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

Moch. Abdul Mukid

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Author-ID : 475550

Decision Sciences, Operations Research & Management Education Other

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PEMILIHAN MODEL REGRESI POLINOMIAL LOKAL DAN SPLINE UNTUK ANALISIS DATA INFLASI DI JAWA TENGAH Elyas Darmawan; Suparti Suparti; Moch. Abdul Mukid
Jurnal Gaussian Vol 3, No 2 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Inflation becomes one of important problems as parameter of economic growth and determiner factor for government in formulating fiscal, monetary and nonmonetary policy. But, these days the policies were arranged can’t give the positive response to inflation pressure in the future. Therefore, the prediction of inflation rates are needed. Inflation rates are predicted by nonparametric regression approach because of the fluctuation of inflation which can’t be solved by classic time series models. In this research, the best nonparametric regression models are selected between local polynomial and spline regression to predict Central Java Inflation movement in 2014. Based on analysis, the best nonparametric regression is spline order 2, knot points are 5,37; 5,44; 5,59 and 9,01 with GCV 0,4367286. By using that model, the prediction of Central Java inflation got down since October 2013 until February 2014 on level 7% and March until December 2014 on level 6%.

PERBANDINGAN ANALISIS FAKTOR KLASIK DAN ANALISIS FAKTOR ROBUST UNTUK DATA INFLASI KELOMPOK BAHAN MAKANAN DI JAWA TENGAH Erna Puspitasari; Moch. Abdul Mukid; Sudarno Sudarno
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Factor analysis is a statistical method used to describe a set of variables based on common dimensions. Factor analysis that is often used is the classical factor analysis with principal components method. Classical factor analysis can not work properly if the data contained many outliers. In order factor analysis remains optimal in explaining a set of variables even in conditions of data containing many outliers, we need a robust estimator. Through factor analysis is expected to obtain robust high accuracy analysis results for data containing many outliers. Estimator fast-MCD is one of the robust estimator that aims to get the smallest determinant of the covariance matrix. Robust factor analysis with fast-MCD method in this thesis is applied to explain the many subgroups of food at food inflation rate in Central Java into a more modest dimensions. The total proportion of the data variance can be explained by factors that are formed through a robust method of factor analysis in foodstuffs inflation data in Central Java that is equal to 72.9 percent larger than the classical factor analysis method which generates at 53.5 percent. This suggests that a more robust factor analysis method is able to cope with food inflation data in Central Java group containing outliers of the classical factor analysis method.

ANALISIS PROCRUSTES PADA INDIKATOR INDEKS PEMBANGUNAN MANUSIA (IPM) DI KABUPATEN/KOTA PROVINSI JAWA TENGAH (STUDI KASUS IPM TAHUN 2008 DAN 2013) Bunga Maharani; Moch. Abdul Mukid; Suparti Suparti
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Human Development Index (HDI) as a measure of development in the performance of a whole formed through the approach of the four indicators which is real expenditure per capita, the average length of school, literacy rates and life expectancy. To learn about how the in contributing each indicators need to be identified the changes that occurred. Of the changes can use these as an ingredient of analysis in order to cope with or reduce the problems of development to realize the quality sustainably. Hence, this study aims to know of the changes of HDI in Central Java by mapping position of districts there are into a map geometry resulting from metric multidimensional scaling analysis. Where in 2008 as the beginning of leadership and 2013 as the end of leadership of Provincial Governor of Central Java Mr. Bibit Waluyo for five years served. By using an analysis procrustes, obtained the results that in the early period and the end of having the consistency of 90,53 %. In other words, the similarity of the large this indicates that at the beginning and end leadership of relatively no change.Keywords: Indicator, Map geometry, Metric multidimensional scaling, Changes analysis procrustes.

ANALISIS KEPUASAN PENGUNJUNG MENGGUNAKAN SECOND ORDER CONFIRMATORY FACTOR ANALYSIS PADA STRUCTURAL EQUATION MODELING (Studi Kasus: Pengunjung Pemandian Air Panas (PAP) Guci) Niken Anggraini Dewi; Rita Rahmawati; Moch. Abdul Mukid
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Pemandian Air Panas (PAP) Guci is one of the famous natural destinations in Tegal regency. The visitors are fluctuated. Therefore, the writer carried out an analysis of visitor satisfaction using Stuctural Equation Modeling (SEM). Confirmatory factor analysis using in the reseach is second order. The construct used are the service quality (tangibles, reliability, responsiveness, insurance, and empathy), product quality (facilities, accessibility, source human and hygiene), price (affordability, suitability, and price comparisons), visitor satisfaction (overall satisfaction, satisfaction as expected, and the employee), and the interest reset. Choosing variables based on justification theory. Significant parameters, namely the quality service to the quality products by 50,8%, the quality product to the prices by 89%, the price to the visitor satisfaction of 91,4%, visitor satisfaction to the interest reset of 55%. Parameters were not significant, envelop service quality to price, quality service to visitor satisfaction, and quality product to visitor satisfaction. Keywords: Second Order Factor Analysis, SEM, Product Quality, Service Quality, Price, Visitor Satisfaction, Interest Reset.

MODEL REGRESI COX PROPORTIONAL HAZARDS PADA DATA LAMA STUDI MAHASISWA (Studi Kasus Di Fakultas Sains dan Matematika Universitas Diponegoro Semarang Mahasiswa Angkatan 2009) Landong Panahatan Hutahaean; Moch. Abdul Mukid; Triastuti Wuryandari
Jurnal Gaussian Vol 3, No 2 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

High education has important role to increase the intellectual life of the nation and the development of natural sciences and technology by producing the quality graduates. The quality graduates just need 48 month to finish the study. There are many factors that will affect time of study students as Grade Point Average(GPA), Bustle student level, etc. Hence, need to know what factors affecting time of study students. One method that can be used is Survival analysis. Survival Analysis is analysis of survival data from the beginning of time research until certain events occurred. One of the methods of survival analysis is Cox Proportional Hazards Regression. Cox Proportional Hazards Regression is a regression which used data of intervals of time an event. The case which is discussed in this research is factors that affect time of study students of Faculty of Science and Mathematics started 2009 Diponegoro of University with the second type of censoring. From the research give conclusion that factors affecting time of study students is Department, GPA, and Organization

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 .

IDENTIFIKASI LAMA STUDI BERDASARKAN KARAKTERISTIK MAHASISWA MENGGUNAKAN ALGORITMA C4.5 (Studi Kasus Lulusan Fakultas Sains dan Matematika Universitas Diponegoro Tahun 2013/2014) Bramaditya Swarasmaradhana; Moch. Abdul Mukid; Agus Rusgiyono
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Based on academics regulation No. 209/PER/UN7/2012, the study period of students in Diponegoro University has been scheduled for 4 years. In this study the graduation status of students that graduate under or equal to 4 years categorized as graduate on time, meanwhile students that graduate over 4 years categorized as graduate out of time. Hence, it is important to understand the profile of students who graduate on time and out of time based on gender, majors, GPA, organizational experience, part time experience, scholarship, students origin and pathways scholar. The purpose of this study is to identify those students profiles using Algorithm C4.5. Algorithm C4.5 contructs a decision tree that able to handle missing values, able to handle continues attribute and able to simplify the trees by pruning. The accuration of the Algorithm C4.5 is 84.475% and the number of the nodes are 20 nodes where 13 nodes are leaf nodes. The students profile that identified graduate on time are students of Physics who had received scholarship and a woman; students of Chemistry with GPA > 3.06; students of Statistics with GPA > 3.43 from SNMPTN also PSSB and students of Mathematics with GPA > 2.96. Keywords: Study Period, Algorithm C4.5, Decision Tree.

ANALISIS DISKRIMINAN FISHER POPULASI GANDA UNTUK KLASIFIKASI NASABAH KREDIT Ungu Siwi Maharunti; Moch. Abdul Mukid; Agus Rusgiyono
Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Credit is the biggest asset carried out by a bank and become the most dominant contributor to the bank income. However, the activity to distribute the credit takes a risk which can influence health and continuance of bank business. The credit risk which potentially occurs can be measured and controlled by analyzing directly whichever the credit client categorized to. The credit risk categorized to current credit, in specific concern credit, less current credit, doubtful credit and bad credit based on Bank Indonesia Regulation No.: 7/2/PBI/2005. The independent variables used in this research are nominal credit, principal balance, in time being bank client, time period, and bank interest. Fisher multiple discriminant analysis is a method whose assumption equality of covariance matrices. The result from using the Fisher multiple discriminant analysis in data of credit client from bank “X” in Pati shows that variable principal balance, in time being bank client, time period, and bank interest significant to measure credit risk. The classification using the Fisher multiple discriminant analysis in data of credit client from bank “X” in Pati gives the accurate 64,33%. Keywords: credit, classification, fisher multiple discriminant analysis

ANALISIS EKUITAS MEREK SEPEDA MOTOR HONDA TERHADAP KEPUTUSAN PEMBELIAN DAN PERILAKU PASCA BELI MENGGUNAKAN STRUCTURAL EQUATION MODELLING (SEM) Herwindhito Dwi Putranto; Abdul Hoyyi; Moch. Abdul Mukid
Jurnal Gaussian Vol 2, No 1 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Research on the implementation of Structural Equation Modelingto analyze the Honda brand equityon purchase decision and post-purchase behavior is based on the strength of the brand equityas a market leader Honda motorcycles in Indonesia for many years. The problem saddressed in this study is how the relationship between brand equity Honda motorcycle on purchase decision and post purchase behavior of consumers. In this study developed six variables consisting of 4 exogenous variables, namely brand awareness, brand response, the impression of quality and product loyalty, to measure brand equityas well as two endogenous variables, ie, purchase decision and post-purchase behavior. The study involved 200 students of the University of Diponegoro as respondents using purposive sampling technique.Structura lequation modeling research is Behavioral Post Buy=Purchasing Decisions + error. From the Goodness of Fittest results, structural equation modelin this study can be used with a value of 70,237 and the Chi-Square probability AGF I1000 and 0951. Brand awareness of 10.1% influence on purchasing decisions and 10% of the post-purchase behavior and is avariable that gives the effect of CR 1477-value ≤2.58. Responses highest brandin fluenceis equal to 32.7% against 32.4% purchase decision and post-purchase behavior. Thusit was concluded that brand awareness does not affect the purchase decision, while there sponse the brand, the impression of quality and product loyalty influence purchasing decisions. Purchasing decisions also provide a positive influence on post-purchase decisions.

PENGELOMPOKAN PROVINSI DI INDONESIA BERDASARKAN KARAKTERISTIK KESEJAHTERAAN RAKYAT MENGGUNAKAN METODE K-MEANS CLUSTER Fitra Ramdhani; Abdul Hoyyi; Moch. Abdul Mukid
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Welfare have a relative explanation, dynamic, and quantitative. Quantitative formulation of welfare is never final because it will continue to evolve along with the development needs of human life. In 2011, the National Team for the Acceleration of Poverty Reduction (NTAPR) made priority sector that can serve as a benchmark the welfare in a region. From the priority sector will be made cluster or group which contains all 33 provinces based on the level of public welfare in the region uses data in 2012 were sourced from the Central Statistics Agency (CSA). The method that can be used to group the 33 provinces is K-Means Cluster method with number cluster as many as two, three, four, and five clusters. K-Means Cluster method is one of cluster analysis method who can partition the data into one or more clusters, so that the data with the same characteristics are grouped into the same cluster and data with different characteristics grouped into other clusters. To know the most optimal of the number of clusters we use Davies-Bouldin Index (DBI). We concluded that the optimal number of cluster is three with details the province in the first clusters have superiority in four sectors like net enrollment rate of primary school, net enrollment rate of junior high school, IMR (Infant Mortality Rate), and access to electricity. The province in the second clusters have superiority in one sector, that is open unemployment rate. The province in the third clusters have superiority in all sectors. Keywords: Welfare, NTAPR Priority Sector, K-Means Cluster Method, Davies-.Bouldin Index (DBI)

Co-Authors Abdul Hoyyi Agus Rusgiyono Alan Prahutama Alvita Rachma Devi Anifa Anifa Anissa Pangastuti Arief Rachman Hakim Bella Cynthia Devi Bramaditya Swarasmaradhana Budi Warsito Bunga Maharani Catra Aditya Wisnu Aji Chainur Arrasyid Hasibuan Cyntia Surya Utami Dedy Douglas Harianja Desy Trishardiyanti Adiningtyas Diah Safitri Dwi Ispriyanti Dyan Anggun Krismala Elyas Darmawan Endah Cahyaningrum Erna Fransisca Angela Sihotang Erna Puspitasari Etik Setyowati Fatma Septy Deviana Fitra Ramdhani Hasbi Yasin Herwindhito Dwi Putranto Iantazar Rezqitullah Maharsi Kiki Febri Azriati Laili Isna Nur Khiqmah Landong Panahatan Hutahaean Mardison Purba Marta Widyastuti Muhammad Rizki Naomi Rahma Budhianti Niken Anggraini Dewi Novia Agustina Nunung Hanurowati Nurhikmah Megawati Panji Wisnu Wirawan Rachmah Dewi Kusumah Restu Sri Rahayu Rita Rahmawati Riza Adi Priantoro Shaumal Luqman Solly Aryza Sudarno Sudarno Sugito Sugito Suparti Suparti Syaifudin Karyadi Syarah Widyaningtyas Tatik Widiharih Trianita Resmawati Triastuti Wuryandari Ungu Siwi Maharunti Yosi Dhyas Monica Yuciana Wilandari

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