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All Journal Jurnal Matematika E-Jurnal Matematika Prosiding Seminar Nasional MIPA BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Ilmiah Ilmu Sosial Dinasti International Journal of Education Management and Social Science Jurnal Cahaya Mandalika JOURNAL SCIENTIFIC OF MANDALIKA (JSM)
I KOMANG GDE SUKARSA
Mathematics Department, Faculty Of Mathematics And Natural Sciences, Udayana University
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Physics Transportation Other

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PEMODELAN RATA-RATA LAMA SEKOLAH MENGGUNAKAN PENDEKATAN REGRESI NONPARAMETRIK SPLINE MULTIVARIABLE NI LUH GEDE SINTA ARYATI; I KOMANG GDE SUKARSA; I GUSTI AYU MADE SRINADI
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.p320

Abstract

Mean years school (MYS) is one of the indicators used in calculating the human development index (HDI). The value of MYS Indonesia in 2019 is 8,75 which is still low. Therefore it still needs to be improved. In this research, MYS modeling will be carried out using six factors that are thought to influence MYS. This research uses multivariable spline nonparametric regression to modeling MYS Indonesia in 2019. The best model is selected based on the minimum value of Generalized Cross Validation (GCV). Based on this research, the best model obtained is a linear orde (orde 2) spline model with four knots. The model has value of 99,91%.
PERBANDINGAN ANALISIS DISKRIMINAN DAN REGRESI LOGISTIK UNTUK MENGKLASIFIKASIKAN KELAYAKAN VISITASI PELAMAR BIDIKMISI NISA HIDAYATI; I KOMANG GDE SUKARSA; DESAK PUTU EKA NILAKUSMAWATI
E-Jurnal Matematika Vol 9 No 1 (2020)
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.2020.v09.i01.p273

Abstract

The purpose of this study is to compare discriminant analysis and logistic regression to classify the feasibility of the Bidikmisi applicant's visitation based on the classification accuracy. The results showed that the assumptions of homogeneity covariance matricies between the groups are unequal, The significant independent variable is the combined amount of parental income , parents income divided by the number of family dependents , and electricity bills , and then the results of the classification of validation data from the logistic regression analysis of 98,21% higher than the discriminant analysis of 94,64%.
ANALISIS KORELASI KANONIK PADA HUBUNGAN ANTARA SOFT SKILLS TERHADAP PRESTASI BELAJAR MAHASISWA NI PUTU JULIANINGSIH; EKA N KENCANA; KOMANG GDE SUKARSA
E-Jurnal Matematika Vol 8 No 4 (2019)
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.2019.v08.i04.p264

Abstract

The purpose of this study is to know the relationship between soft skills and learning achievement using canonical correlation analysis and to find out the dominant dimensions of soft skills and learning achievement using confirmatory factor analysis. The data used are primary data obtained by distributing questionnaires. The sampling technique used was proportional to size sampling with the number of respondents as many as 150 respondents. The results of the study with canonical correlation analysis showed that soft skills with learning achievement had a close relationship with canonical correlation values ??of 0.70397. The results of the study with confirmatory factor analysis showed that the dominant dimensions of soft skills and learning achievement were flexibility with the percentage of the variance of 69.081% and cognitive percentage of the variance of 71.706%.
PERAMALAN JUMLAH KUNJUNGAN WISATAWAN MANCANEGARA YANG BEKUNJUNG KE BALI MENGGUNAKAN FUNGSI TRANSFER I KETUT PUTRA ADNYANA; I WAYAN SUMARJAYA; I KOMANG GDE SUKARSA
E-Jurnal Matematika Vol 5 No 4 (2016)
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.2016.v05.i04.p133

Abstract

The aim of this research is to model and forecast the number of tourist arrivals to Bali using transfer function model based on exchange rate USD to IDR from January 2009 to December 2015. Transfer function model is a multivariate time series model which can be used to identify the effect of the exchange rate to the number of tourist arrivals to Bali. The first stage in transfer function modeling is identification of ARIMA model in exchange rate USD to IDR variable. The best ARIMA model is chosen based on the smallest Akaike information criterion (AIC). The next stage are as follows identification of transfer function model, estimation of transfer function model, and diagnostic checking for transfer function model. The estimated transfer function model suggests that the number of tourist arrivals to Bali is affected by the exchange rate of the previous eight months. The mean absolute percentage error (MAPE) is equal of the forecasting model to 9,62%.
PENERAPAN METODE BOOTSTRAP RESIDUAL DALAM MENGATASI BIAS PADA PENDUGA PARAMETER ANALISIS REGRESI NI MADE METTA ASTARI; NI LUH PUTU SUCIPTAWATI; I KOMANG GDE SUKARSA
E-Jurnal Matematika Vol 3 No 4 (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.i04.p075

Abstract

Statistical analysis which aims to analyze a linear relationship between the independent variable and the dependent variable is known as regression analysis. To estimate parameters in a regression analysis method commonly used is the Ordinary Least Square (OLS). But the assumption is often violated in the OLS, the assumption of normality due to one outlier. As a result of the presence of outliers is parameter estimators produced by the OLS will be biased. Bootstrap Residual is a bootstrap method that is applied to the residual resampling process. The results showed that the residual bootstrap method is only able to overcome the bias on the number of outliers 5% with 99% confidence intervals. The resulting parameters estimators approach the residual bootstrap values ??OLS initial allegations were also able to show that the bootstrap is an accurate prediction tool.
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.
PENERAPAN METODE SIX SIGMA DALAM ANALISIS KUALITAS PRODUK (Studi Kasus Produk Batik Handprint Pada PT XYZ di Bali) TRI ALIT TRESNA PUTRA; I KOMANG GDE SUKARSA; I GUSTI AYU MADE SRINADI
E-Jurnal Matematika Vol 6 No 2 (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.i02.p156

Abstract

The aim of this study was to demonstrate the application of Statistics Quality Control in fierce industries. By observing Batik production process at PT XYZ as a case in this work, we applied Six Sigma Method to analyze defective product and their cause while also measure overall quality goodness. Six Sigma is a method to improve a process and reduce defects in productions into 3.4 defects per million productions. We use handprint batik productions at PT XYZ as a case in this study. The method is involving Define, Measure and Analyze (DMA) phases. By using Six Sigma, it was obtained that the quality of handprint batik are quite good with sigma of 3.105 and defect rate of 54.269 million production (DPMO). There are four defect causes of handprint batik namely: ripped fabric, shallowness, perforation, and mispattern which contribute 41,7%, 35,8%, 15%, 7,5% respectively from overall defects. The main cause of defects is the carelessness of workers in production process. Therefore we need to reduce the carelessness to improve production quality.
ANALISIS PREFERENSI MASYARAKAT TERHADAP KUALITAS PELAYANAN RUMAH SAKIT DINI AMALIA PUTRI; I KOMANG GDE SUKARSA; KETUT JAYANEGARA
E-Jurnal Matematika Vol 8 No 3 (2019)
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.2019.v08.i03.p256

Abstract

Conjoined analysis is a multivariate technique specifically developed to get people's preferences. The purpose of this study is to determine people's preferences for the quality of hospital services based on attributes to determine the combination of these attributes that are most desired by customers. This study uses primary data taken through surveys using a questionnaire. The survey conducted at Udayana Denpasar Hospital was applied with non-probability sampling techniques, namely accidental sampling with the number of samples needed was 100 respondents. The attributes used in this study were (a) physician services, (b) number of patients, (c) facilities, (d) location of the bathroom, and (e) price. The results showed that the most valued attribute by respondents was Facility. The combination of the level of each attribute that most influences the respondents in determining the room when doing hospitalization at the Level II Hospital of Udayana Denpasar is handled by a Specialist, consisting of 1 patient, bathroom, with facilities consisting of tv, air conditioning, refrigerator, cupboard , buffet, sofa, table, living room and bed for the patient's family, with a price of> 1,000,000.
PERBANDINGAN PERAMALAN HASIL PRODUKSI IKAN MENGGUNAKAN METODE PERMULUSAN EKSPONENSIAL HOLT-WINTERS DAN ARIMA DIAN RAHMAN; I WAYAN SUMARJAYA; I KOMANG GDE SUKARSA
E-Jurnal Matematika Vol 7 No 4 (2018)
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.2018.v07.i04.p227

Abstract

Every year fish consumption in Indonesia always increases. Basis landing of fish (PPI) Kedonganan is one of the ports where the ships docked and take part in economic activities of fisheries in Bali. The aim of this study is to forecast the amount of fish production so that the fish production can be managed. Some methods that can handle seasonal factors in time series forecasting include Holt-Winters exponential smoothing and ARIMA. The results show that ARIMA(2,0,4)×(3,1,2)12 yields RMSE is 89,358 and MAPE is 0.81% whereas the value of fish outcomes prediction using Holt-Winters exponential smoothing method yields RMSE is 119,158 and MAPE is 1.14%.
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.
Co-Authors ADI PUTRAYASA ALEXANDER JOSEPH RIADI ANAK AGUNG ISTRI AYU PRATAMI Damayanthi, Ni Wayan Rita Desak Putu Eka Nilakusmawati DESAK PUTU PRAMI MEITRIANI DEWA AYU MADE DWI YANTI PURNAMI DIAN PRAMESTI DEWI DIAN RAHMAN Diana Diana DINI AMALIA PUTRI DOMINGGAS TEO DWI HERAYANTHI W. Eka N Kencana Eka N. Kencana EKA N. KENCANA EKA N. KENCANA EVI NOVIYANTARI FATIMAH G. K. GANDHIADI G.K. GANDHIADI Gandhiadi, GK Gandhiadi, I. G. K GEDE ARY PRABHA YOGESSWARA GUSTI AYU MADE ARNA PUTRI HANY DEVITA I GEDE AGUS JIWADIANA I GEDE SEKA SUYOGA I Gusti Ayu Made Srinadi I KETUT PUTRA ADNYANA I MADE ARYA ANTARA I MADE CANDRA SATRIA I MADE DANNY DANANJAYA I PUTU AGUS WIDHIANTARA I PUTU EKA IRAWAN I PUTU EKA N. KENCANA, I PUTU EKA N. I Putu Eka Nila Kencana I Wayan Sumarjaya I WAYAN WIDHI DIRGANTARA IA KOMANG MERIANI IDA AYU MADE SUPARTINI IDA AYU PRASETYA UTHAMI Isabel Divya Georgiana Walewangko KADEK DWI FARMANI Kencana, Eka N Kencana, Eka N. Ketut Jayanegara KOMANG AYU YULIANINGSIH Komang Dharmawan LUH KOMANG MARDIANI Luh Putu Trisna Darmayanti Made Susilawati MOCH. ANJAS A MODANA LOLITA Mohamad Dwi Agus Arianto NADIYA YUVITA RIZKI NGURAH GDE PRABA MARTHA NI GUSTI KETUT TRISNA PRADNYANTARI NI KADEK ARISKA DEWI NI KADEK SETIAWATI NI KETUT TRI UTAMI NI KOMANG AYU SRI CAHYANI NI LUH ARDILA KUSUMAYANTI NI LUH GEDE SINTA ARYATI Ni Luh Putu Suciptawati NI LUH SUKERNI Ni Made Asih NI MADE LASTI LISPANI NI MADE METTA ASTARI Ni Made Santiningsih NI MADE SEKARMINI NI MADE SUKMA PERTIWI NI MADE SUMA FRIDAYANI NI PUTU AYU DINITA TRISNAYANTI NI PUTU JULIANINGSIH NI PUTU NADYA AGUSVIANI NI WAYAN AMANDA DEWI SULISTYANINGSIH NI WAYAN NINING ISMIRANTI NI WAYAN YULIANI NISA HIDAYATI NOVA SARI BARUS NYOMAN GDE PRAJNAWIWEKA RATMASA TARAM PUTU AYU MAZIYYA PUTU EKA SWASTINI PUTU GDE BUDHA WIRYADANA PUTU MIRAH PURNAMA D. PUTU SUSAN PRADAWATI Ratna Sari Widiastuti REYNALDO PANJI WICAKSONO Riadi, Alexander Joseph Safitri, Asa Vira Tjokorda Bagus Oka TRI ALIT TRESNA PUTRA VANIA RISKASARI YR Wijayakusuma, I Gusti Ngurah Lanang Yasmin Roni Mz