Diah Safitri
Universitas Diponegoro

Published : 61 Documents
Articles

ANALISIS CLUSTER PADA KABUPATEN/KOTA DI JAWA TENGAH BERDASARKAN PRODUKSI PALAWIJA Safitri, Diah; Widiharih, Tatik; Wilandari, Yuciana; Saputra, Arsyil Hendra
MEDIA STATISTIKA Vol 5, No 1 (2012): Media Statistika
Publisher : Jurusan Statistika FSM Undip

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (213.891 KB) | DOI: 10.14710/medstat.5.1.11-16

Abstract

Production of palawija, namely maize, cassava, sweet potato, peanut, soybean, and green bean is an important food crop in Central Java. In this article, districts/cities in Central Java are grouped into three groups based on the production of palawija so as to know which group have high potential the production of maize, cassava, sweet potato, peanut, soybean or green bean by using k-means cluster analysis. Cluster 1 consists of District Cilacap, Wonosobo, Magelang, Karanganyar, Semarang, Temanggung, Kendal, and Batang that have a high potential in maize production. Cluster 2 consists of District Banyumas, Purbalingga, Banjarnegara, Kebumen, Purworejo, Boyolali, Klaten, Sukoharjo, Sragen, Blora, Rembang, Pati, Kudus, Jepara, Demak, Pekalongan, Pemalang, Tegal, Brebes, Magelang City, Surakarta City, Salatiga City, Semarang City, Pekalongan City, and Tegal City  that have a high potential in peanut production. Cluster 3 consist of District Wonogiri and Grobogan that have a high potential in soybean production, green bean production, cassava production, and sweet potato production
ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI KESEMBUHAN PASIEN PENYAKIT FLU BURUNG Wilandari, Yuciana; Safitri, Diah
MEDIA STATISTIKA Vol 2, No 1 (2009): Media Statistika
Publisher : MEDIA STATISTIKA

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Abstract

Avian influenza is contagion which caused by influenza virus type H5N1 often cause death. Avian influenza anticipated to be influenced by gender, age, epidemiology and case, to know the factors have a significant effect used by independent test. is later on made model of regresi binary logistics. Then obtained by factor having an effect is case and epidemiology, that is made regression logistics model. Someone which including case of suspect to be able to have probability recover bigger than someone which including confirmation case, someone which contact with dead an avian to be able to have probability  recover smaller than someone which no contact.
ANALISIS KORELASI KANONIK PADA PERILAKU KESEHATAN DAN KARAKTERISTIK SOSIAL EKONOMI DI KOTA PATI JAWA TENGAH Safitri, Diah; Indrasari, Paramita
MEDIA STATISTIKA Vol 2, No 1 (2009): Media Statistika
Publisher : MEDIA STATISTIKA

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Abstract

One of the general problem that is social and economics which not yet flatten and still meeting of low health case. To know the correlation between social and economics characteristic and behavior of health in Pati of Central Java is used the canonical correlation analysis. The variable that is taken are  social and economics characteristic and behavior of health variable, which each  consisting of nine indicator variable. Some assumptions like linearity, normal multivariable and do not multicolinearity should be fulfilled. After the assumption have fulfilled, data processing can be done so that obtained a conclusion. The result of canonical correlation analysis indicate that there is a signifikan correlation between social and economics characteristic variable and behavior of health variable. From nine indicator which forming variable of social and economics characteristic, earnings indicator variable, education of mother, expenditure and education of father giving the most dominant of contribution. While from nine behavior of health variable, indicator of balanced nutrient variable, physical activity, eradication of mosquito den, house floor, exclusive ASI, and brush teeth giving the most dominant of contribution.   Keywords   :     Social and Economics Characteristic, Behavioral of Health, Canonical Correlation Analysis
ANALISIS KLASTER UNTUK SEGMENTASI PEMIRSA PROGRAM BERITA SORE STASIUN TV SWASTA Rosiatun, Aan; Widiharih, Tatik; Safitri, Diah
MEDIA STATISTIKA Vol 3, No 2 (2010): Media Statistika
Publisher : MEDIA STATISTIKA

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Abstract

A procedure market segmentation is designing the market segmentation use the method of cluster k-means analyze which applied in process designing the market evening news audiences on  tv chanels. The process of grouping audiences into each segment which  formed, based on likeness of characteristic owned and it formed 3 market segment evening news audiences, that is audiences group who give low evaluation, audiences group who give enough evaluation, and audiences group who give high evaluation. Result from the market segmentation with case study at Pangkah district Tegal regency got first cluster is 25.2 %, second cluster is 46 %, and third cluster is 28.8 %. Marketing strategy can target be old > 20 years because it has members total of cluster is biggest. The result can be used by a television company to determine marketing strategy.   Keywords: Characteristic, Market Segmentation, Cluster K-Means Analysis
KOMPONEN UTAMA UNTUK PENGENDALIAN KUALITAS SECARA STATISTIK Nurhasanah, Nunik; Safitri, Diah
MEDIA STATISTIKA Vol 3, No 1 (2010): Media Statistika
Publisher : Jurusan Statistika FSM Undip

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (400.162 KB) | DOI: 10.14710/medstat.3.1.9-20

Abstract

Statistically Quality Control is a problem solving technique that used to check, control, analyze, bring off and repair product with statistical methods. One of the method that used statistically control quality is Principal Component Analysis. Principal Component Analysis is a multivariate technique that used to reduce the dimension of data. Principal component is concerned with explaining the variance-covariance structure of a set of variables through a few linear combinations of these variables. Statistically quality control with principal components is used by constructing multivariate control charts which consist of Ellipse Chart for first two principal components and  Chart for unexplained principal components in Ellipse Chart.   Keywords : Principal Component Analysis, Ellipse Chart,  Chart
Model Dinamik Pertumbuhan Ekonomi Indonesia Pasca Krisis Moneter: Suatu Pendekatan Koreksi Kesalahan (Model Koreksi Kesalahan) I Marudani, Di Asih; Wilandari, Yuciana; Safitri, Diah
JURNAL SAINS DAN MATEMATIKA Volume 15 Issue 1 Year 2007
Publisher : JURNAL SAINS DAN MATEMATIKA

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Abstract

ABSTRACT---Salah satu perkembangan utama pada spesifikasi dinamis adalah Error Correction Model (ECM). ECM dapat dipakai untuk menjelaskan mengapa pelaku ekonomi menghadapi ketidakseimbangan (disequilibrium). Secara khusus, Teorema Representasi Gramger menyatakan bahwa ECM dapat dikatakan valid jika memuat himpunan variabel yang memenuhi uji kointegrasi. Pada hubungan keseimbangan antara xt dan yt adalah : yt = β0 + β1 xt maka dari penurunan rumus diperoleh Error Correction Model : ∆ yt= b1 ∆ xt – λ (yt-1 - β0 - β1 xt-1) + et 0 < λ < 1 Pada penelitian ini, akan diselidiki faktor-faktor yang mempengaruhi pertumbuhan ekonomi Indonesia pasca krisis moneter, yaitu periode 1997(III) – 2004(IV), sebagai studi kasus. Hasil empiris digunakan untuk menyelidiki efek jangka pendek dan jangka panjang dari variabel-variabel penjelas pada model pertumbuhan ekonomi. Dari hasil analisis diperoleh ECM : ∆ln(ĝdp)t = 0.004633 – 0.954748∆ln(kre)t + 0.397869∆ln(eks)t + 0.046700 ∆ln(fdi)t + 0.286713∆ln(kre)t-1– 0.183157∆ln(eks)t-1 – 0.360344∆ln(fdi) t-1 + 0.34592ECT Dan model jangka panjang yang dihasilkan adalah : ln (ĝdp)t= 0.013418 + 1.828841 ln(kre) + 0.470522 ln(eks) – 0.041697 ln (fdi) Kata kunci : Model Koreksi Kesalahan, kointegrasi, stasioneritas
PENDETEKSIAN INFLUENTIAL OBSERVATION PADA MODEL REGRESI LINIER MULTIVARIAT MENGGUNAKAN JARAK COOK TERGENERALISASI (STUDI KASUS INDIKATOR PENDIDIKAN PROVINSI JAWA TENGAH TAHUN 2010) Ekacitta, Puti Cresti; Safitri, Diah; Wuryandari, Triastuti
Jurnal Gaussian Vol 1, No 1 (2012): Wisuda Periode Oktober 2012
Publisher : Jurusan Statistika UNDIP

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Abstract

Multivariate linear regression model is regression model with one or more response variable and one or more predictor variable, with each response variable are mutually. In multivariate linear regression model sometimes often found Influential Observation. Influential Observation give most contributing in estimating regression coefficient. For detection Influential Observation on multivariate linear regression model is used Generalized Cook’s Distance. The aim of this research is to detection any or not any Influential Observation on multivariate linear regression model of education indicator in Central Java Province with response variable are Gross Participation Rate (APK), School Participation Rate (APS), and Pure Participation Number (APM) and predictor variable is percentage of population aged 10 years and over who graduated from junior high school. Result from this research  can be explained that if the percentage of population aged 10 years and over who graduated from junior high school increase one percent, it will have an impact on increasing gross participation rate the junior high school is 1.7849 % , increasing school participation rate is 1.6275 % and   increasing pure participation number is 1.3712 %. Also, from this results were obtained two observations are included Influential observation. Elimination of the two observations are included Influential observation in the multivariate linear regression model of education indicators in Central Java, affects the regression coefficients change only and does not have a major impact on the closeness of the relationship between response variables and predictor variables in the multivariate.
ANALISIS REGRESI LINIER PIECEWISE DUA SEGMEN Syilfi, Syilfi; Ispriyanti, Dwi; Safitri, Diah
Jurnal Gaussian Vol 1, No 1 (2012): Wisuda Periode Oktober 2012
Publisher : Jurusan Statistika UNDIP

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Abstract

Regression analysis is a statistical method that is widely used in research. In general, the regression analysis is the study of the relationship of one or more independent variables with the dependent variable. In analyze the functional relationship between X as the independent variables and Y as the dependent variable, there may be a linear relationship is different for each interval X. If the regression of X on Y has a linear relationship on the certain of the interval of X, but also has a distinct linear relationship at another interval of X, so the use of piecewise linear regression is appropriate in this case. Piecewise linear regression is a method in regression analysis that divided the independent variable into several segments based on a particular value called the X-knots, and in each segment of the data contained linear regression model. X-knot is a value on the independent variable, where X is the current value of the X-knots, it will form a linear regression equation of the line that is different than the current value of X is under X-knots. Piecewise linear regression can be applied in many fields, one of them in the waters of the analysis regarding the influence of river discharge on the basis of the number of transport sediman. By comparison MSE simple linear regression and multiple linear piecewise two segments, the result that the two segments piecewise linear regression is a model that describes the influence of river discharge on the basis of the number of bedload transport
PENGUKURAN VALUE AT RISK MENGGUNAKAN PROSEDUR VOLATILITY UPDATING HULL AND WHITE BERDASARKAN EXPONENTIALLY WEIGHTED MOVING AVERAGE (EWMA) (Studi Kasus pada Portofolio Dua Saham) Putri, Nurissalma Alivia; Hoyyi, Abdul; Safitri, Diah
Jurnal Gaussian Vol 2, No 4 (2013): Wisuda Periode Oktober 2013
Publisher : Jurusan Statistika UNDIP

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Abstract

Investment is an effort to get profits for individual or institution. But the investment policy is always faced with market risk as the effect of financial instruments movement such as stock price movements. Market risk measurement tool commonly used is Value at Risk (VaR), which measures the amount of loss at a certain confidence level. VaR measurement by Hull and White volatility updating procedure is a modification of the historical simulation involving information of volatility change calculated by Exponentially Weighted Moving Average (EWMA). This procedure is fit to financial data such as stock returns that are generally not normally distributed and are heteroskedastic. VaR calculation applied to the portfolio between Kalbe Farma Tbk (KLBF) stock and Lippo Karawaci Tbk (LPKR) stock from 3 January 2011 to 19 April 2013 were selected based on the largest trading volume at the end of the observation for LQ45 stocks listed in the Indonesia Stock Exchange (IDX) . The data used is the return calculated from the closing price of stocks. The validity of VaR was tested through a back test by Kupiec test, and concluded that the 95% VaR and 99% VaR are valid.
REGRESI ROBUST MM-ESTIMATOR UNTUK PENANGANAN PENCILAN PADA REGRESI LINIER BERGANDA Candraningtyas, Sherly; Safitri, Diah; Ispriyanti, Dwi
Jurnal Gaussian Vol 2, No 4 (2013): Wisuda Periode Oktober 2013
Publisher : Jurusan Statistika UNDIP

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Abstract

The multiple linear regression model is used to study the relationship between a dependent variable and more than one independent variables. Estimation method which is the most frequently be used to analyze regression is Ordinary Least Squares (OLS). OLS for linear regression models is known to be very sensitive to outliers. Robust regression is an important method for analyzing data contaminated by outliers. This paper will discuss the robust regression MM-estimator. This estimation is a combined estimation method which has a high breakdown value (LTS-estimator or S-estimator) and M-estimator. Generally, there are three steps for MM-estimator: estimation of regression parameters initial using LTS-estimators, residual and robust scale using M-estimator, and the final estimation parameter using M-estimator. The purpose of writing this paper are to detect outliers using DFFITS and determine the multiple linear regression equations containing outliers using robust regression    MM-estimator. The data used is the generated data from software Minitab 14.0. Based on the analysis results can be concluded that data 21st, 27th, 34th are outliers and equation of multiple linear regression using robust regression MM-estimators is .
Co-Authors Aan Rosiatun Abdul Hoyyi Afianti Sonya Kurniasari Agus Rusgiyono Agustifa Zea Tazliqoh Alan Prahutama Amelia Crystine Anik Nurul Aini, Anik Nurul Annisa Pratiwi, Annisa Arlita, Erna Musri Arsyil Hendra Saputra Artha Ida Sri Anggriyani, Artha Ida Sri Aryono Rahmad Hakim, Aryono Rahmad Aulia Putri Andana, Aulia Putri Bisri Merluarini Budi Warsito Desy Trishardiyanti Adiningtyas, Desy Trishardiyanti Dhinda Amalia Timur Di Asih I Marudani Di Asih I Maruddani Dwi Ispriyanti Esti Pratiwi Evi Yulia Handaningrum Fandi Ahmad Galuh Ayu Prameshti Hasbi Yasin Imam Nur Sholihin Indri Puspitasari, Indri Kishatini Kishartini Lailly Rahmatika, Lailly Mekar Sekar Sari Moch. Abdul Mukid Muhamad Faliqul Asbah Muhammad Abid Muhyidin Muhammad Sunu Widianugraha, Muhammad Sunu Mustafid Mustafid Nariswari Diwangkari, Nariswari Natanael, Dimas Kevin Ndaru Dian Darmawanti Nunik Nurhasanah Nur Musrifah Rohmaningsih, Nur Musrifah Nuril Faiz Nurissalma Alivia Putri Octafinnanda Ummu Fairuzdhiya Onny Kartika Hitasari, Onny Kartika Paramita Indrasari Puti Cresti Ekacitta Rahma Nurfiani Pradita, Rahma Nurfiani Revaldo Mario, Revaldo Ridha Ramandhani, Ridha Rita Rachmawati, Rita Rita Rahmawati Rizal Yunianto Ghofar Rizka Asri Brilliani, Rizka Asri Rose Debora Julianisa, Rose Debora Sherly Candraningtyas Sisca Agustin Diani Budiman, Sisca Agustin Diani Sudarno Sudarno Sugito Sugito Suparti Suparti Syilfi Syilfi Tatik Widiharih Trianita Resmawati Triastuti Wuryandari Tyas Estiningrum Vierga Dea Margaretha Sinaga, Vierga Dea Margaretha Vina Riyana Fitri Wella Rumaenda, Wella Yani Puspita Kristiani, Yani Puspita Yogi Setiyo Pamuji, Yogi Setiyo Yuciana Wilandari