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INDONESIA
E-Jurnal Matematika
Published by Universitas Udayana
ISSN : 23031751     EISSN : -     DOI : -
Core Subject : Education,
Mathematics
E-Jurnal Matematika merupakan salah satu jurnal elektronik yang ada di Universitas Udayana, sebagai media komunikasi antar peminat di bidang ilmu matematika dan terapannya, seperti statistika, matematika finansial, pengajaran matematika dan terapan matematika dibidang ilmu lainnya. Jurnal ini lahir sebagai salah satu bentuk nyata peran serta jurusan Matematika FMIPA UNUD guna mendukung percepatan tercapainya target mutu UNUD, selain itu jurnal ini terbit didorong oleh surat edaran Dirjen DIKTI tentang syarat publikasi karya ilmiah bagi program Sarjana di Jurnal Ilmiah. E-jurnal Matematika juga menerima hasil-hasil penelitian yang tidak secara langsung berkaitan dengan tugas akhir mahasiswa meliputi penelitian atau artikel yang merupakan kajian keilmuan.
Arjuna Subject : -
Articles 6 Documents
 1 
Search results for , issue "Vol 5 No 3 (2016)" : 6 Documents clear
ANALISIS REGRESI NONPARAMETRIK SPLINE MULTIVARIAT UNTUK PEMODELAN INDIKATOR KEMISKINAN DI INDONESIA DESAK AYU WIRI ASTITI; I WAYAN SUMARJAYA; MADE SUSILAWATI
E-Jurnal Matematika Vol 5 No 3 (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.i03.p129

Abstract

The aim of this study is to obtain statistics models which explain the relationship between variables that influence the poverty indicators in Indonesia using multivariate spline nonparametric regression method. Spline is a nonparametric regression estimation method that is automatically search for its estimation wherever the data pattern move and thus resulting in model which fitted the data. This study, uses data from survey of Social Economy National (Susenas) and survey of Employment National (Sakernas) of 2013 from the publication of the Central Bureau of Statistics (BPS). This study yields two models which are the best model from two used response variables. The criterion uses to select the best model is the minimum Generalized Cross Validation (GCV). The best spline model obtained is cubic spline model with five optimal knots.
PERAMALAN JUMLAH KUNJUNGAN WISATAWAN AUSTRALIA YANG BERKUNJUNG KE BALI MENGGUNAKAN MODEL TIME VARYING PARAMETER (TVP) I PUTU GEDE DIAN GERRY SUWEDAYANA; I WAYAN SUMARJAYA; NI LUH PUTU SUCIPTAWATI
E-Jurnal Matematika Vol 5 No 3 (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.i03.p130

Abstract

The purpose of this research is to forecast the number of Australian tourists arrival to Bali using Time Varying Parameter (TVP) model based on inflation of Indonesia and exchange rate AUD to IDR from January 2010 – December 2015 as explanatory variables. TVP model is specified in a state space model and estimated by Kalman filter algorithm. The result shows that the TVP model can be used to forecast the number of Australian tourists arrival to Bali because it satisfied the assumption that the residuals are distributed normally and the residuals in the measurement and transition equations are not correlated. The estimated TVP model is . This model has a value of mean absolute percentage error (MAPE) is equal to dan root mean square percentage error (RMSPE) is equal to . The number of Australian tourists arrival to Bali for the next five periods is predicted: ; ; ; ; and (January - May 2016).
MENENTUKAN PORTOFOLIO OPTIMAL MENGGUNAKAN MODEL CONDITIONAL MEAN VARIANCE I GEDE ERY NISCAHYANA; KOMANG DHARMAWAN; I NYOMAN WIDANA
E-Jurnal Matematika Vol 5 No 3 (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.i03.p125

Abstract

When the returns of stock prices show the existence of autocorrelation and heteroscedasticity, then conditional mean variance models are suitable method to model the behavior of the stocks. In this thesis, the implementation of the conditional mean variance model to the autocorrelated and heteroscedastic return was discussed. The aim of this thesis was to assess the effect of the autocorrelated and heteroscedastic returns to the optimal solution of a portfolio. The margin of four stocks, Fortune Mate Indonesia Tbk (FMII.JK), Bank Permata Tbk (BNLI.JK), Suryamas Dutamakmur Tbk (SMDM.JK) dan Semen Gresik Indonesia Tbk (SMGR.JK) were estimated by GARCH(1,1) model with standard innovations following the standard normal distribution and the t-distribution.  The estimations were used to construct a portfolio. The portfolio optimal was found when the standard innovation used was t-distribution with the standard deviation of 1.4532 and the mean of 0.8023 consisting of 0.9429 (94%) of FMII stock, 0.0473 (5%) of  BNLI stock, 0% of SMDM stock, 1% of  SMGR stock.
PENENTUAN CADANGAN PREMI DENGAN METODE PREMIUM SUFFICIENCY PADA ASURANSI JIWA SEUMUR HIDUP JOINT LIFE NI PUTU MIRAH PERMATASARI; I NYOMAN WIDANA; KARTIKA SARI
E-Jurnal Matematika Vol 5 No 3 (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.i03.p127

Abstract

The aim of this research was to get the formula of premium reserves through the premium sufficiency method. Premium reserve is the amount of fund that is collected by the insurance company in preparation for the claim’s payment. Premium sufficiency method is gross premium calculation. To construct that formula, this research used Tabel Mortalitas Indonesia (TMI) 2011, interest rate 2.5% and cost of alpha %. Based on simulation result in men premium reserve value of age 1 of 56 years propotional with insured periods, but after56 years enhancement of premium reserve value.
IMPLEMENTASI ALGORITMA CAT SWARM OPTIMIZATION DALAM MENYELESAIKAN JOB SHOP SCHEDULING PROBLEM (JSSP) I WAYAN RADIKA APRIANA; NI KETUT TARI TASTRAWATI; KARTIKA SARI
E-Jurnal Matematika Vol 5 No 3 (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.i03.p126

Abstract

Cat Swarm Optimization (CSO) algorithm is a metaheuristic algorithm which is based on two behaviors of cat, seeking and tracing. CSO algorithm is used in solving optimization problems. One of the optimization problems which can be seen in daily life is Job Shop Scheduling Problem (JSSP). This study aimed to observe the performance of CSO algorithm in solving JSSP. This study focused on 5 job-12 machine cases. According to this study, CSO algorithm was effective in solving real case of JSSP in 5 jobs – 12 machines scheduling at CV Mitra Niaga Indonesia agriculture tools industry. In implementing CSO algorithm in JSSP, a correct parameter choosing could lead to an optimal result. On other hand, the greater the number of jobs or machines the more complex and difficult the JSSP that needed to be solved.
BOOTSTRAP AGGREGATING (BAGGING) REGRESI LOGISTIK ORDINAL UNTUK MENGKLASIFIKASIKAN STATUS GIZI BALITA DI KABUPATEN KLUNGKUNG PALUPI PURNAMA SARI; MADE SUSILAWATI; I GUSTI AYU MADE SRINADI
E-Jurnal Matematika Vol 5 No 3 (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.i03.p128

Abstract

This research was conducted to determine the variables that significantly influence nutritional status of children based on indicators that defined as height for age (H/A) and to classify children nutritional status into normal, short or very short categories. Height for age (H/A) is indicator used to describe the circumstances of malnutrition short. Short children (stunting) is  children who fail to reach optimal growth. The secondary data was list of 116 data of children aged 24-59 months at UPT. Puskesmas Klungkung I in 2015. The method was used was ordinal logistic regression and bagging ordinal logistic regression. Based on the research results, it was obtained variables children body length at birth, birth weight, and length of mid-upper arm circumference (MUAC) in pregnant woman were significantly affects the nutritional status of children by the classification accuracy level of ordinal logistic regression and misclassification . Classification accuracy of ordinal logistic regression can be improved by bagging ordinal logistic regression method. Bagging works well on classification method which has unstable procedures. One of classification method which has unstable procedures is ordinal logistic regression. Bagging ordinal logistic regression method by 501 times replication capable to improve classification accuracy of ordinal logistic regression model from to , increased .

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