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Jurnal Gaussian

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Published by Universitas Diponegoro

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Jurnal Gaussian terbit 4 (empat) kali dalam setahun setiap kali periode wisuda. Jurnal ini memuat tulisan ilmiah tentang hasil-hasil penelitian, kajian ilmiah, analisis dan pemecahan permasalahan yang berkaitan dengan Statistika yang berasal dari skripsi mahasiswa S1 Departemen Statistika FSM UNDIP.

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Articles 733 Documents

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KLASIFIKASI NASABAH KREDIT BANK “X” DI PROVINSI LAMPUNG MENGGUNAKAN ANALISIS DISKRIMINAN KERNEL Azkiya, Maulida; Mukid, Moch. Abdul; Ispriyanti, Dwi
Jurnal Gaussian Vol 4, No 4 (2015): 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 the credit client which belongs to current credit or bad credit based on the character in credit assessment, such as age, and amount of loan, how long the relationship between company and bank, the period of company, total income, and debt risk of company to the income. Discriminant analysis is a multivariate statistical technique which can be used to classify the new observation into a specific group. Kernel discriminant analysis is a non-parametric method which is flexible because it does not have to concern about assumption from certain distribution and equal variance matrices as in parametric discriminant analysis. The classification using the kernel discriminant analysis with the normal kernel function with optimum bandwidth 0,1 in data of credit client from bank “X” in Lampung Province gives accurate classififcation 92% whereas kernel discriminant analysis with the epanechnikov function with the optimum bandwidth 4,6 gives the accurate classification 79%. Keywords: credit, classification, kernel discriminant analysis

PENERAPAN METODE KORESPONDENSI BERSAMA UNTUK ANALISIS PERUBAHAN PERILAKU PENGGUNA SMARTPHONE Isowedha Widya Dewi; Mustafid Mustafid; Abdul Hoyyi
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Competition is extremely tight in the technology sector including smartphones , the manufacturers compete to satisfy the desire of consumers with a variety of innovations. This study aims is form joint correspondence plot to determine whether consumers switch from one type to the other types of smartphones, as well as knowing what respondents consider when buying a smartphone . By adding a time variable data on methods of joint correspondence, changes in consumer behavior can be determined within a certain time . Time variables used was from 2011 to 2013 and smartphones that will be compared is Blackberry, Android and iOS. From the resulting graph can be seen that many kinds of smartphones used in each time variable and variables that affect the time of purchase . After doing research , showed that smartphone users in 2011, mostly used a Blackberry switched to Android in 2012 and 2013. Blackberry users at the time of puchase paid attention to the brand , color , design , and camera , but did not pay attention to prestige . Android users paid attention to completeness of the application , RAM , data capacity , color , resale price and network coverage . While iOS is not widely used by respondents from 2011 to 2013. iOS users considered the prestige , but did not consider the brand , design and battery life.

PREDIKSI JUMLAH PENUMPANG KERETA API MENGGUNAKAN MODEL VARIASI KALENDER DENGAN DETEKSI OUTLIER (Studi Kasus : PT. Kereta Api Indonesia DAOP IV Semarang) Saputri, Ani Funtika; Hoyyi, Abdul; Sugito, Sugito
Jurnal Gaussian Vol 6, No 3 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Transportation is an inseparable and indispensable part of society in everyday life. Trains became one of the most popular public transportation, especially during the Eid. The shifting of the lunar month of Eid forms a pattern called calendar variation. The calendar variation model is a model that combines the dummy regression model with the ARIMA model. In time series models sometimes there are outliers that can affect the suitability of the model. So that modeling and forecasting method is done using model of calendar variation with outlier detection. Based on the analysis that has been done on the data of the number of passengers of Argo Bromo Anggrek railway, we get the ARIMA model ([11], 0, 1), Dt, Dt-2,t with the addition of 4 outliers as the best model and the resulted forecasting shows increase Railway passengers increase in the months leading up to Eid. Keywords: Train, Calendar Variations, Outlier Detection

ANALISIS SUPPORT VECTOR REGRESSION (SVR) DALAM MEMPREDIKSI KURS RUPIAH TERHADAP DOLLAR AMERIKA SERIKAT Rizky Amanda; Hasbi Yasin; Alan Prahutama
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In economy, the global markets have an important role as a forum for international transactions between countries in selling or purchasing goods or services on an international scale. Money as legal tender in the trading activities, but the problem is the difference between the state of the currency, the exchange rate will be established. Exchange rate is the value of a country's currency is expressed in another country's currency value. Fluctuations in foreign exchange rates greatly affect the Indonesian economy, so the determination of the exchange rate should be beneficial to a country can run the economy well. To predict the exchange rate of the Rupiah against the United States dollar in this study used methods of Support Vector Regression (SVR) is a technique to predict the output in the form of continuous data. SVR aims to find a hyperplane (line separator) in the form of the best regression function is used to predict the exchange rate against the United States dollar with linear kernel and polynomial functions. Criteria used in measuring the goodness of the model is the MAPE (Mean Absolute Percentage Error) and R2 (coefficient of determination). The results of this study indicate that both the kernel function gives very good accuracy in the prediction results of the exchange rate with R2 of 99.99% with MAPE 0.6131% in the kernel linear and R2 result of 99.99% with MAPE 0.6135% in the kernel polynomial. Keyword : Exchange rate, Support Vector Regression (SVR), Hyperplane, Linear Kernel, Polynomial Kernel, ε-insensitive, Accuracy

ANALISIS KERAGAMAN PADA DATA HILANG DALAM RANCANGAN KISI SEIMBANG Diwangkari, Nariswari; Rahmawati, Rita; Safitri, Diah
Jurnal Gaussian Vol 5, No 1 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In a research, it is required a design experiment that obtained a conclusion desired. Balanced Lattices design is an experiment which the number of groups is k, the number of treatment is equal to square of the number of groups (k2) and the number of replication is equal to the number of groups plus one (k+1). In Balanced Lattices design often occurs the missing data. There are two methods estimate missing data. The first method is use equation. The second method is iteration. The second method is used if there was more than one missing data. Analysis of varians in of missing data in Balanced Lattices design is counted as in the complete, but the total degrees of freedom and the error degrees of freedom are substracted by m, respectively where m is the number of missing data. Based on the data used, a research conducted to determine the influence of 16 varieties fertilizer to the product of grain. The result of the research shows that in the case of with one missing data resulting that there is influence of varieties fertilizer to the product of grain with the F count is 5,092. The results of the study with two missing data resulting that there is influence varieties fertilizer to the product of grain with the F count is 4,246. The pairwise test of means by LSD test resulting that the variety fertilizer is varieties fertilizer 14. There is no significant different of the influence with varieties fertilizer 12, 11, 15, 3, 8, 4 and 6. Keywords: Balanced Lattices Designs, Analysis of Varians, LSD Test

ANALISIS PENGARUH KUALITAS LAYANAN DAN KUALITAS PRODUK TERHADAP LOYALITAS PELANGGAN PADA ONLINE SHOP MENGGUNAKAN STRUCTURAL EQUATION MODELING Fina Fitriyana; Mustafid Mustafid; Suparti Suparti
Jurnal Gaussian Vol 2, No 2 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Semakin meningkatnya jumlah pengguna internet membawa dampak yang besar bagi dunia bisnis dengan berbelanja lewat internet sebagai lifestyle. Fenomena ini membuat para pebisnis mulai beralih dari pemasaran tradisional ke pemasaran modern seperti membuka toko online lewat website maupun social media. Penelitian ini bertujuan menganalisa pengaruh kualitas layanan dan kualitas produk terhadap loyalitas pelanggan pada online shop. Model yang dipakai adalah model e-SERVQUAL dan metode analisisnya menggunakan structural equation modeling (SEM). Hasil dari penelitian ini menunjukkan adanya hubungan antara kualitas layanan dan kualitas produk terhadap loyalitas pelanggan pada online shop. Variabel indikator daya tanggap memiliki pengaruh yang paling besar terhadap variabel kualitas layanan pada online shop. Sedangkan, variabel indikator daya tahan memiliki pengaruh yang paling besar terhadap variabel kualitas produk pada online shop.

METODE GENERALIZED MEAN DISTANCE-BASED K-NEAREST NEIGHBOR CLASSIFIER (GMDKNN) UNTUK ANALISIS CREDIT SCORING CALON DEBITUR KREDIT TANPA AGUNAN (KTA) Saraswati, Mei Sita; Mukid, Moch. Abdul; Hoyyi, Abdul
Jurnal Gaussian Vol 8, No 1 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Unsecured Credit is one of the credit facilities provided by banks, where the prospective debtor can borrow some amount of fund from the bank without having to provide collateral. Credit scoring is a process that aims to assess the worthiness of credit applications and classify the credit applicants into prospective debtors whose the credit application is worthy to be accepted and prospective debtors whose the credit application should be rejected. One of the statistical methods that can be applied in examining the analysis of credit scoring is the Generalized Mean Distance-Based k-Nearest Neighbor (GMDKNN) classifier. Empirical study on this method uses 23,337 data of prospective debtor of unsecured credit in 2018, with the dependent variable being the credit scoring final decision and seven independent variables, i.e. age, child dependent, length of employment, age of the company, income, loan proposed, and duration of credit. Based on the feature selection test, all independent variables are significantly taking effect on the credit scoring final decision. The best classification model is obtained in the parameters k = 137 and p = -1 with the classification performance metrics represented by the values of APER = 0,2580, accuracy = 74,20%, sensitivity = 0,6083, specificity = 0,8393, AUC = 0,7238, and G-Mean = 0,7146.Keywords: Unsecured Credit, credit scoring, classification, Generalized Mean Distance-Based k-Nearest Neighbor (GMDKNN).

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

ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI PERSENTASE PENDUDUK MISKIN DI JAWA TENGAH DENGAN METODE GEOGRAPHICALLY WEIGHTED PRINCIPAL COMPONENTS ANALYSIS (GWPCA) ADAPTIVE BANDWIDTH Mas'ad, Mas'ad; Yasin, Hasbi; Maruddani, Di Asih I
Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Poverty is one of the fundamental problems that is faced by developing country such as Indonesia. One of provinces with high poverty in Java is Central Java. The factors affecting poverty in the districts/cities in Central Java are Human Development Index, pre-prosperous family, population density, Labor Force Participation Rate, and Regional Minimum Wage. Variables which is affecting poverty percentage are multivariate data that have spatial effect and are correlated to each other. Therefore, Geographically Weighted Principal Components Analysis (GWPCA) Adaptive Bandwidth is suitable to analyze what dominant factor that effects poverty percentage in the districts/cities in Central Java. GWPCA Adaptive Bandwidth is a multivariate analysis method that is used to remove the correlation in multivariate data that have spatial effects with the distance weighting measure and the extent of location influence relative to each other location conforming to the variance size of data density. The result of this research the variables affecting poverty percentage each region can be replaced by new variables called principal components which can explain 82% of the original variables. This research also found five regional groups that have different poverty-percentage-affecting characterics. Keywords : poverty, multivariate, correlation, spatial effect, GWPCA adaptive bandwidth.

ANALISIS ANTRIAN RAWAT JALAN POLIKLINIK LANTAI 1, LANTAI 3 DAN PENDAFTARAN RSUP Dr. KARIADI SEMARANG Vita Dwi Rachmawati; Sugito Sugito; Hasbi Yasin
Jurnal Gaussian Vol 2, No 4 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Hospital is an organization social and health that provides complete (comprehensive), the healing of disease (curative) and disease prevention (preventive) to the public. Hospital quality can be know from the professionality hospital personnel, efficiency, and effectiveness of services.The duration of registration procedure and service for doctor consultation can affect patient satisfaction of Outpatient Hospital Dr. Kariadi Semarang in obtaining health care. Therefore, it’s necessary queuing models that suitable. so as to obtainable an effective service, balance and efficient which can reduce the long queues and long waiting time. From the analysis, obtainable queuing models at the registration that is (M/M/8):(GD/∞/∞) with the counter number 8 server. In the vct-cst polyclinic and child development polyclinic the model is (M/M/1):(GD/∞/∞) with the number of server 1 doctor while for the nervers polclinic, child health, internal disease, gynecologic and obstetrics, cdc, general surgery, hemodialysis and kb, fertility and the test tube babies that is (M/M/c): (GD/∞/∞) with the number of servers depending on each clinic.

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