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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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Peramalan Inflasi Menurut Kelompok Pengeluaran Makanan Jadi, Minuman, Rokok dan Tembakau Menggunakan Model Variasi Kalender (Studi Kasus Inflasi Kota Semarang) Berlian, Amanda Lucky; Wilandari, Yuciana; Yasin, Hasbi
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Inflation is rising prices in general and continuously. Inflationary expenditure groups are divided into seven groups, and one group which spending considerable influence current inflation in Indonesia is by expenditure groups, food, beverages, cigarettes and tobacco. This is because the Indonesian people are very consumptive, especially when it coming to Eid. The movement of the month when Eid occurs once in every three years, so that changes raises a calendar variation. Calendar variation method is a method which modifies the dummy regression models with ARIMA models. In this final project, modeling and forecasting of inflation data by type of expenditure, food, beverages, cigarettes and tobacco in Semarang using variations of the calendar with holidays variation effects due to Eid. Based on the analysis and discussion shows that the best calendar variation model is ARIMA (1,0,0), with the forecasting results shows a significant increase of inflation when the month of Ramadan come.Keywords : inflation, calendar variation, the dummy regression, ARIMA

PREDIKSI NILAI KURS DOLLAR AMERIKA MENGGUNAKAN EXPONENTIAL SMOOTHING DENGAN KAJIAN GRAFIK MOVING AVERAGE (MA) DAN EXPONENTIALLY WEIGHTED MOVING AVERAGE (EWMA) (Studi Kasus: Kurs Jual dan Kurs Beli Dollar Amerika) Nova Yanti Gultom; Sudarno Sudarno; Triastuti Wuryandari
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The exchange rate is an exchange between two different currencies, it will receive the value or price comparisons between two currencies. It is to determine the predictive value of the exchange rate in the next period is done by using Exponential Smoothing. The quality control can be done by forming graphics controllers. The exchange rate can be done in small shifts, so the exchange rate can use graphics controller Moving Average and Exponentially Weighted Moving Average (EWMA). At the selling rate is found value trial and error alpha is 0,9 and gamma is 0,01 with value of MAPE is 0,37; MAD is 46,94 and value of MSD is 4515,27. At the buying rate is found value trial and error alpha is 0,84 and gamma is 0,01 with value of MAPE is 0,37; MAD is 46,57 and value of MSD is 4524,48. In the graph MA and EWMA most sensitive is the MA control chart so in the weekly chart MA selling rate with w is 5 and L is 2,8 obtainable UCL is 13132,52; CL is 12654, LCL is 12175,47. On the weekly chart MA buying rate with w is 5 and L is 2,8 obtainable UCL is 13002,08; CL is 12528, LCL is 12053,91. Then the possibility of the exchange rate for the next period will be increased or decreased to the rupiah.Keywords: Exchange Rate, Exponential Smoothing, Graphic control, Moving Average (MA), Exponentially Weighted Moving Average (EWMA).

ANALISIS FAKTOR KONFIRMATORI STRATEGI POSITIONING PASAR MODERN INDOMARET (Studi Kasus Wilayah Tembalang Kota Semarang) Sholihin, Imam Nur; Mustafid, Mustafid; Safitri, Diah
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Indomaret marketing strategy became one of modern market that has significant development in the last five years. Market positioning is one form of marketing strategy that functions to adjust as desired market position of market actors. Positioning has some major elements of the constituent factors of the product, price, place and promotion. Measurement of the magnitude of the influence of each factor were developed with confirmatory factor analysis. This study aims to examine the factors that influence the positioning strategy and the characteristics of the modern consumer market. The method used in the study using confirmatory factor analysis as used multivariate analysis to confirm the hypothesized model. The study was based on a case study on consumer Indomaret modern market in Tembalang, Semarang City. Results of the analysis showed that all the variables are valid and reliable indicators to measure the factors. Can be known as well as some consumer characteristics of a modern market. Among the interested consumer spending in the modern market with regard to the quality of the stuff is good, the existence of a clear price list, inventory as well as an interesting ad.

PEMODELAN REGRESI HECKIT UNTUK KONSUMSI SUSU DI PROVINSI JAWA TENGAH Dwi Asti Rakhmawati; Dwi Ispriyansti; Agus Rusgiyono
Jurnal Gaussian Vol 6, No 3 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In multiple regression if the response variable is dummy variable then it can not be used because it will produce biased and inconsistent estimator. The appropriate method for binary response variables is Heckit Regression. Estimation of Heckit Regression parameter using Two Step Method of Procurement is the selection equation and the result equation. In the selection equation will get new variable that is Invers Mills Ratio. While in Equation Result of new variable of Inverse Mills Ratio is added as independent variable along with other independent variable. Heckit Regression method is applied to household milk consume data obtained from 2015 SUSENAS results as many as 201 households. The response variable used is household expenditure for milk consumption. The independent variables used are the working status of the head of the household, the last education of the head of the household, the number of household members, the number of toddler age in the family and the income of the household.Keywords: Multiple Regression, OLS, Heckit Regression, Two Step Procedure, Milk consumption expenditure.

PERBANDINGAN REGRESI KOMPONEN UTAMA DENGAN REGRESI RIDGE PADA ANALISIS FAKTOR-FAKTOR PENDAPATAN ASLI DAERAH (PAD) PROVINSI JAWA TENGAH Tazliqoh, Agustifa Zea; Rahmawati, Rita; Safitri, Diah
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Assuming violation multicollinearity in classical regression analysis can cause estimator resulting from classical model regression inefficient. Principal components regression and ridge regression are the methods that can be used to overcome the problem of multicollinearity. This research aimed to compare between the principal components regression with ridge regression to tackle the problem of multicollinearity in the analysis of the factors that affect revenue (PAD) of the Central Java province. The data used in this research are data revenue (PAD), and factors that affect the region, such as local tax, retribution, Gross Regional Domestic Products (GRDP) at current prices, Gross Regional Domestic Products (GRDP) at constant prices, population, regional spending. Based on the coefficient of determination value and test on individual regression coefficients, the value of variance inflation factor and correlations sufficiently high among some independent variables so we can conclude the existence of a violation of multicollinearity on analysis factors PAD. Based on standard error resulting from principal components regression and ridge regression show that principal components regression results in a standard smaller error. This shows that principal component regression is better than ridge regression in solving the problem multicollinearity on analysis of factors that affects pad province of central java. Keywords: Multicolinearity, revenue (PAD), Principal Component Regression, Ridge Regression, standard error

PEMODELAN INDEKS PEMBANGUNAN MANUSIA MENGGUNAKAN SPATIAL PANEL FIXED EFFECT (Studi Kasus: Indeks Pembangunan Manusia Propinsi Jawa Tengah 2008 - 2013) Novian Trianggara; Rita Rahmawati; Hasbi Yasin
Jurnal Gaussian Vol 5, No 1 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The success of a country could be seen from the condition of it society. A country needs to have developed society, a way to establish it is by human development. Human development is formed by three basic components, they are long and healthy life, knowledge, and decent living. Some indicators that represent these three components are summarized in one single value, the Human Development Index. This study models the Human Development Index for each city in Central Java using econometric approach by considering the specific spatial effect. The independent variable used were health facilities representing health component, School Participation Rate that represents education component, and Poverty Percentage that represents component of decent living standard. By using Spatial Panel Fixed Effect the best model is Spatial Autoregressive Model (SAR) with the influencing independent variabels are school participation rate and poverty percentage, with R2 of 99.54%.Keyword: HDI, Spatial, Panel, Fixed Effect

PENENTUAN KOEFISIEN KORELASI KANONIK DAN INTERPRETASI FUNGSI KANONIK MULTIVARIAT Asbah, Muhamad Faliqul; Sudarno, Sudarno; Safitri, Diah
Jurnal Gaussian Vol 2, No 2 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Canonical correlation analysis is a useful technique to identify and quantify the linier relationships, involving multiple independent and multiple dependent variable. It focuses on the correlation between a linier combination of the variables in one set independent and a linier combination of the variables in another set dependent. The pairs of linier combinations are called canonical function, and their correlation are called canonical correlation coefficient. The statistical assumptions should be fulfilled are: linearity, multivariate normality, homoscedasticity, and nonmulticollinearity. The use of variable consists of three dependent variable: y1 =Maximum daily relative humidity, y2 = Minimum daily relative humidity, and y3 = Integrated area under daily humidity curve and three independent variable: x1 = Maximum daily air temperature, x2 = Minimum daily air temperature, and x3 = Integrated area under daily air temperature curve. For The result of canonical correlation analysis indicate that there are two significant canonical correlation between the daily air temperature level with the daily humidity level. The reduncancy index showed that the daily humidity level can explained a total of 69 % of the variance in the daily air temperature level, otherwise the daily air temperature level can explained a total 60 % of the variance in the daily humidity level. Interpretations involves examining the canonical function to determine the relative contibution of each of the original variables in the canonical relationships: canonical weights, canonical loadings, and canonical cross loadings showed that the sequence variables which contribute on the independent variate are x1,x3, and x2. Then, the sequence variables which contribute on the dependent variate are y1, y2, and y3.

PENERAPAN METODE SIMPLE ADDITIVE WEIGHTING (SAW) DAN WEIGHTED PRODUCT (WP) DALAM SISTEM PENUNJANG PEMILIHAN LAPTOP TERFAVORIT MENGGUNAKAN GUI MATLAB Abdiel Pandapotan Manullang; Alan Prahutama; Rukun Santoso
Jurnal Gaussian Vol 7, No 1 (2018): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Laptops have become an important requirement for most students is to support educational activities and business activities. The number of brands of laptops or types of laptops that exist makes consumers especially students have their own preferences in choosing a laptop. The method can be used to select the favorite laptop are SAW (Simple Additive weighting) and WP (Weighted Product). Both of these methods are the methods used to solve the problem of MADM (Multi Attribute Decision Making). There are 30 types of laptops that will be used in the selection of the favorite laptops.For the selection criteria for the type of laptop that is priced, RAM (Random Access Memory), HDD (hard drive), a processor, a VGA (Video Graphics Array), weight, color, screen size, service centers, warranty, availability of spare parts, battery capacity, equipped with OS and application software. Selection of the favorite type of laptop is done with the help of MATLAB (Graphical User Interface) GUI (Matrix Laboratory) as a computing tool. SAW method and WP, in this research showed the same results that the most favored type of laptop laptop mode DEL INSPIRON 15Z-5523 with a value preference for SAW method amounted to 0.9518 while the WP method amounted to 0.9511.Keywords: SAW, WP, Laptop, favorite, GUI

PREDIKSI INDEKS HARGA SAHAM GABUNGAN MENGGUNAKAN SUPPORT VECTOR REGRESSION (SVR) DENGAN ALGORITMA GRID SEARCH Septiningrum, Lutfia; Yasin, Hasbi; Sugito, Sugito
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The existence of capital market Indonesia is one of the important factors in the development of the national economy, proved to have many industries and companies that use these institutions as a medium to absorb investment and media to strengthen its financial position. Capital market Indonesia is an emerging market development is very vulnerable to global economic conditions and capital markets of the world. Prediction JCI (Jakarta Composite Index) is necessary to know the great value that will occur in the future so as investors can take the right policy. To predict in this study used a Support Vector Regression (SVR) method to find the hyperplane in the best regression function to predict the closing price of the JCI using a linear kernel function with output in the form of continuous data. Parameter selection cost and epsilon using a grid search algorithm combined with cross validation and obtained best cost 1 and best epsilon 0.1. While the criteria to measure the goodness of the model is MAPE (Mean Absolute Percentage Error) and R2 (Coefficient Determination). The results of this study showed that SVR with linear kernel function provides excellent accuracy in the prediction of JCI with R2 results on training data 98.4% with a MAPE 0.873% while the testing of data R2 90.9% with a MAPE 0.613%.Keywords: JCI, Support Vector Regression (SVR), Hyperplane, Kernel Linear, Grid Search Algorithm, Cross Validation, Accuracy

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

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