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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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ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI LAJU PERTUMBUHAN PENDUDUK KOTA SEMARANG TAHUN 2011 MENGGUNAKAN GEOGRAPHICALLY WEIGHTED LOGISTIC REGRESSION Catra Aditya Wisnu Aji; Moch. Abdul Mukid; Hasbi Yasin
Jurnal Gaussian Vol 3, No 2 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Geographically Weighted Logistic Regression (GWLR) is a local form of logistic regression where geographical factors considered and it is assumed that the Bernoulli distribution of data used to analyze spatial data from non-stationary processes. This research will determine the factors that affect the Population Growth Rate (PGR) in the Semarang city using logistic regression and GWLR with a weighting function of bisquare kernel and gaussian kernel. The result showed that GWLR model with a weighting function of bisquare kernel better than logistic regression model and GWLR model with a weighting function of gaussian kernel because it has the smallest AIC value and classification accuracy is 87,5%. Factor that have significant effect is the number of couples of childbearing age in the Semarang city.

IDENTIFIKASI VARIABEL YANG MEMPENGARUHI BESAR PINJAMAN DENGAN METODE POHON REGRESI (Studi Kasus di Unit Pengelola Kegiatan PNPM Mandiri) Shaumal Luqman; Moch. Abdul Mukid; Abdul Hoyyi
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Most people need a loan to fullfil their daily needs, such as a loan of goods or money. Loan can be obtained from financial institutions or individuals. In order to the loan granted by a financial institutions is not wrong target, financial institutions usually apply precaution principle. In making decisions related to how much a decent loan granted to a customer, the financial institutions often use the help of statistical methods. One methods often used is the Classification and Regression Trees (CART). Classification and Regression Trees (CART) is a nonparametric method that can be used to identify the variable that affect the amount of the loan at a financial institutions and estimate how much worth of loans granted. Because of the loan is a continous variable so the form of the tree is a Regression Tree. In this thesis, the financial institutions is UPK PNPM Mandiri Mekar Sejati in Kecamatan Bawang Kabupaten Batang. Variables that may be affected for large loans are age, occupation, type of warranty, the number family members, and the average income per month. The analysis showed that the variables that most influence on the income of the loans. Mean Absolute Percentage Error (MAPE) value from this method is 36%.Keyword : Regression tree, CART, Large loans.

ANALISA FAKTOR-FAKTOR YANG MEMPENGARUHI KINERJA PERUSAHAAN MENGGUNAKAN PENDEKATAN PARTIAL LEAST SQUARE (Studi Kasus pada PT. Telkom Indonesia Divisi Regional Jawa Tengah-DIY dan Wilayah Telekomunikasi Semarang) Endah Cahyaningrum; 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

Persaingan dalam pasar global membawa banyak perubahan yang cukup dinamis pada semua aspek di suatu perusahaan. Hal ini menimbulkan trend baru dimana perusahaan yang berkelanjutan bergantung pada kemampuan perusahaan dalam merespon perubahan-perubahan yang ada secara efektif. Adanya sejumlah keunikan yang menjadi karakteristik sebuah perusahaan dan tidak dimiliki perusahaan lain dapat menciptakan faktor-faktor yang dapat meningkatkan suatu kinerja perusahaan. Faktor-faktor yang mempengaruhi kinerja perusahaan pada PT. Telkom Indonesia diungkapkan secara komprehensif dengan persamaan struktural berbasis komponen, Partial Least Square (PLS). PLS merupakan metode analisis yang tidak didasarkan pada banyak asumsi. Pada PLS tidak diperlukan asumsi normal multivariat, dapat menggunakan skala pengukuran nominal, ordinal, interval dan rasio serta ukuran sampel tidak harus besar. PLS mengestimasi model hubungan antar variabel laten dan variabel laten dengan indikatornya. Berdasarkan hasil analisis diperoleh kesimpulan bahwa kinerja perusahaan dipengaruhi oleh kinerja manajerial, keunggulan bersaing, Total Quality Management, kompensasi, sistem pengukuran kinerja dan budaya kualitas namun angkanya relatif kecil. Kata kunci : Partial Least Square, kinerja perusahaan

PERBANDINGAN DISKRIMINAN KUADRATIK KLASIK DAN DISKRIMINAN KUADRATIK ROBUST PADA KASUS PENGKLASIFIKASIAN PEMINATAN PESERTA DIDIK (Studi Kasus di SMA Negeri 1 Kendal Tahun Ajaran 2014/2015) Laili Isna Nur Khiqmah; Moch. Abdul Mukid; Alan Prahutama
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Discriminant is a multivariate statistical technique that can be used to perform the classification new observation into a particular group. Quadratic discriminant analysis tied to an assumption of normal multivariate distributed observations and variance covariance matrix inequality. Robust quadratic discriminant analysis can be used if the observations contain outliers. Classification using robust quadratic discriminant analysis with the Minimum Covariance Determinant (MCD) estimator in the data specialization students of SMA Negeri 1 Kendal that containing outliers gives the results of the classification accuracy of 95,06% with a percentage of 4,94% classification error while generating the classical quadratic discriminant analysis classification accuracy of 92,59% with a percentage of 7,41% classification error. Thus a robust quadratic discriminant analysis with the MCD estimator is more appropriate in the case of the data which contains outliers. Keywords : discriminant, outliers, robust, MCD estimators, classification

SEGMENTASI PASAR PADA PUSAT PERBELANJAAN MENGGUNAKAN FUZZY C-MEANS (STUDI KASUS: RITA PASARAYA CILACAP) Nurhikmah Megawati; Moch. Abdul Mukid; Rita Rahmawati
Jurnal Gaussian Vol 2, No 4 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

RITA Pasaraya Cilacap is the first supermarket in Cilacap. Previously, RITA Pasaraya become a shopping center for all people in Cilacap. Now, more and more supermarket is standing. To find this target, RITA Pasaraya needs grouping or market segmentation. Grouping method used fuzzy cluster means (FCM). For an optimal cluster number using the accuracy of the measurement criteria is Xie Beni Index. Research data obtained by questionnaire on RITA Pasaraya Cilacap with 10 psikografik variables. Results of the research, consumer segmentation more accurate if grouped into 2 clusters. The final result is respondents in cluster 1 more attention to low price levels, complete goods, big discounts, satisfactory service, strategic location, roomy parking, comfortable for shopping, adequate public facilities, complete payment facilities, and cleaner room than to respondents in cluster 2. Basically, similar profiles cluster in cluster 1 and cluster 2. Mainly RITA Cilacap Supermarkets are women, with the range age of 16-29 years, with a frequency of shopping 2-4 times per month. Only last education and income are different. In cluster 1, dominated b senior high school with income of 2-5 million every month, and in cluster 2 dominated by bachelor with income <2 million every month.

ANALISIS PENGARUH INFLASI, KURS, DAN SUKU BUNGA SERTIFIKAT BANK INDONESIA TERHADAP INDEKS HARGA SAHAM GABUNGAN MENGGUNAKAN REGRESI LINIER BERGANDA BAYES Marta Widyastuti; Moch. Abdul Mukid; Yuciana Wilandari
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Jakarta Composite Index (JCI) is one of the stock price index emitted by Indonesia Stock Exchange (IDX). JCI is influenced by macro factors (external factors of a company) and micro factors (factors that come within the company). Some of the macro factors include inflation, exchange rate, and interest rate of Bank Indonesia Certificate. To obtain model of inflation, exchange rate, and interest rate of Bank Indonesia Certificate on JCI, Bayesian multiple linier regression can be used so that researcher is able to take into account prior information and apply it together with current data to obtain posterior estimation. From the data processing, it is known that interest rate of Bank Indonesia Certificate is not significantly influencing the model. Meanwhile, inflation and exchange rate are significantly influencing the model and both of them result 72,72% of R-Squared. Furthermore, the final model of Bayesian multiple linier regression proven to be very accurate because it has 4,951% of MAPE. Keywords: JCI, inflation, exchange rate, interest rate of Bank Indonesia Certificate, Bayesian multiple linier regression, prior, posterior, MAPE

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.

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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