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Jurnal Gaussian

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Published by Universitas Diponegoro

ISSN : - EISSN : 23392541 DOI : -

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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 9 Documents

Search results for , issue "Vol 2, No 1 (2013): Jurnal Gaussian" : 9 Documents clear

ANALISIS FAKTOR-FAKTOR TINGKAT KEMISKINAN DI KABUPATEN WONOSOBO DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED REGRESSION Permana, Maulana Taufan; Yasin, Hasbi; Rusgiyono, Agus
Jurnal Gaussian Vol 2, No 1 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Poverty reduction is the main priority in development strategies in Indonesia, but during this computation is modeled as a function of the poor global regression. That is, the value of the regression coefficient applies to all geographic regions. In reality each region has different characteristics according to the geographical location, therefore Geographically Weighted Regression models are developed (GWR). GWR model is used to consider the element of geography or location as the weighting in estimating the model parameters. In the model GWR model parameter estimation is obtained by using Weighted Least Square (WLS) is to give a different weighting at each location. This study discusses the factors that affect the level of poverty in the District Wonosobo. The results of testing the suitability of the model shows that there is no spatial factors influence the level of poverty in the District Wonosobo. Based on research, there are 3 variables thought to affect the level of household poverty in Wonosobo district, percentage of the number of families that have slums, percentage number of families severely malnourished, percentage of the number of families who have agricultural land. These variables have a similar effect in each district.Keywords: Poverty, Geographically Weighted Regression, Weighted Least Square, Wonosobo

ANALISIS SPASIAL PENYEBARAN PENYAKIT DEMAM BERDARAH DENGUE DENGAN INDEKS MORAN DAN GEARY’S C (STUDI KASUS DI KOTA SEMARANG TAHUN 2011) Nuril Faiz; Rita Rahmawati; Diah Safitri
Jurnal Gaussian Vol 2, No 1 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Dengue Haemorrhagic Fever (DHF) is an infectious disease transmitted by the mosquito Aedes aegypti through its the virus dengue virus from patient to another via the bite. Rate dependence dengue in an area estimated to be affected by dengue fever in other neighboring areas. The statement was supported by the First Law of Geography expressed Tobler that all things related to everything else, but near things are more related than distant things. Therefore, if a dengue endemic area, the suspected region make the area immediately adjacent to endemic dengue with a new one. The purpose of this study was to determine whether there is spatial autocorrelation in the spread of dengue fever in the city of Semarang. Limited to methods index and Geary's C Moran and mapping the spread of dengue fever in the city of Semarang with respect to the location (district) in 2011. Of the two methods used showed a pattern of spread of Dengue Hemorrhagic Fever (DHF) are spatially in Semarang and show positive spatial autocorrelation, indicating a nearby location to have similar values, and tend to cluster. Keyword: Dengue Hemorrhagic Fever (DHF), Spatial, Moran Index, Geary’s c.

PEMILIHAN MODEL REGRESI LINIER MULTIVARIAT TERBAIK DENGAN KRITERIA MEAN SQUARE ERROR Aminuddin Aminuddin; Sudarno Sudarno; Sugito Sugito
Jurnal Gaussian Vol 2, No 1 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Regresi linier multivariat merupakan salah satu metode analisis regresi yang melibatkan lebih dari satu variabel respon, dengan model regresinya adalah . Penggunaan banyak variabel dalam analisis regresi linier multivariat dapat menjadi hal yang menyulitkan untuk menentukan besarnya pengaruh variabel prediktor terhadap variabel respon. Oleh karena itu, dilakukan penyeleksian variabel guna mendapatkan model regresi terbaik. Prosedur seleksi variabel dengan kriteria Mean Square Error (MSE) merupakan suatu metode untuk mendapatkan model terbaik dengan cara mencari model yang memiliki nilai MSE terkecil dari seluruh model yang mungkin

ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI KEPUTUSAN PEMBELIAN DAN KEPUASAN KONSUMEN PADA NOTEBOOK MEREK ACER (Studi Kasus Mahasiswa Universitas Diponegoro) Koko Arie Bowo; Abdul Hoyyi; Moch. Abdul Hoyyi
Jurnal Gaussian Vol 2, No 1 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Consumer perception about notebook product is a variated, this condition based on consumer need is referred that will exploit existing facility at a notebook. Generally, consumer buys a notebook product based on some considerations for example price, brand and product quality. If the product that the of exceed its expectation, consumer will satisfied and possibility will submit the good things about the products to others people. This research aims to analyze the factors that have an effect on purchasing decisions and consumer satisfaction on Acer notebook. Data collecting in this research use questionnaire , that was distributed to 110 students from Diponegoro University that have a Acer notebook.Technique sample uses accidental sampling method. The data obtained are then analyzed using Structural Equation Modeling (SEM). Based on research result is obtained that brand image not has an effect on to purchasing decision Acer notebook, while the product quality and price have an effect on purchasing decision Acer notebook. Despitefully also, the product quality and purchasing decision Acer notebook have an effect on consumer satisfaction. Keywords: brand image, price, quality product, purchasing decision, consumer satisfaction.

ESTIMASI PARAMETER REGRESI LOGISTIK MULTINOMIAL DENGAN METODE BAYES Wayaning Apsari; Hasbi Yasin; Sugito Sugito
Jurnal Gaussian Vol 2, No 1 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Multinomial logistic regression is a logistic regression where the dependent variable is polychotomous is dependent variable value of more than two categories. Multinomial logistic regression parameter estimation usually use classical method that is based only on current information obtained from the sample without taking into account the initial information of logistic regression parameters. If have early information about parameter is prior distribution, the parameter estimation can use Bayes method. Bayesian methods combine information on the sample with prior distribution of information, and the results are expressed in the posterior distribution. If posterior distribution can not be derived analytically so approximated using Markov Chain Monte Carlo (MCMC) algorithm especially Metropolis-Hastings algorithm. This algorithm uses acceptance and rejection mechanism to generate a sequence of random samples. Keyword: Multinomial Logistic Regression, Bayes Method, Markov Chain Monte Carlo algorithm (MCMC), Metropolis-Hastings algorithm.

ESTIMASI KANDUNGAN HASIL TAMBANG MENGGUNAKAN ORDINARY INDICATOR KRIGING Aldila Abid Awali; Hasbi Yasin; Rita Rahmawati
Jurnal Gaussian Vol 2, No 1 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Kriging is a geostatistical analysis of the data used to estimate the value that represents a no sample point based sample point in the surrounding by considering the spatial correlation in the data. Kriging is an interpolation method that generates unbiased predictions or estimations and has a minimum error. Indicator kriging is an estimation method that does not require the assumption of normality of data and can also be used to treat data that have a significant outlier. The indicator kriging that based on the principle of ordinary kriging also called ordinary indicator kriging. In this case study conducted Morowali estimated iron content in Central Sulawesi using ordinary indicator kriging method. The data used in the form of data coordinate point and iron content. The results obtained are presented probability value locations that fall within the zone of potential and non potential with the value the error variance. Based on the analysis to obtain a plot depicting the location of the entry in the zones of potential iron mine on the abscissa coordinate (7150–7210), the ordinate (54180–54540), and the depth ranges (440–500) meters and also the coordinates of the abscissa (7710–8130), the ordinate (54800–54960), and depths ranging from (327–342) meters.

ANALISIS INTERVENSI DAN DETEKSI OUTLIER PADA DATA WISATAWAN DOMESTIK (Studi Kasus di Daerah Istimewa Yogyakarta) Lenny Budiarti; Tarno Tarno; Budi Warsito
Jurnal Gaussian Vol 2, No 1 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The tourist data is very interesting to be studied because the Indonesian tourism sector is an activator of the national economic which is potential to push higher economic growth in the future. Therefore, the forecast about tourist data is very needed for tourism business. The tourist data tend to fluctuate caused by many factors that affect the number of tourists extremely in an area, such as disasters, government regulation, social stability, violence and terrorism. That the extreme data can be assessed using intervention analysis and outlier detection. Intervention model is a time series model that can be used to forecast data consist of intervention of internal and external factors. In the intervention model, there are two kinds of intervention function, i.e., step and pulse functions. Step function is a form of intervention occurred in period of time while the pulse function is a form of intervention occurred only in a certain time. For the outlier detection, there are four types, such as additive outlier (AO), innovational outlier (IO), level shift (LS) and temporary change (TC). As an empirical studies was conducted by the domestic tourists data in Yogyakarta from January 2006 until December 2010 who staying on five-star hotels and motel throughout Yogyakarta. Based on the result of this research, known that the intervention occurred on January 2010 using the pulse function with MSE value 1172. Meanwhile based on the outliers detection, known any five outliers but only four outliers that significant included to the intervention model with MSE value 523,7167. So, the intervention model and outlier detection are chosen as a the best model based on the smallest MSE criterion. Keywords: Domestic tourists, intervention model, pulse function, outlier detection

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.

ANALISIS PEMILIHAN MEREK TELEPON SELULER PADA MAHASISWA UNIVERSITAS DIPONEGORO DENGAN METODE REGRESI LOGISTIK POLITOMUS Maralika Yundya Sari; Triastuti Wuryandari; Yuciana Wilandari
Jurnal Gaussian Vol 2, No 1 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Telepon seluler (ponsel) merupakan alat telekomunikasi dua arah yang memiliki mobilitas sangat tinggi. Merek-merek ponsel yang beredar di Indonesia yaitu Nokia, Blackberry, Samsung, Sony Ericsson, merek China dan merek lain. Faktor-faktor yang diduga mempengaruhi mahasiswa Universitas Diponegoro dalam membeli sebuah merek ponsel adalah usia, jenis kelamin, nama merek, harga, fitur, desain dan gaya serta kinerja. Pengambilan sampel penelitian menggunakan salah satu teknik dari non probability sampling, yaitu teknik purposive sampling. Untuk menganalisis permasalahan ini digunakan analisis regresi logistik politomus. Berdasarkan uji signifikansi model dan parameter, diketahui usia, nama merek, harga, fitur, desain dan gaya serta kinerja berpengaruh terhadap pemilihan merek ponsel. Estimasi probabilitas terbesar untuk merek Nokia, Blackberry, Samsung, Sony Ericsson, merek China dan merek lain masing-masing adalah sebesar 96.83%, 94.26%, 86.98%, 93.45%, 86.07% dan 99.99%. Kata Kunci: ponsel, purposive sampling, regresi logistik politomus

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