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Tatik Widiharih
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PENDEKATAN REGRESI POLINOMIAL ORTHOGONAL PADA RANCANGAN DUA FAKTOR (DENGAN APLIKASI SAS DAN MINITAB) widiharih, Tatik
MATEMATIKA Vol 4, No 1 (2001): JURNAL MATEMATIKA
Publisher : MATEMATIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (56.697 KB)

Abstract

            Pendekatan regresi polinomial orthogonal dapat dilakukan pada rancangan dengan faktor kuantitatif dan jarak antar taraf faktor sama. Pendekatan ini dilakukan bila peneliti ingin menentukan taraf faktor dari masing-masing faktor yang mengoptimalkan respon yang diamati. Penentuan derajat polinomial berdasarkan kontras-kontras orthogonal yang nyata (significant) dari masing-masing faktor, kemudian dapat ditemukan bentuk regresi pendekatannya. Persamaan yang diperoleh merupakan fungsi matematika dengan dua peubah. Dengan menggunakan hitung differensial dapat ditentukan titik ekstrem dari fungsi tersebut. Bila dikembalikan kebentuk rancangan berarti dapat ditentukan taraf faktor dari masing-masing faktor yang mengoptimalkan respon yang diamati.
INFERENSI FUNGSI KETAHANAN DENGAN METODE KAPLAN-MEIER Widiharih, Tatik; Andriani, Nasichah Siska
MATEMATIKA Vol 9, No 3 (2006): JURNAL MATEMATIKA
Publisher : MATEMATIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (79.585 KB)

Abstract

. Let T be a nonnegatif random variable representing the life time of individuals in some population. Life time data of individuals are devided in two kinds, cencored and uncencored data. The probability of an individual surviving till time t is given by the survival function S(t)=P(T≥t). Product Limit estimator (Kaplan-Meier estimator) is a nonparametric method to find the survival function for cencored data.  
PEMILIHAN MEREK LIPSTIK TERFAVORIT DENGAN MADM BERBASIS GUI MATLAB Finisa, Husnul; Widiharih, Tatik; Mukid, Moch. Abdul
Jurnal Gaussian Vol 6, No 3 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (599.957 KB) | DOI: 10.14710/j.gauss.v6i3.19307

Abstract

Lipstick is a cosmetic usually worn by women to improve appearance with apply to the lips. The interest on lipstick among student at indonesia based on the various brands lipstick of national and international land of selling in indonesia. Based on this condition , it takes a method that can evaluate most favorite brand lipstick according to college student .  The method applied to choose most favorite brand lipstick are Simple Additive Weighting (SAW) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Both this method can do the decision to establish an alternative best of a number of alternatives based on a number of certain criteria in overcoming Multi Attribute Decision Making (MADM), The concept of SAW is looking for a sum of the weighted performance rating for each alternative in all criteria. While TOPSIS using the principle that alternative chosen should have the shortest distance of a solution ideal positive and farthest of a solution ideal negative. There are 10 alternative brand lipstick and 10 criteria, the criterias are the price, color, form, packaging, resilience, pigmentation, texture, scent, the availability of code expired lipstick. The result of the research indicated that to the SAW method most favorite  brand lipstick is of NYX and to the TOPSIS method most favorite brand lipstick is Wardah. The research also produce an application programming GUI Matlab that can help users in process data uses the method saw and topsis for an election most favorite brand lipstick.Keywords : GUI,  Lipstick, MADM, SAW, TOPSIS
PEMODELAN B-SPLINE UNTUK MENGESTIMASI KURVA YIELD OBLIGASI PEMERINTAH KODE FIXED RATE Nurcahyanti, Tri Meida; Widiharih, Tatik; Warsito, Budi
Jurnal Gaussian Vol 8, No 2 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (853.178 KB) | DOI: 10.14710/j.gauss.v8i2.26669

Abstract

Bond is a medium-long term loan agreement that can be handed over, it contains a promise from the issuer to pay rewards in the form of interest on a particular period and paying off the principal debt on the time that has been appointed to the bond buyer. A method to find out the relationship between yield and time to maturity for a type of bond at any given time is illustrated through the yield curve. One of the methods for estimating yield curve is B-spline. The data that used to estimate the yield curve with B-spline model are sourced from Indonesia Stock Exchange, namely Government Bond Trading Report with code FR (Fixed Rate). The data periods used are 9, 16, and 23 November 2018. The best model for estimating the yield curve at any period of the data is linear B-spline model with 6 knots but the knot position is different for every data period. Based on the calculation of MAPE, the ability of the model to predict is very good. Investment with maximum profit based on the estimation of yield curve using B-spline linear model with 6 knot is FR0071.Keywords: bond, yield, yield curve, Government Bond, B-spline
METODE k-MEDOIDS CLUSTERING DENGAN VALIDASI SILHOUETTE INDEX DAN C-INDEX (Studi Kasus Jumlah Kriminalitas Kabupaten/Kota di Jawa Tengah Tahun 2018) Nahdliyah, Milla Alifatun; Widiharih, Tatik; Prahutama, Alan
Jurnal Gaussian Vol 8, No 2 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (547.719 KB) | DOI: 10.14710/j.gauss.v8i2.26640

Abstract

The k-medoids method is a non-hierarchical clustering to classify n object into k clusters that have the same characteristics. This clustering algorithm uses the medoid as its cluster center. Medoid is the most centrally located object in a cluster, so it’s robust to outliers. In cluster analysis the objects are grouped by the similarity. To measure the similarity, it can be used distance measures, euclidean distance and cityblock distance. The distance that is used in cluster analysis can affect the clustering results. Then, to determine the quality of the clustering results can be used the internal criteria with silhouette width and C-index. In this research the k-medoids method to classify of regencies/cities in Central Java based on type and number of crimes. The optimal cluster at k= 4 use euclidean distance, where the silhouette index= 0,3862593 and C-index= 0,043893. Keywords: Clustering, k-Medoids, Euclidean distance, Cityblock distance, Silhouette index, C-index, Crime
PERBANDINGAN MODEL ARCH/GARCH MODEL ARIMA DAN MODEL FUNGSI TRANSFER (Studi Kasus Indeks Harga Saham Gabngan dan Harga Minyak Mentah Dunia Tahun 2013 sampai 2015) Fakhriyana, Deby; Hoyyi, Abdul; Widiharih, Tatik
Jurnal Gaussian Vol 5, No 4 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (597.137 KB) | DOI: 10.14710/j.gauss.v5i4.14720

Abstract

Indonesian Composite Index is a value that used to measure the combined performance of shares listed in stock market. Price of crude oil is one of the factors that affect Indonesian Composite Index. If the prices of crude oil is increasing, it will be responsed by Indonesian goverment directly with also increasing the fuel prices, that will have an impact on Indonesian Composite Index. ARIMA  and transfer function are methods of modeling time series data and it have assumption that the residual models have to be homogen. To overcome violations of those assumption, this study continue to modelling ARCH/GARCH with ARIMA and transfer function approach. The data used in this study are daily of Indonesian Composite Index and West Texas Intermediate (WTI) crude oil prices data from 2013 to 2015. This study gained two models, the first is ARIMA (1,1,[3]) which variance model of ARCH(1), it’s AIC value is equal to 7707,4287. The second is transfer fuction model (1,0,0) which noise model ARMA(0,[1,3) as well as variance model ARCH(1), it’s AIC value equal to 7689,18984. The best model is the one that has smallest AIC value. From this study can be concluded that the best of ARCH/GARCH model is ARCH/GARCH model with transfer function approach. Keywords : Indonesian Composite Index, crude oil prices, ARIMA, transfer function, ARCH/GARCH
GUI MATLAB UNTUK METODE FUZZY SAW DAN FUZZY TOPSIS DALAM PEMILIHAN PENERIMA BEASISWA PPA DENGAN PEMBOBOTAN ENTROPI (Studi Kasus : Pemilihan Penerima Beasiswa PPA tahun 2017 Mahasiswa FSM UNDIP, Semarang) Rahmaniar, Ratna; Widiharih, Tatik; Ispriyanti, Dwi
Jurnal Gaussian Vol 7, No 2 (2018): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1374.165 KB) | DOI: 10.14710/j.gauss.v7i2.26653

Abstract

For students, scholarships are important to ease the burden on parents, namely tuition fees.The large number of scholarship applicants is a challenge for FSM to be able to provide an appropriate, effective and efficient decision to manage data on scholarship recipients who are truly entitled to receive scholarships. Prospective scholarship recipients are selected based on the criteria determined by FSM.The criteria determined by the FSM are GPA (Grade Point Average), parent income, number of certificates, number of dependents of parents, semester, and electricity. The method applied to select 170 PPA scholarship recipients (Academic Achievement Improvement) is FSAW (Fuzzy Simple Additive Weighting) and FTOPSIS (Fuzzy Technique for Order Preference by Similarity to Ideal Solution) with entropy weighting. This entropy weighting does                                             a combination of the initial weight that has been determined by FSM and the calculation weight. This research was conducted with the help of MATLAB (Matrix Laboratory)  GUI (Graphical User Interface) as a computing tool. With the MATLAB GUI system built, it can simplify and speed up the selection process. FSAW and FTOPSIS calculation results are 96% the same, while FSAW with FSM is only 39% the same and FTOPSIS with FSM is only 42% the same.The FSAW and FTOPSIS methods are better used than the determination of the FSM, because the results of the FSM are not appropriate.FSM selects manually by looking at files collected by registrants. Keywords:Scholarship, FSAW, FTOPSIS, Entropy, GUI
PEMBENTUKAN KURVA IMBAL HASIL (YIELD) DENGAN MODEL NELSON SIEGEL-SVENSSON (NSS) (Studi Kasus Data Obligasi Pemerintah Periode 27 Oktober 2014 Sampai 31 Oktober 2014) Hutahayan, Eugenia Septri; Widiharih, Tatik; Wilandari, Yuciana
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (693.759 KB) | DOI: 10.14710/j.gauss.v4i3.9430

Abstract

Medium-term debt to long-term contains a promise from the issuer to pay interest in return for a certain period and repayment of the principal debt at a specified time to the purchaser bonds are called Bonds. A method to determine the relationship between the yield (yield) were obtained with the time to maturity for a particular type of bond at a given time is described by the yield curve (yield curve). One method to describe the yield curve is the Nelson Siegel Svensson. Observed data from the Bursa Efek Indonesia (BEI) that the data of Surat Utang Negara (SUN) with code FR (Fixed Rate). In this case the entire SUN FR with a yield is not empty in the period October 27, 2014 to October 31, 2014. Construction of the yield curve on October 27, 2014, October 28, 2014 and October 30, 2014 to form the normal curve (Positive Yield Curve) while the date October 29, 2014 and October 31, 2014 to form the combined curve between the normal curve (Positive Yield Curve) and negative curves (Inverted Yield Curve).Keywords : bond, the yield curve, Government Securities, Nelson Siegel Svensson.
IMPLEMENTASI METODE SAW DAN WASPAS DENGAN PEMBOBOTAN ROC DALAM SELEKSI PENERIMAAN PESERTA DIDIK BARU (Studi Kasus: Madrasah Tsanawiyah (MTs) Negeri Kisaran Kabupaten Asahan Provinsi Sumatera Utara Tahun Ajaran 2018/2019) Nabila, Eva Salsa; Rahmawati, Rita; Widiharih, Tatik
Jurnal Gaussian Vol 8, No 4 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (995.655 KB) | DOI: 10.14710/j.gauss.v8i4.26723

Abstract

Multi Attribute Decision Making (MADM) is one of the decision-making methods to determine the best alternative from a number of alternatives based on certain criteria. There are several methods that can be used to solve MADM problems including Simple Additive Weighting (SAW) and Weighted Aggregated Sum Product Assesmen (WASPAS). Both methods are applied in the selection of prospective new students. In this study, MTsN Kisaran selected 192 students received from 422 registrans and determined certain criteria to get quality students. The criteria determined are the value of the national exam, the value of the Al-Qur'an test, and the value of the academic potential test. The method applied is SAW and WASPAS with the  weighting Rank Order Centroid (ROC). Then a sensitivity analysis is carried out to determine a viable methods selected to obtain optimal results. This research was designed with the help of the Matlab GUI as a computing tool to simplify and accelerate the selection process. Based on the results of the study, the average percentage value of sensitivity for the SAW method was -0.82% while the WASPAS method was -0.87%. With the existence of sensitivity analysis it can be known the most appropriate method for this case is the SAW method.                                                   Keywords: Students, SAW, WASPAS, ROC, Sensitivity, GUI Matlab.
KLASIFIKASI REGRESI LOGISTIK MULTINOMIAL DAN FUZZY K-NEAREST NEIGHBOR (FK-NN) DALAM PEMILIHAN METODE KONTRASEPSI DI KECAMATAN BULAKAMBA, KABUPATEN BREBES, JAWA TENGAH Rismia, Erysta Risky; Widiharih, Tatik; Santoso, Rukun
Jurnal Gaussian Vol 10, No 4 (2021): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v10i4.33095

Abstract

The characteristics of society in choosing contraceptive methods are also the crucial factors for the government to prepare the family planning services needed at Bulakamba District, Brebes Regency, Central Java. In this case, a classification process needs to be done to assist the process of classifying the characteristics of society in the selection of contraceptive methods. Multinomial Logistic Regression classification is good in exploring data information  meanwhile Fuzzy K Nearest Neighbor (FK-NN) classification is good for handling big data and noise. These two methods used in this study because they are relevant to the data applied and will be compared their classification accuracy through APER and Press's Q calculations.The classification accuracy results obtained based on the APER calculation for Multinomial Logistic Regression is 88,25% and Fuzzy K Nearest Neighbor (FK-NN) is 88,92%.  Meanwhile, the Press's Q value of both methods are 9600,945 and 9518,014 greater than χ 2𝛼,1 which is 3,841, so that it is statistically accurate. Based on the results obtained, it can be concluded that Multinomial Logistic Regression classification method has a better classification accuracy than Fuzzy K Nearest Neighbor (FK-NN) method. 
Co-Authors Aan Rosiatun Abdul Hoyyi Alan Prahutama Arsyil Hendra Saputra Budi Warsito Deby Fakhriyana, Deby Di Asih I Maruddani Diah Safitri Dwi Ispriyanti Eugenia Septri Hutahayan, Eugenia Septri Fajar Agung Nugroho Finisa, Husnul Hendi Septianto Mahendra, Ida Bagus Satya Moch. Abdul Mukid Nabila, Eva Salsa Nahdliyah, Milla Alifatun Nasichah Siska Andriani Nurcahyanti, Tri Meida Priyo Sidik Sasongko Putri Milenia, Erin Novela Rahmaniar, Ratna Reihanah, Khalifah Nadya Rieuwpassa, Jessica Athalia Rismia, Erysta Risky Rita Rahmawati Robiah Peni Raharjanti Raharjanti Rukun Santoso Sayekti Dewi Anggraini Sugito - Triastuti Wuryandari Wiwin Mardjiyati Yuciana Wilandari