Garuda - Garba Rujukan Digital

p-Index From 2021 - 2026

0.751

P-Index

This Author published in this journals

All Journal COPING (Community of Publishing in Nursing) Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang Pendas : Jurnah Ilmiah Pendidikan Dasar Review of Accounting and Taxation Jurnal Riset Ilmu Kesehatan Umum dan Farmasi

Diah Safitri

Unknown Affiliation

Author-ID : 2977048

Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Health Professions Nursing Public Health Social Sciences Other

Published : 44 Documents Claim Missing Document

Claim Missing Document

Articles

1 2 3 4 5

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

DIAGRAM KONTROL MULTIVARIAT BERDASARKAN JARAK CHI-KUADRAT UNTUK QUALITY CONTROL PRODUKSI DI PT ARA SHOES Galuh Ayu Prameshti; Sudarno Sudarno; Diah Safitri
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Shoes are demands required by everyone. As a time changing and increasing demand for shoes, so many competitor shoe factories produce the best shoes for the customer. PT Ara Shoes is a famous shoe factory that has been well known for six decades. To be able to make fairness quality competition shoe factory would have to ability to produce a high quality product. To improve quality and production process is the way to determine whether quality of production is already achieve the minimum standard quality needed by applying the minimum standard quality control system. Control charts based on chi-square distance is a diagram of the control that can be used for multivariate data attributes. Production processes at PT ARA Shoes is divided into 3 stages of the shoe production process, including the process of cutting, process of sewing and assembling process. The cases study examined in this observation is the production process of cutting from January 2012 - October 2013 total applying 22 observations. Based on the research that has been done it is concluded that the production process is not enough controlled in cutting and improvement needed to be done twice, by eliminating observations 4th and 5th.Keywords : shoes charts control, chi-square distance, PT ARA Shoes

PENERAPAN DIAGRAM KONTROL D^2 MAHALANOBIS PADA PROSES PRODUKSI MINUMAN KEMASAN RETURNABLE GLASS BOTTLE (Studi Kasus di PT. Coca-cola Bottling Indonesia Central Java) Muhammad Abid Muhyidin; Diah Safitri; Rita Rahmawati
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Quality being one of the basic factors in choosing a product consumers. Therefore, an industry or a company should always maintain the quality of their products in order to get loyal customers and are able to survive in the competitive market. Coca-cola Bottling Indonesia Central Java Limited Compay is one of the manufacturing company engaged in the beverage packaging industry and always trying to improve the quality for customer satisfaction. Although it has been to improve the quality, there are still defective product because it does not meet the quality characteristics. Monitoring the result of production process aims to determine whether the process is stable or not. Mahalanobis control chartis one of the control charts that can be used to monitor the production mismatch that is multivariate attributes. By using Mahalanobis control chart, beverage production process of returnable glass bottle (RGB) in Coca-cola Bottling Indonesia Central Java Limited Compay based on the characteristics of disability shows that the results have not yet stable and controllable. This is due to Mahalanobis control chartphase II there are 5 observations of 75 observations or 6.66 % identified uncontrolled observations

KLASIFIKASI KELULUSAN MAHASISWA FAKULTAS SAINS DAN MATEMATIKA UNIVERSITAS DIPONEGORO MENGGUNAKAN MULTIVARIATE ADAPTIVE REGRESSION SPLINE (MARS) Rizal Yunianto Ghofar; Diah Safitri; Agus Rusgiyono
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Education is a top priority for today's society. The quality of education can be seen from the learning achievement. There are so many factors that influence learning achievement in this regard graduation, therefore, necessary to identify the most influential factors that will be used to improve the quality of education. This study was conducted to obtain a model that is capable of classifying the data Faculty of Science and Mathematics Diponegoro University Semarang graduation using Multivariate Adaptive Regression Spline (MARS) method. MARS is a nonparametric regression method that can be used for data of high dimension. To get the best MARS models, made possible combinations Basis Function (BF), Maximum Interaction (MI), and Minimum Observation (MO) by trial and error. The best model is the model that is used in combination with BF = 28, MI = 2, MO = 1 because it has the smallest GCV value that is equal to 0,17781. There are three variables that contribute to the MARS model of the variable GPA, majors and gender. As for the variable organization, part time, entry point, and scholarships do not contribute to the model. Obtained misclassification of 20,50%. Press's Q test value indicates that statistically MARS method has been consistent in classifying the data FSM Diponegoro University Semarang graduation.

PENGELOMPOKAN KABUPATEN/KOTA DI PROVINSI JAWA TENGAH BERDASARKAN ANGKA PARTISIPASI PENDIDIKAN JENJANG SMA/MA/PAKET C DENGAN FUZZY SUBTRACTIVE CLUSTERING Onny Kartika Hitasari; Diah Safitri; Suparti Suparti
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Education is one aspect of nation building is very important to realize the human resource development and national character. Awareness of the importance of education can be seen through education enrollment rates. This study aims to classify the enrollment rates in the district / city Central Java. The data used is the Gross Enrollment Rate (GER), Net Enrollment Rate (NER) and School Enrollment Rate (SER) at the district / city in Central Java Province in 2013. The grouping method used in this study is Fuzzy Subtractive Clustering. The results showed that the best cluster grouping enrollment rates in Central Java Province which consists of 4 clusters with value of cluster variant is 0.00749 and radii between 0.35 to 0.50. Keywords: education participation rate, GER, NER, SER, Fuzzy Subtractive Clustering

Co-Authors Abdul Hoyyi Afianti Sonya Kurniasari Agus Rusgiyono Alan Prahutama Amelia Crystine Amir, Yufitriana 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 Erin Padilla Siregar Erna Musri Arlita FANDI AHMAD Galuh Ayu Prameshti Hasbi Yasin Indri Puspitasari Lailly Rahmatika Mekar Sekar Sari Mertika Moch. Abdul Mukid Muhammad Abid Muhyidin Muhammad Sunu Widianugraha Mulyasari, Windu Nana Nofianti, Nana Ndaru Dian Darmawanti Nindy Citroresmi 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 Yulia Irvani Dewi

Title

Found 44 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 44 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 44 Documents
Search