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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 5 Documents
 1 
Search results for , issue "Vol 4 No 1 (2015)" : 5 Documents clear
MENGATASI HETEROSKEDASTISITAS PADA REGRESI DENGAN MENGGUNAKAN WEIGHTED LEAST SQUARE PUTU AYU MAZIYYA; I KOMANG GDE SUKARSA; NI MADE ASIH
E-Jurnal Matematika Vol 4 No 1 (2015)
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.2015.v04.i01.p083

Abstract

In the regression analysis we need a method to estimate parameters to fulfill the BLUE characteristic. There are assumptions that must be fulfilled homoscedasticity one of which is a condition in which the assumption of error variance is constant (same), infraction from the assumptions homoskedasticity called heteroscedasticity. The Consequence of going heteroscedasticity can impact OLS estimators still fulfill the requirements of not biased, but the variant obtained becomes inefficient. So we need a method to solve these problems either by Weighted Least Square (WLS). The purpose of this study is to find out how to overcome heteroscedasticity in regression with WLS. Step of this research was do with the OLS analysis, then testing to see whether there heteroscedasticity problem with BPG method, the next step is to repair the beginning model by way of weighting the data an exact multiplier factor, then re-using the OLS procedure to the data that have been weighted, the last stage is back with a heteroscedasticity test BPG method, so we obtained the model fulfill the assumptions of homoskedasicity. Estimates indicate that the WLS method can resolve the heteroscedasticity, with exact weighting factors based on the distribution pattern of data seen.
INTERPOLASI SPASIAL DENGAN METODE ORDINARY KRIGING MENGGUNAKAN SEMIVARIOGRAM ISOTROPIK PADA DATA SPASIAL (Studi Kasus: Curah Hujan di Kabupaten Karangasem) PUTU MIRAH PURNAMA D.; KOMANG GDE SUKARSA; KOMANG DHARMAWAN
E-Jurnal Matematika Vol 4 No 1 (2015)
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.2015.v04.i01.p084

Abstract

Spatial data is data that is presented in the geographic of an object, related to the location, shape and relationship of the earth in space. One of example of spatial data is rainfall. To determine the value of rainfall in an area, built to predict rain post information regarding rainfall. Spatial interpolation is used to estimate rainfall by collecting rainfall values held rain heading around. Assessment methods used in the estimate the rainfall in the Karangasem district is ordinary kriging using isotropic semivariogram that takes into account height on spatial data. Isotropic semivariogram which only takes into account the distance alone. Ordinary kriging method using isotropic semivariogram that takes into account height  value estimated rainfall is much different to the values at the control points Amlapura and Besakih. Interpolation on 3D data are not suitable for use on ordinary kriging method, grouping should be done at the data into a few weeks to application of ordinary kriging interpolation method using anisotropic semivariogram on 3D data.
FAKTOR-FAKTOR YANG MENENTUKAN KEPUASAN PELANGGAN SEPEDA MOTOR MATIC HONDA DI KOTA DENPASAR NI KADEK LESTARI PUTRI; NI MADE ASIH; DESAK PUTU EKA NILAKUSMAWATI
E-Jurnal Matematika Vol 4 No 1 (2015)
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.2015.v04.i01.p080

Abstract

This study aimed to elaborate the dominant factor affecting consumer’s loyalties regarding Honda motor matic and to determine effective marketing strategy for this product.  This study conducted at Denpasar where 150 respondents randomly chosen as the data sources.  From factor analysis, we found emotional factor is the most dominant factor for consumer’s loyalties with eigen value as much as 3,365 and variance explained by this factor is 48,08 percent.  Meanwhile, to determine effective marketing strategy, we found the product’s quality dominated by its design; service quality dominated by service reliability, emotional factor dominated by the product’s esthetic, each of these has communalities as much as 56,38 percent; 72,33 percent, and 65,20 percent respectively.
PERBANDINGAN TRANSFORMASI BOX-COX DAN REGRESI KUANTIL MEDIAN DALAM MENGATASI HETEROSKEDASTISITAS NI WAYAN YUNI CAHYANI; I GUSTI AYU MADE SRINADI; MADE SUSILAWATI
E-Jurnal Matematika Vol 4 No 1 (2015)
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.2015.v04.i01.p081

Abstract

Ordinary least square (OLS) is a method that can be used to estimate the parameter in linear regression analysis. There are some assumption which should be satisfied on OLS, one of this assumption is homoscedasticity, that is the variance of error is constant. If variance of the error is unequal that so-called heteroscedasticity. The presence heteroscedasticity can cause estimation with OLS becomes inefficient. Therefore, heteroscedasticity shall be overcome. There are some method that can used to overcome heteroscedasticity, two among those are Box-Cox power transformation and median quantile regression. This research compared Box-Cox power transformation and median quantile regression to overcome heteroscedasticity. Applied Box-Cox power transformation on OLS result ????2point are greater, smaller RMSE point and confidencen interval more narrow, therefore can be concluded that applied of Box-Cox power transformation on OLS better of median quantile regression to overcome heteroscedasticity.
PENENTUAN CADANGAN PREMI UNTUK ASURANSI PENDIDIKAN MADE PUTRI ARIASIH; KETUT JAYANEGARA; I NYOMAN WIDANA; I PUTU EKA N. KENCANA
E-Jurnal Matematika Vol 4 No 1 (2015)
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.2015.v04.i01.p082

Abstract

This aims of this research is determine the insurance premium reserve for education with retrospective calculations and determine the premium reserves who acquired during the period of guarantee for insurance education. This research  observes the premium reserve for persons aged 40 years with a coverage period of 17 years. The secondary data used is an education insurance data product  from the insurance company that issued the insurance product. Premium reserve is determined by using the retrospective calculation, the calculation using the annuity value, net single premium value, net annual premiums, the value of net monthly premium, CSO 1980 mortality and fixed interest rate at 9%. Retrospective calculations produce a faster value backup  and sequentially in each year. The results showed that the premium reserve with retrospective calculation should be close up to the cash price owned by insurance company and must be the same at the end of the insurance period is Rp 7.000.000,00.

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