in the data sample is known. Each partition is represented by a node in the tree. QUEST is one of the binary classification tree method. The results of the classification tree is formed, an important variable in classifying a person affected by liver disease or not, that is the variable Direct Bilirubin, Alkaline Phosphatase, Serum Glutamic Oxaloacetic Transaminase (SGOT), and age of the patient. Accuracy of the QUEST algorithm classifying liver patient data by 73,4 %. Keywords: binary classification trees, QUEST algorithm, liver patient data.

GEOGRAPHICALLY WEIGHTED REGRESSION PRINCIPAL COMPONENT ANALYSIS (GWRPCA) PADA PEMODELAN PENDAPATAN ASLI DAERAH DI JAWA TENGAH Nurmalita Sari; Hasbi Yasin; Alan Prahutama
Jurnal Gaussian Vol 5, No 4 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Linear Regression Analysis is a method for modeling the relation between a response variable with two or more independent variables. Geographically Weighted Regression (GWR) is a development of the regression model where each observation location has different regression parameter values because of the effects of spatial heterogenity. Regression Principal Component Analysis (PCA) is a combination of PCA and are used to remove the effect of multicolinearity in regression. Geographically Weighted Regression Principal Component Analysis (GWRPCA) is a combination of PCA and GWR if spatial heterogenity and local multicolinearity occured. Estimation parameters for the GWR and GWRPCA using Weighted Least Square (WLS). Weighting use fixed gaussian kernel function through selection of the optimum bandwidth is 0,08321242 with minimum Cross Validation (CV) is 3,009035. There are some variables in PCA that affect locally-generated revenue in Central Java on 2012 and 2013, which can be represented by PC1 that explained the total variance data about 71,4%. GWRPCA is a better model for modeling locally-generated revenue for the districts and cities in Central Java than RPCA because it has the the smallest Akaike Information Criterion (AIC) and the largest R2. Keywords : Spatial Heterogenity, Local Multicolinearity, Principal Component Analysis, Geographically Weighted Regression Principal Component Analysis.

Co-Authors - Sugito Abdul Hoyyi Agus Rusgiyono Arief Rachman Hakim Aselina Pratidina Wrediningsih Azizah Mulia Mawarni Berta Elvionita Fitriani Budi Warsito Chainur Arrasyid Hasibuan Diah Safitri Dian Andhika Prameswara Dwi Ispriyanti Dwi Ispriyanti Dwi Ispriyanti Erna Fransisca Angela Sihotang Fathimatuzzahra Syahrozad Nuroqi Fizry Listiyani Maulida Hasbi Yasin Irawati Tamara Jenesia Kusuma Wardhani Laili Isna Nur Khiqmah Luthfi Nashukha Dewi Mariska Srihardianti Mega Susilowati Moch Abdul Mukid Moch. Abdul Mukid Muhammad Rosyid Abdurrahman Mustafid Mustafid Nia Puspita Sari Nunung Hanurowati Nurmalita Sari Omy Wahyudi Rengganis Purwakinanti Rezzy Eko Caraka Rita Rahmawati Rizky Adhi Nugroho Rizky Amanda Rizky Dwi Rahmawati Ronny Gusnadi Rukun Santoso Siti Azizah Sudarno Sudarno Sugito - Sugito Sugito Suparti - Suparti Suparti Tarno Tarno Tatik Widiharih Tiani Wahyu Utami Viliyan Indaka Ardhi Yogi Setiyo Pamuji

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