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All Journal Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang

Yuciana Wilandari

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Author-ID : 475549

Decision Sciences, Operations Research & Management Other

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PERBANDINGAN MODEL PERTUMBUHAN EKONOMI DI JAWA TENGAH DENGAN METODE REGRESI LINIER BERGANDA DAN METODE GEOGRAPHICALLY WEIGHTED REGRESSION Kelik Isbiyantoro; Yuciana Wilandari; Sugito Sugito
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

One of the equipments to see the success of the Government in economics field is the economic growth. To see the economic growth of a region, can be seen from the growth of region Gross Domestic Product (GDP). All this time, the economic growth is often modeled by multiple linear regression, whereas the model describes the general conditions. In fact, there are differences such as geographical factor, socio-cultural circumstance, and the other matters. This allows the appearance of spatial heterogenity in the regression parameters, to overcomes it, the OLS (Ordinary Least Square) regression is developed into Georaphically Weighted Regression (GWR). This model is a local linear regression model that generates local estimator model parameters for each point or location where the data is collected. This research discusses the factors that effect the economic growth in Central Java. The model suitability testing result shows that there is no differences in multiple linear regression model and GWR model toward the economic growth in Central Java. Results of the research shows there are three variables that have effect, they are: Total Labor Force, Major MSEs, and the number of markets. The three variables have the same effect in each county / city.

ANALISIS INTERVENSI KENAIKAN HARGA BBM BERSUBSIDI PADA DATA INFLASI KOTA SEMARANG Novia Dian Ariyani; Triastuti Wuryandari; Yuciana Wilandari
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Intervention model is a model of time series data analysis that originally used to explore impact of unexpectedly external events to the observation variable. In this study, an increases subsidized fuel price analysis has done in June 2013 (first step function) and November 2014 (second step function) for Semarang inflation data at January 2007 until January 2015 and purposed to obtain the intervention model and forecast the Semarang inflation for some time later. Based on the result of inflated subsidized fuel price analysis for Semarang inflation data, the resulted model is ARIMA (1,0,0) with first intervention order b = 1, s = 2, r = 0 and second intervention order b = 1, s = 1, r = 0. Furthermore, the model is used to forecast inflation in Semarang for forward some periods.Keywords: ARIMA, intervention analysis, step function, inflation, subsidized fuel.

KOMPUTASI METODE EXPONENTIALLY WEIGHTED MOVING AVERAGE UNTUK PENGENDALIAN KUALITAS PROSES PRODUKSIMENGGUNAKAN GUI MATLAB (STUDI KASUS : PT Djarum Kudus SKT Brak Megawon III) Iyan Antono; Rukun Santoso; Yuciana Wilandari
Jurnal Gaussian Vol 5, No 4 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Control chart is one of tools for quality control of production. control chart is one of tool that can be used to control the quality of production for variable data such as weight of product. However, there is a weakness of control chart, which is sensitivless in detecting small shift of the mean process. Exponentially Weighted Moving Average (EWMA) control chart is one of the quality control tool that can improve the weakness of control chart. EWMA control chart has a weight smoothing parameter (λ) which makes EWMA control chart more sensitive in detecting small shifts the process mean. Each production data will be weighted and past production data will be affected by present production data. EWMA control chart will be used to make a control chart by weight of cigarette data in Brak Megawon III PT Djarum Kudus. In this study, will be established to assist in the GUI Matlab computational EWMA methods chart controller to control the quality of production at PT Djarum Kudus.In this study showed that the most optimum weight refiner which is at a value of 0.6.Keyword : EWMA, Smoothing weight (λ), GUI, Weight of cigarette

PENERAPAN METODE EMPIRICAL BEST LINEAR UNBIASED PREDICTION (EBLUP) PADA MODEL PENDUGA AREA KECIL DALAM PENDUGAAN PENGELUARAN PER KAPITA DI KABUPATEN BREBES Rahayu Ningtyas; Rita Rahmawati; Yuciana Wilandari
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The coming of a policy about regional autonomy makes district government's choices of strategy and policy become crucial and important for it's district's development and prosperity. Indicator that can states this district development is Human Development Index (HDI). One of dimension that being used to predict the value of HDI is the dimensions of decent living, which can be shown from expenditure per capita. Should the samples of expenditure per capita are less than needed, it can cause difficulty to analyze the value of HDI on next level, which is sub-districal HDI. Direct estimaton only will not give enough validity for the results which can cause the increasing value for it's variance. Another method that can be used is small area estimation (SAE) with Empirical Best Linear Unbiased Prediction (EBLUP) method. This estimation uses the information from it's surrounding areas that correlates with the subject's parametrics. The evaluation for the results is done by comparing the value of Relative Root Mean Square Error (RRMSE) from a direct estimation with the RRMSE from an indirect estimation, which is the EBLUP method. Results from EBLUP estimation is better with average of RRMSE of 7,219% than direct estimation's average of RRMSE with 9,361%. Keywords : Expenditure per capita, Small Area Estimation (SAE), Empirical Best Linear Unbiased Prediction (EBLUP)

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

PERBANDINGAN KLASIFIKASI PENYAKIT HIPERTENSI MENGGUNAKAN REGRESI LOGISTIK BINER DAN ALGORITMA C4.5 (Studi Kasus UPT Puskesmas Ponjong I, Gunungkidul) Wella Rumaenda; Yuciana Wilandari; Diah Safitri
Jurnal Gaussian Vol 5, No 2 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Hypertension is a major problem in the world today. In Indonesia prevalence of hypertension is still high. There are two types of hypertension based on cause, primary and secondary hypertension. In this thesis focused on the classification of types of hypertension based on the cause using binary logistic regression and C4.5 algorithms with case studies in UPT Puskesmas Ponjong I, Gunungkidul of October-November 2015. Binary logistic regression is a method that describes the relationship between the response variable and several predictor variables with the variable equal to 1 to declare the existence of a characteristic and the value 0 to declare the absence of a characteristic. C4.5 algorithm is one method of classification of data mining is used to create a decision tree. The predictor variables were used in this thesis are gender, age, systolic blood pressure, diastolic blood pressure, treatment history, as well as diseases and or other complaints. Based on this analysis, classification of hypertension by binary logistic regression method obtained value APER=27,4648% and 72,5352% of accuracy, while the value obtained using the algorithm C4.5 APER=35,9155% and the accuracy 64,0845 %. In two different test proportion was found that there were significant differences of the two methods.Keywords : Types of Hypertension, Classification, C4.5 Algorithm, Biner Logistic Regression, APER

KLASIFIKASI TINGKAT KELUARGA SEJAHTERA DENGAN MENGGUNAKAN METODE REGRESI LOGISTIK ORDINAL DAN FUZZY K-NEAREST NEIGHBOR (STUDI KASUS KABUPATEN TEMANGGUNG TAHUN 2013) Dini Puspita; Suparti Suparti; Yuciana Wilandari
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Indonesian is a country that have a lot of people, its about 250 millions people. Each of they have a family. Family is a group of person who have relationship and responsibility for each other. The characteristic of family is very important in relationship with society. A lot of requirement must to be have in family. Ownership requirement in family can be figure of that family. In case, accuracy of classification about prosperity family in Kabupaten Temanggung 2013th will be analysed, in BKKBN is have 5 level of prosperity family, there are pra prosperity family, prosperity family 1, prosperity family 2, prosperity family 3, and prosperity family 3 plus. Regression Logistics Ordinal method and Fuzzy K-Nearest Neighbor (FK-NN) method be use for analysis this minithesis. From the analysis regression logistics ordinal accuracy of classification have value 80,47%, and FK-NN have value 87,60%. Both of the value accuracy of classification can get conclusion regression logistics ordinal method have a less value than FK-NN. So FK-NN method is a best method for level of prosperity family in Kabupaten Temanggung 2013th.Keywords : Prosperity Family, Regression Logistics Ordinal, Fuzzy K-Nearest Neighbor (FK-NN)

MODEL ASURANSI KENDARAAN BERMOTOR MENGGUNAKAN DISTRIBUSI MIXED POISSON Tina Diningrum; Yuciana Wilandari; Rukun Santoso
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Motor vehicle insurance is a form of protection of motor vehicles owned by the insured. One of the activities in insurance companies is claim. Claim is risk of loss claim is paid by the insurance company to the insured. Analysis of motor vehicle insurance claims typically uses poisson distribution approach. Nevertheless in many cases of motor vehicle insurance claim, the value of variance greater than the mean value. In this case overdispersed has been going on the assumption poisson distribution. If the poisson distribution continued to be used when going overdispersed, so the poisson distribution is inefficient because it affects the error standard. To solve the problem can be used mixed Poisson distribution. This final project used two mixed Poisson distribution which is a mixture of gamma poison known as negative binomial distribution and poisson-exponential mixture known as a geometric distribution. Carried out on the data motor vehicle claim in PT. Jasa Asuransi Indonesia, Semarang branch year 2010 to 2011 it is estimated that of the 100 vehicle type Car policyholders aged <1 year will be 2 claims per year.

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

ANALISIS KEPUTUSAN KONSUMEN MEMILIH BAHAN BAKAR MINYAK (BBM) MENGGUNAKAN MODEL REGRESI LOGISTIK BINER DAN MODEL LOG LINIER (Studi Kasus SPBU 44.502.10 Ketileng Semarang) Lintang Ratri Wardhani; Yuciana Wilandari; Triastuti Wuryandari
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Fuel oil is a fuel derived and/or processed from petroleum. Fuel is often used for motor vehicles among others premium and pertamax. Some recent times has happened several times increase and decrease in fuel prices, even at the beginning of 2015 has happened a new policy on the elimination of fuel subsidies. It affects on fuel consumption, especially consumption of premuim and pertamax. Many factors influence the consumer's decision in choosing a fuel, therefore needs to be analyzed to find out factors influencing consumer decision in choosing a fuel. This study was conducted to determine the factors that influence consumer decisions in choosing a fuel with a binary logistic regression model and the factors that influence the relationship with log linear models. Binary logistic regression is a method of data analysis used to find the relationship between the response variable (Y) that is binary or dichotomous with some predictor variables (X). Log linear models were used to analyze the relationship between categorical variables. Of a binary logistic regression model obtained influential variable is employment, vehicle age and income variable, with the biggest opportunity is 0,78862, is premium consumers with private employment, the age of the vehicle mote than 5 years and the income less than 1.500.000. for log linear models got the biggest opportunity is 0,91259, is premium consumers to the work of civil servant, the age of the vehicle mote than 5 years and the income less than 1.500.000. Keywords : fuel, binary logistic regression model, log linear models

Co-Authors Abdul Hoyyi Adhitya Ronnie Effendie, Adhitya Ronnie Afifah Alrizqi Agus Rusgiyono Aisha Shaliha Mansoer Alfiyatun Rohmaniyah Alif Hartati Ariyo Kurniawan Ayu Hapsari Budi Utami Bayu Heryadi Wicaksono Candra Silvia Dhinda Amalia Timur Diah Budiati Diah Safitri Dini Puspita Dwi Ispriyanti Feby Kurniawati Heru Prabowo Fiki Farkhati Fitrian Fariz Ichsandi Galih Maraseta W H Prasaja Galuh Riani Putri Gita Suci Ramadhani Gustriza Erda Hasbi Yasin Iantazar Rezqitullah Maharsi Icha Puspitasari Indradewa, Rhian Iyan Antono Kelik Isbiyantoro Lintang Ratri Wardhani Maharani Febriana Putri Maralika Yundya Sari Marlia Aide Revani Marta Widyastuti Moch. Abdul Mukid Muh Najib Hilmi Muhammad Fitri Lutfi Anshari Musandingmi Elok Nurul Islam Niken Nindyaiswari Novia Dian Ariyani Prizka Rismawati Arum Rahayu Ningtyas Ratih Binadari Rita Rahmawati Rizki Taher Dwi Kurniawati Rosita Wahyuningtyas Rukun Santoso Safitri Daruyani Siti Lis Ina Atul Hidayah Sudarno Sudarno Sugito Sugito Suparti Suparti Tarno Tarno Tatik Widiharih Taufan Fahmi Tina Diningrum Triastuti Wuryandari Tyas Estiningrum Wasis Wicaksono Wella Rumaenda Yuyun Naifular

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