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I Putu Eka Nila Kencana
Mathematics Study Program, Faculty Of Mathematics And Natural Sciences, Udayana University
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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PERSEPSI KONSUMEN MINUMAN ISOTONIK DI KOTA DENPASAR I PUTU WINADA GAUTAMA; I PUTU EKA NILA KENCANA; LUH PUTU SUCIPTAWATI
E-Jurnal Matematika Volume 1, No 1, Tahun 2012
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2012.v01.i01.p007

Abstract

Isotonic beverages is a drink that has a composition and the same osmotic pressure of body fluids. One of isotonic fluid and electrolyte replacement for the missing body. The main properties caused by consuming isotonic drinks, among others, to restore power after the move which can be exhausting. Denpasar City community largely has activities/jobs that drain a lot of energy. This condition is asufficient condition for both the isotonic beverage market and have many opportunities to promote its products to the city of Denpasar. Therefore, in this study wanted to know the competition some isotonic drinks brands with a range of variables examined in this case represented the city of Denpasar with Multidimensional Scaling Analysis and using Biplot Analysis of the perceptual mapping.
MEMODELKAN ANGKA GIZI BURUK DI PROVINSI BALI DENGAN PENDEKATAN REGRESI SPASIAL ANAK AGUNG ISTRI AYU PRATAMI; I KOMANG GDE SUKARSA; NI LUH PUTU SUCIPTAWATI; I PUTU EKA NILA KENCANA
E-Jurnal Matematika Vol 10 No 2 (2021)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2021.v10.i02.p328

Abstract

Nutritional problems in toddler are still a serious problem in various districts/cities in Indonesia. The case of malnutrition in Bali Province vary in many regions and hypothesized to be influenced by geographic location, which is often known as spatial heterogeneity. To overcome this problem, a spatial regression method is used on this research. This study aims to model the factors that are hypothesized affect malnourished toddlers in Bali Province using spatial regression methods, i.e. spatial autoregressive model (SAR) and spatial error model (SEM). Both models have 5 predictors variable, i.e. the percentage of toddlers aged between 6 - 59 months who received vitamin A, the percentage of babies with low birth weight (LBW), the percentage of households with clean and healthy living behavior (PHBS), the percentage of children under five receiving exclusive breastfeeding, and the percentage of toddler health services, which are obtained from Bali Provincial Health Office. The results showed SEM method produced smaller AIC value and higher , with and AIC values ??of 96.24% and 60.84, respectively.
KOMPARASI ANALISIS GEROMBOL (CLUSTER) DAN BIPLOT DALAM PENGELOMPOKAN I MADE ANOM ARIAWAN; I PUTU EKA NILA KENCANA; NI LUH PUTU SUCIPTAWATI
E-Jurnal Matematika Vol 2 No 4 (2013)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2013.v02.i04.p053

Abstract

One of functions of multivariate analysis is to group data. Multivariate analysis often used in grouping  data are cluster analysis and biplot analysis. In this paper, a comparative analysis will be made between clusters analysis and biplot analysis  for grouping the data. Technique used in the cluster analysis is k-mean method  and biplot analysis used two-dimensional display.  The results ware that biplot analysis produces are better in grouping accuracy than clusters analysis. But in general, biplot analysis can not be said to be better than clusters analysis in grouping the data and vice versa.
REGRESI KUANTIL MEDIAN UNTUK MENGATASI HETEROSKEDASTISITAS PADA ANALISIS REGRESI IDA AYU PRASETYA UTHAMI; I KOMANG GDE SUKARSA; I PUTU EKA NILA KENCANA
E-Jurnal Matematika Vol 2 No 1 (2013): E-Jurnal Matematika
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2013.v02.i01.p021

Abstract

In regression analysis, the method used to estimate the parameters is Ordinary Least Squares (OLS). The principle of OLS is to minimize the sum of squares error. If any of the assumptions were not met, the results of the OLS estimates are no longer best, linear, and unbiased estimator (BLUE). One of the assumptions that must be met is the assumption about homoscedasticity, a condition in which the variance of the error is constant (same). Violation of the assumptions about homoscedasticity is referred to heteroscedasticity. When there exists heteroscedas­ticity, other regression techniques are needed, such as median quantile regression which is done by defining the median as a solution to minimize sum of absolute error. This study intended to estimate the regression parameters of the data were known to have heteroscedasticity. The secondary data were taken from the book Basic Econometrics (Gujarati, 2004) and analyzing method were performed by EViews 6. Parameter estimation of the median quantile regression were done by estimating the regression parameters at each quantile ?th, then an estimator was chosen on the median quantile as regression coefficients estimator. The result showed heteroscedasticity problem has been solved with median quantile regression although error still does not follow normal distribution properties with a value of R2 about 71 percent. Therefore it can be concluded that median quantile regression can overcome heteroscedasticity but the data still abnormalities.
APLIKASI MULTIVARIATE MULTIPLE REGRESSION UNTUK MENDUGA FAKTOR-FAKTOR YANG MEMENGARUHI KESEJAHTERAAN MASYARAKAT PUTU EKA SWASTINI; I KOMANG GDE SUKARSA; I PUTU EKA N. KENCANA
E-Jurnal Matematika Vol 3 No 3 (2014)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2014.v03.i03.p071

Abstract

This essay aimed to apply the Multivariate Multiple Regression (MMR) methodfor the welfare issue. The predictor variables in the model are 18 indicators of welfare according to Indonesian Central Bureau of Statistic (BPS) and  the response variables are Human Development Index (IPM), Gross Regional Domestic Product (PDRB), and Regional Crime Index (IKD). In modeling the relationship between q responses and a single set of predictor variables , MMR assumed each pairs of two response variables were correlated and its distribution follows normal multivariate. Based on the result of MMR, we obtained six out of 18 predictor variables simultaneously affect IPM and  PDRB. The final model showed the association between those variables very closed to 100 percent.
PERBANDINGAN INTERPOLASI SPASIAL DENGAN METODE ORDINARY DAN ROBUST KRIGING PADA DATA SPASIAL BERPENCILAN (Studi Kasus: Curah Hujan di Kabupaten Karangasem) NI MADE SUMA FRIDAYANI; I PUTU EKA NILA KENCANA; KOMANG GDE SUKARSA
E-Jurnal Matematika Volume 1, No 1, Tahun 2012
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2012.v01.i01.p012

Abstract

Kriging as optimal spatial interpolation can produce less precise predictive value if there are outliers among the data. Outliers defined as extreme observation value of the other observation values that may be caused by faulty record keeping, improper calibration equipment or other posibbilities. Development of Ordinary Kriging method is Robust Kriging which transforms weight of clasic variogram thus become variogram that robust to outlier. The spatial data that used in this research is the spatial data that contains outliers and meet the assumptions of Ordinary Kriging. The analysis showed that the estimation value of Ordinary Kriging and Robust Kriging method is not much different in terms of Mean Absolute Deviation values which generated by both methods. An increase value of Mean Absolute Deviation on Robust Kriging estimation does not indicate that the Ordinary Kriging method is more precise than Robust Kriging method in the rainfall estimates of Amlapura control point remind that Robust Kriging does not eliminate the data of observation such as the Ordinary Kriging method. In general, Ordinary Kriging and Robust Kriging method can estimate the rainfall value of Amlapura control point quite well although it is not able to cover the changes in rainfall value that occurs due to the behavior geographic data.
PERAMALAN PRODUK DOMESTIK REGIONAL BRUTO (PDRB) PROVINSI BALI DENGAN MENGGUNAKAN METODE FUZZY TIME SERIES I GUSTI NGURAH ARYA WANAYASA; I PUTU EKA NILA KENCANA; DESAK PUTU EKA NILAKUSMAWATI
E-Jurnal Matematika Volume 1, No 1, Tahun 2012
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2012.v01.i01.p003

Abstract

The purpose of this research is forecasting the growth of the GDRP in Bali Province on 2011. The fuzzy time series method and Holt-Winter’s exponential smoothing method used to forecast the GDRP in Bali Province on 2011 by using the data of Bali Province’s GDRP constant prices of year 2000 from first quarter of 1991 until fourth quarter of 2010. Then, the forecasting result of both methods compared by see the AFER and MSE value on each method. The comparison result shows the forecasting method by using Holt-Winter’s exponential smoothing is 7.13% while using the fuzzy time series method is 0.64%, these shows the forecasting using fuzzy time series method have a higher accuracy rate compared to Holt-Winter’s exponential smoothing method with the difference of forecasting error rateis6.49%.
PENGGOLONGAN UANG KULIAH TUNGGAL MENGGUNAKAN SUPPORT VECTOR MACHINE I GEDE SEKA SUYOGA; I PUTU EKA NILA KENCANA; I KOMANG GDE SUKARSA
E-Jurnal Matematika Vol 6 No 4 (2017)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2017.v06.i04.p169

Abstract

Tuition fee is the payment of tuition fees each semester borne by each student based on their economic capabilities. Tuition fee is divided into five groups from tuition fee group 1 to tuition fee group 5. This research aims to find the accuracy of the classification of tuition fee using Support Vector Machine (SVM). SVM is a method used for classification of the concept to find hyperplane (separator function) that can separate the data into a predetermined class. In this research, SVM is used to determine the accuracy of tuition fee classification. The variables used are income parents, father’s occupation, mother’s occupation, home ownership status, building, land area, electricity cost, water cost, phone cost, saving accounts, jewelry ownership, and a premium ownership. The results obtained are five hyperplanes to separate tuition fee with accuracy of the classification of tuition fee was 59,69%.
PENGKLASIFIKASIAN DEBITUR DENGAN MENGGUNAKAN ALGORITMA GRAHAM SCAN DALAM PENGAPLIKASIAN CONVEX HULL AGUS EKA ARIESTA; G.K. GANDHIADI; NI KETUT TARI TASTRAWATI; I PUTU EKA NILA KENCANA
E-Jurnal Matematika Vol 2 No 4 (2013)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2013.v02.i04.p058

Abstract

Computational geometry is the mathematical science of computation by using the algorithm analysis to solve the problems of geometry. The problems of computational include polygon triangulations, convex hulls, Voronoi diagrams, and motion planning. Convex hull is the set of points that form a convex polygon that covers the entire set of points. The algorithms for determining the convex hull, among others, Graham Scan, Jarvis March, and Divide and Conquer. In the two-dimensional case, Graham Scan algorithm is highly efficient in the use of time complexity. This article discusses the quest convex hull of the data bank debtors, some of the data used to look at the classification accuracy of the convex hull formed. The coordinates of all the data found by using principal component analysis.After the data are analyzed, we get the accuracy of classification by 74%.
PENGELOMPOKKAN KABUPATEN DI PROVINSI BALI BERDASARKAN PERKEMBANGAN FASILITAS PARIWISATA NOVA SARI BARUS; I PUTU EKA NILA KENCANA; KOMANG GDE SUKARSA
E-Jurnal Matematika Vol 2 No 3 (2013)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2013.v02.i03.p049

Abstract

The development of tourism facilities in each district/city between districts with each district is different. The purpose of this study was to determine the grouping of several districts in the province of Bali is based on the number of tourism facilities as well as what the variable identifier of each group. The analysis used in this study is the analysis of clusters and Biplot. The data used is secondary data obtained from the Bali Tourism Office in 2011. Variables used are classified hotel, non-classified hotels, home stays, restaurants, bars, tourist destination, the area of ??tourism, water tourism and business. The results of this study formed three groups: group 1 Bangli, Buleleng, Jembrana District, Klungkung, Karangasem district and Denpasar City. Group 2 and group 3 Badung district of Gianyar district. Variable identifier is a restaurant for all variables.
Co-Authors A. A. I. DWI FIBRIAYORA ADI PUTRAYASA AGUS EKA ARIESTA ALEXANDER HIRO WIBISONO ANAK AGUNG ISTRI AYU PRATAMI Anak Agung Putu Agung Suryawan Wiranatha ASTITI, Anak Agung Eka Putri Dewi Aulia Wicaksono Damanik, Veni Jean Gabriella Darmateja, I Made Sugita Desak Putu Eka Nilakusmawati DESAK PUTU PRAMI MEITRIANI Diana Diana DOMINGGAS TEO Driyandita, Bernadeta G. K. GANDHIADI G. K. GANDHIADI GEDE AGUS HENDRA YOGANGGA Gede Satria Suputra GUSTI AYU MADE ARNA PUTRI HANY DEVITA I GEDE HARDI KARMANA I GEDE SEKA SUYOGA I Gusti Ayu Made Srinadi I Gusti Ayu Oka Suryawardani I GUSTI NGURAH ARYA WANAYASA I KADEK TEGUH PRADANA I Ketut Satriawan I Ketut Surata I KOMANG GDE SUKARSA I KOMANG GEDE ANTARA I MADE ANOM ARIAWAN I MADE ARYA ANTARA I MADE DANNY DANANJAYA I Made Ramia Adnyana I Nyoman Widana I PUTU AGUS WIDHIANTARA I PUTU ARYA YOGA SUMADI I PUTU JERYANA I Putu Utama I Putu Winada Gautama I PUTU WINADA GAUTAMA I PUTU YUDANTA EKA PUTRA I Wayan Mertha I Wayan Rediyasa I Wayan Sumarjaya I Wayan Tika IDA AYU PRASETYA UTHAMI Ida Bagus Gde Pujaastawa Ida Bagus Kade Puja Arimbawa K. IMAMUDDIN KAMIL Isabel Divya Georgiana Walewangko JUEN LING KADEK BUDINIRMALA KADEK DWI FARMANI KADEK RISNA WITARI Ketut Jayanegara Komang Dharmawan LUH PUTU IDA HARINI MADE ARISTIAWAN JIWA ATMAJA MADE AYU DWI OCTAVANNY MADE PUTRI ARIASIH MADE SANJIWANI Made Susilawati Mahardika, Putu Harry MELINDA HERMANTO MOCH. ANJAS A MUHAMAD RIFAI MULIA YASMAN NGURAH GDE PRABA MARTHA Ni Kadek Emik Sapitri NI KADEK PUSPITAYANTI NI KADEK SETIAWATI Ni Ketut Tari Tastrawati NI LUH ARDILA KUSUMAYANTI Ni Luh Putu Ayu Fitriani Ni Luh Putu Suciptawati Ni Made Asih Ni Made Santiningsih NI MADE SUMA FRIDAYANI NI PUTU ANIK MAS RATNASARI NI WAYAN ARNI YANITA NI WAYAN EKA SURYA ARTINI NI WAYAN NINING ISMIRANTI NOVA SARI BARUS Putu Edi Dimas Saputra PUTU EKA SWASTINI Putu Harry Mahardika Putu Harry Mahardika PUTU NOPITA PURNAMA NINGSIH RAHMAD RAHMAD WIDODO Ratna Sari Widiastuti REYNALDO PANJI WICAKSONO SLAMET SAMSUL HIDAYAT SRI DIANTINI Tjokorda Bagus Oka TRISNA RAMADHAN VANIA RISKASARI YR VICTOR MALLANG Wijayakusuma, I Gusti Ngurah Lanang