Garuda - Garba Rujukan Digital

p-Index From 2019 - 2024

0.23

P-Index

This Author published in this journals

All Journal COPING (Community of Publishing in Nursing) Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang

Diah Safitri

Unknown Affiliation

Author-ID : 2977048

Decision Sciences, Operations Research & Management Education Health Professions Nursing Public Health Other

Published : 41 Documents Claim Missing Document

Claim Missing Document

Articles

Title

1 2 3 4

ANALISIS BIPLOT ROW METRIC PRESERVING UNTUK MENGETAHUI KARAKTERISTIK PROVIDER TELEPON SELULER PADA MAHASISWA S1 FSM UNIVERSITAS DIPONEGORO Artha Ida Sri Anggriyani; Diah Safitri; Triastuti Wuryandari
Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Communication is the basis of human interaction. One of the progression in telecommunications is telecommunication tools, e.g. a mobile phone. Usually on every communication tools such as mobile phones are equipped with a provider. The methods used to analyze mobile phone provider is the biplot analysis. Biplot analysis is an analysis which gives a demonstration of the matrix data graphically X into a plot with vector in row matrix X as describing an object, with a vector in column matrix X describing variables. If α = 1 then it is called analysis biplot Row Metric Preserving (RMP). The predictor variable used in this final project is the product, price, promotion and distribution. After analysis biplot, can be known that a two-dimensional graph biplot was able to explain 97,7% of actual data. The nearest competitor for Indosat provider is XL Axiata provider. Indosat provider winning in terms of promotions and distribution, Telkomsel provider winning in terms of products and Hutchison provider winning in terms of price. Keywords: telephone provider, Row Metric Preserving biplot, marketing mix

MODEL REGRESI MENGGUNAKAN LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATOR (LASSO) PADA DATA BANYAKNYA GIZI BURUK KABUPATEN/KOTA DI JAWA TENGAH Aulia Putri Andana; Diah Safitri; Agus Rusgiyono
Jurnal Gaussian Vol 6, No 1 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Gizi buruk adalah bentuk terparah dari proses terjadinya kekurangan gizi yang menahun. Gizi buruk dipengaruhi oleh banyak faktor yang saling terkait. Dalam penelitian ini, dilakukan pemodelan dari faktor-faktor yang mempengaruhi gizi buruk menggunakan metode Least Absolute Shrinkage Selection and Operator (LASSO) dengan algoritma Least Angle Regression (LARS) karena pada faktor-faktor yang mempengaruhi gizi buruk terdeteksi multikolinearitas. LASSO menyusutkan koefisien regresi dari variabel bebas yang memiliki korelasi tinggi menjadi tepat pada nol atau mendekati nol. Koefisien LASSO dicari dengan menggunakan pemrograman kuadratik sehingga digunakan algoritma LARS yang lebih efisien dalam komputasi LASSO. Berdasarkan analisis yang telah dilakukan, model LASSO pada data gizi buruk Kabupaten/Kota di Jawa Tengah tahun 2014 diperoleh pada tahap kedua saat nilai s=0.02 dengan nilai MSE sebesar 0,82977. Disimpulkan bahwa variabel bayi (0-6 Bulan) yang diberi ASI Eksklusif, rumah tangga berperilaku hidup bersih dan sehat, bayi yang mendapat imunisasi Hepatitis B, bayi yang mendapat imunisasi DPT-HB3, rumah dengan sanitasi yang layak, dan rumah dengan air minum sesuai dengan syarat kesehatan berpengaruh terhadap bayi gizi buruk di Jawa Tengah tahun 2014. Kata Kunci: gizi buruk, multikolinearitas, LASSO, LARS

PERBANDINGAN ANALISIS KLASIFIKASI MENGGUNAKAN METODE K-NEAREST NEIGHBOR (K-NN) DAN MULTIVARIATE ADAPTIVE REGRESSION SPLINE (MARS) PADA DATA AKREDITASI SEKOLAH DASAR NEGERI DI KOTA SEMARANG Bisri Merluarini; Diah Safitri; Abdul Hoyyi
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Classification methods have been developed and two of the existing are K-Nearest Neighbor (K-NN) and Multivariate Adaptive Regression Spline (MARS). The purpose of this research is comparing the classification of public elementary school accreditation in Semarang city with K-NN and MARS methods. This research using accreditation data with the result of eight accreditation components in public elementary school that has A accreditation (group 1) and B accreditation (group 2) in Semarang city. To evaluate the classification method used test statistic Press’s Q, APER, specificity, and sensitivity. The best classification results of the K-NN method is when using K=5 because it produces the smallest error rate and obtained information that the correct classification data are 159 and the misclassification data are 9. The best classification result of the MARS method is when using combination BF=32, MI=2, MO=1 because it produces the smallest Generalized Cross Validation (GCV) and obtained information that the correct classification data are 164 and the misclassification data are 4. Based on analyze result, Press’s Q showed that both methods are good as classification or statistically significant to classify the public elementary school in Semarang city based of the accreditation. APER, specificity, and sensitivity showed that classify of public elementary school accreditation in Semarang city using MARS method is better than K-NN method.

PERAMALAN JUMLAH TAMU HOTEL DI KABUPATEN DEMAK MENGGUNAKAN METODE SUPPORT VECTOR REGRESSION Desy Trishardiyanti Adiningtyas; Diah Safitri; Moch. Abdul Mukid
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The purpose of this research is to forecast the number of hotel’s guests in Demak using Support Vector Regression. Support Vector Regression (SVR) is method used for forecasting. Forecasting the number of hotel’s guests in Demak using SVR produce good accuracy for forecasting the training and testing data. Forecasting for the training data generate MAPE value of 10.2806% and forecasting of testing data generate MAPE value of 11.622%.Keywords: Support Vector Regression, hotel, Demak, accuracy, forecasting, training, testing

ANALISIS KELOMPOK DENGAN ALGORITMA FUZZY C-MEANS DAN GUSTAFSON KESSEL CLUSTERING PADA INDEKS LQ45 Lailly Rahmatika; Suparti Suparti; Diah Safitri
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Clustering analysis is a data analysis aimed at determining a group of data based on common characteristics. Grouping method that’s being developed now is fuzzy clustering analysis. Fuzzy clustering algorithm that’s commonly used is the Fuzzy C-Means (FCM) algorithm and developed further by Gustafson Kessel Clustering (GK) which is able to detect groups with different shape than the FCM. This study examines the comparative application of FCM and GK clustering method in a case study, namely grouping in LQ45 based on the shares ratio of Earning Per Share (EPS) and Price Earning Ratio (PER). Determination of the optimal number of groups is done through calculation Xie and Beni validity index.In this research the algorithm FCM and GK will be made using MATLAB software, such as GUI-based application program which can help users to perform clustering analysis. In some cases, the research results showed that GK is better than FCM, specifically in generating the objective function and the standard deviation ratio of the minimum group. Based on the validity index Xie and Beni, it can be concluded that the optimal number of groups are divided into three.Keywords: Categories of Stocks, Fuzzy C-Means, Gustafson Kessel clustering, Xie and Beni index.

VALUASI KUPON OBLIGASI PT. BPD LAMPUNG TBK. MENGGUNAKAN OPSI MAJEMUK CALL ON CALL TIPE EROPA Revaldo Mario; Diah Safitri; Agus Rusgiyono
Jurnal Gaussian Vol 5, No 2 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

A bond is a debt capital market instrument issued by a borrower, who is then required to repay to the lender/investor the amount borrowed plus interest at maturity, and also known as fixed-income securities, and therefore the bond is an attractive investment in the financial sector. Most theories about the financial statistics is based on the bond without coupon bonds. Whereas, in fact most companies issue bonds with a coupon. Option is an agreement or contract which provides the right and not an obligation for the holder of a contract to buy (call option) or sell (put option) a particular asset at a price and time have been set. Underlying assets can be stocks, bonds, warrants and more. One type of option trading is a European type option is an option that can be used only at the time of maturity. The approach used in the valuation of bond coupons is to use the theory of Europe style compound option call on call. European style compound option call on call is the type of European call options with underlying assets are call options. Final project aims to get the value of equity and the value of liabilities on the bonds PT BPD Lampung Tbk with a coupon rate when the bond before maturity (compound option strike price) and a coupon rate of the bond at maturity (the strike price of the call option). The current bond coupon payments prior to maturity was conducted on July 9, 2017 and a coupon payment at maturity conducted on 9 October 2017. Based on the results of data processing with the help of open source software R 3.1.1, the value of the equity is greater than the value of liabilities.Keywords: bond, call option, compound option, coupon bond, equity, liability

PEMODELAN REGRESI LINIER MULTIVARIAT DENGAN METODE PEMILIHAN MODEL FORWARD SELECTION DAN ALL POSSIBLE SUBSET SELECTION PADA JUMLAH KEMATIAN BAYI DAN INDEKS PEMBANGUNAN MANUSIA (IPM) ( Studi Kasus di Provinsi Jawa Tengah Tahun 2013 ) Indri Puspitasari; Abdul Hoyyi; Diah Safitri
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Regression analysis is a statistical analysis that aims to measure the effect of the independent variables to the dependent variable. Multivariate Linear Regression is a regression model that consists of more than one dependent variables and the dependent variables are correlated. The Number of Infant Mortality and Human Development Index (HDI) of Central Java Province in 2013 was influenced by several variables, such as: mean years of schooling and the number of health centers. To analyze the effects of mean years of schooling and the number of health centers to The Number of Infant Mortality and Human Development Index (HDI) can use multivariate linear regression analysis becuase the dependent variables are correlated. Model selection is determined by using the Forward Selection and All Possible Subset Selection. Selection the model by using Forward Selection, first variables that is included in the model is based of independent variable that have the greatest correlation with the dependent variables. For All Possible Subset Selection, model selection is done by modeling all the models that may have formed. AIC criteria is used for determining the model for All Possible Subset Selection. The model which is selected by using Forward Selection and All Possible Subset Selection has the same independent variables, the model with independent variables mean years of schooling and the number of health centers. The error of the model fulfill all of the error assumptions. Based on the model, the value of AIC is 247.8142 and Eta Squared Lambda is 92.22%. Keywords : Multivariate Linear Regression, Forward Selection, All Possible Subset Selection, AIC

ANALISIS PREFERENSI KONSUMEN TERHADAP PRODUK SUSU BERBASIS ANALISIS CONJOINT MENGGUNAKAN METODE PRESENTASI PAIRWISE-COMPARISON (Studi kasus di Beberapa SMP di Kecamatan Banyumanik Kota Semarang) Trianita Resmawati; Moch. Abdul Mukid; Diah Safitri
Jurnal Gaussian Vol 2, No 4 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In this study aims to help producer or milk companies to know and understand consumer preferences for attributes combination of milk products specifically for adolescent. The method used in this study is the conjoint analysis using pairwise-comparison as a method of presentation. In this research, the attributes that used are the type of milk, flavor, packaging, and fat content. The result of this reserach shows that the packaging is the most important attribute between the other attributes with a relative importance value of 56.13%. The second most importance attribute is flavor of milk with a relative importance value of 38.55%. Fat content was ranked in the third place with a relative importance value of 4.28%, and the type of milk as the fourth attribute with a relative importance value of 1.05%. In addition, the stimuli is desired by consumers for milk products specifically for adolescent are condensed milk, chocolate, canned, and non fat.

REGRESI ROBUST MM-ESTIMATOR UNTUK PENANGANAN PENCILAN PADA REGRESI LINIER BERGANDA Sherly Candraningtyas; Diah Safitri; Dwi Ispriyanti
Jurnal Gaussian Vol 2, No 4 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

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 .

KLASIFIKASI KEIKUTSERTAAN KELUARGA DALAM PROGRAM KELUARGA BERENCANA (KB) DI KOTA SEMARANG MENGGUNAKAN METODE MARS DAN FK-NNC Aryono Rahmad Hakim; Diah Safitri; Sugito Sugito
Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Classification method is a statistical method for grouping or classifying data. A good classification method will produce a little bit of misclassification. Classification method has been greatly expanded and two of the existing classification methods are Multivariate Adaptive Regression Spline (MARS) and Fuzzy k-Nearest Neighbor in Every Class (FK-NNC). This study is aimed to compare a classification of Keluarga Berencana participation based on suspected factors that affect them between the methods of MARS and FK-NNC. This study uses secondary data which one is the participation of Keluarga Berencana in Semarang on 2014. Evaluation of errors use an Apparent Error Rate (APER). In the method MARS best classification results is obtained with the combination of BF = 24, MI = 3, MO = 0 for generating a smallest Generalized Cross Validation (GCV) value and the APER is obtained by 19%. While FK-NNC method is obtained the best classification results in k = 3 for generating the greatest accuracy of classification value and APER value is obtained by 22%. Based on APER (Apparent Error Rate) calculation, it shown that the classification of family participation in Keluarga Berencana (KB) programs in Semarang using MARS method is better than FK-NNC method.Keywords: Classification, MARS, FK-NNC, APER, Keluarga Berencana

Co-Authors Abdul Hoyyi Afianti Sonya Kurniasari Agus Rusgiyono Alan Prahutama Amelia Crystine Annisa Pratiwi Artha Ida Sri Anggriyani Aryono Rahmad Hakim Aulia Putri Andana Bisri Merluarini Budi Warsito Desy Trishardiyanti Adiningtyas Dhinda Amalia Timur Di Asih I Maruddani Dimas Kevin Natanael Dwi Ispriyanti Erna Musri Arlita FANDI AHMAD Galuh Ayu Prameshti Hasbi Yasin Indri Puspitasari Lailly Rahmatika Mekar Sekar Sari Moch. Abdul Mukid Muhammad Abid Muhyidin Muhammad Sunu Widianugraha Ndaru Dian Darmawanti Nur Musrifah Rohmaningsih Nuril Faiz Onny Kartika Hitasari Puti Cresti Ekacitta Rahma Nurfiani Pradita Revaldo Mario Ridha Ramandhani Rita Rachmawati Rita Rahmawati Rizal Yunianto Ghofar Rizka Asri Brilliani Sherly Candraningtyas Sisca Agustin Diani Budiman Sudarno Sudarno Sugito Sugito Suparti Suparti Syilfi Syilfi Trianita Resmawati Triastuti Wuryandari Vierga Dea Margaretha Sinaga Vina Riyana Fitri Wella Rumaenda Yani Puspita Kristiani Yogi Setiyo Pamuji Yuciana Wilandari Yufitriana Amir Yulia Irvani Dewi

Title Search

Found 34 Documents Search Journal : Jurnal Gaussian

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 34 Documents
Search
Journal : Jurnal Gaussian