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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 10 Documents
 1 
Search results for , issue "Vol 2 No 1 (2013): E-Jurnal Matematika" : 10 Documents clear
PENENTUAN KEUNTUNGAN MAKSIMUM PADA PENJUALAN OLAHAN TAPE DENGAN MENGGUNAKAN METODE LAGRANGE (Studi Kasus: UD. Sari Madu) FEMY AYU ASTITI; NI MADE ASIH; I NYOMAN WIDANA
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.p023

Abstract

Optimization problems can be solved by various methods, such as Lagrange Method.   This  method can be used to find the solution. Using Lagrange method, the extreme value can be obtained, so that the optimal solution can be found. In this research, the maximum revenue of UD. Sari Madu is a limited by several constraints. After the objective function and constraint function being model, than maximum revenue is found. From first until fourth quarterly, the maximum revenue is found Rp. 9.701.333, Rp. 10.064.148, 9.793.272 and Rp. 9.397.730 respectively.
PREDIKSI WAKTU KETAHANAN HIDUP DENGAN METODE PARTIAL LEAST SQUARE PANDE PUTU BUDI KUSUMA; I GUSTI AYU MADE SRINADI
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.p028

Abstract

Coronary heart disease is caused due to an accumulation of fat on the inside walls of blood vessels of the heart (coronary arteries). The factors that had led to the occurrence of coronary heart disease is dominated by unhealthy lifestyle of patients, and the survival times of different patients. This research objective is to predict the survival time of patients with coronary heart disease by taking into account the explanatory variables were analyzed by the method of Partial Least Square (PLS).  PLS method is used to resolve the multiple regression analysis when the specific problems of multicollinearity and microarray data. The purpose of the PLS method is to predict the explanatory variables with multiple response variables so as to produce a more accurate predictive value.  The results of this research showed that the prediction of survival for the three samples of patients with coronary heart disease had an average of 13 days, with a RMSEP value (error value) was 1.526 which means that the results of this study are not much different from the predicted results in the field of medicine. This is consistent with the fact that the medical field suggests that the average survival for patients with coronary heart disease by 13 days.
FAKTOR–FAKTOR YANG MEMENGARUHI MINAT MAHASISWA ASAL LUAR BALI KULIAH DI FMIPA UNIVERSITAS UDAYANA BALI DAIMATUL KHOIRIYAH; MADE SUSILAWATI; DESAK PUTU EKA NILAKUSMAWATI
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.p024

Abstract

Tujuan dari penelitian ini adalah untuk mengetahui faktor–faktor yang memengaruhi minat mahasiswa luar Bali kuliah di FMIPA Universitas Udayana Bali. Analisis yang digunakan  dalam  penelitian  ini  adalah  analisis  faktor.  Data  yang digunakan  adalah data primer yang diperoleh dengan menyebarkan kuesioner kepada setiap mahasiswa asal luar Bali yang kuliah di FMIPA Universitas Udayana Bali angkatan 2008-2011. Dalam penelitian ini faktor-faktor  yang digunakan  adalah  lokasi,  faktor  biaya,  produk,  latar  belakang sosial ekonomi,  motivasi,  fasilitas,  referensi,  promosi,  dan  reputasi.  Hasil  penelitian menunjukkan  bahwa,  terdapat  delapan  faktor  yang memengaruhi  minat  mahasiswa luar Bali kuliah di FMIPA Universitas Udayana Bali. Faktor tersebut yaitu: (1) faktor produk yang merupakan faktor dengan nilai eigen paling tinggi yaitu 7,792 dan varian 28,860%, (2) faktor referensi dengan varian 8,732%, (3) faktor reputasi dengan varian 7,808%,  (4)  faktor  biaya  dengan  varian  6,723%, (5) faktor  latar  belakang sosial ekonomi dengan varian 4,921%, (6) faktor motivasi dengan varian 4,430%, (7) faktor lokasi dengan  varian 3,836% dan (8)  faktor promosi  dengan  varian  3,708%, dengan total varian yang dapat dijelaskan adalah sebesar 69,018%.
PENERAPAN METODE GENERALIZED RIDGE REGRESSION DALAM MENGATASI MASALAH MULTIKOLINEARITAS NI KETUT TRI UTAMI; I KOMANG GDE SUKARSA
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.p029

Abstract

Ordinary least square is parameter estimation method for linier regression analysis by minimizing residual sum of square. In the presence of multicollinearity, estimators which are unbiased and have a minimum variance can not be generated. Multicollinearity refers to a situation where regressor variables are highly correlated. Generalized Ridge Regression is an alternative method to deal with multicollinearity problem. In Generalized Ridge Regression, different biasing parameters for each regressor variables were added to the least square equation after transform the data to the space of orthogonal regressors. The analysis showed that Generalized Ridge Regression was satisfactory to overcome multicollinearity.
ALGORITMA FLOYD WARSHALL UNTUK MENENTUKAN JALUR TERPENDEK EVAKUASI TSUNAMI DI KELURAHAN SANUR AJENG FITRAH SANI; NI KETUT TARI TASTRAWATI; I MADE EKA DWIPAYANA
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.p020

Abstract

Sanur village is one of beautiful tourism spots in Bali. Sanur is located in south of Bali, Indonesia. There are many beaches in that place. Besides of beautifulness of it, Sanur potentially to be attacked by Tsunami disaster because of it is location  near subduction Zone. It is important to know Tsunami evacuation track. This research tries to give alternative Tsunami evacuation track by using Floyd Warshall algorithm. The result of this research is Tsunami evacuation track in sanur by using Floyd Warshall algotihm
ANALISIS PORTOFOLIO SAHAM LQ45 MENGGUNAKAN FUNGSI UTILITAS KUADRATIK KADEK FRISCA AYU DEVI; KOMANG DHARMAWAN; NI MADE ASIH
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.p025

Abstract

Utility function can use to give risk preference for investors who want to get the benefits gained meets investment targets. Quadratic utility functions on optimal portfolio is strongly influenced by the expected return and standard deviation. The establishment of optimal portfolios using a quadratic utility function optimization problems. Under the settlement portfolio optimization, the necessary data is expected return, variance, and variance covariance matrix. The optimal portfolio is affected by some factors Risky less Rate, risk aversion index, and Borrow Rate. The results of settlement portfolio optimization is obtaining the utility value while the relatively large changes influencing by risk averse index.
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.
MENENTUKAN KOMPOSISI OPTIMAL DARI FAKTOR-FAKTOR YANG MEMENGARUHI KETAHANAN ASPAL DENGAN METODE TAGUCHI GUSTI AYU PUTU YULIANDARI; I GUSTI AYU MADE SRINADI; I WAYAN SUMARJAYA
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.p026

Abstract

Taguchi method purpose to improve the quality of a product. This method can reduce the number of execution of the experiment when compared to using a full factorial method. measures taken, namely the calculation of degrees of freedom, the selection of orthogonal array to reduce the run, then calculating S/NR is used to determine the optimal composition of the factors that will affect the durability of asphalt. The results of this research that the optimal composition of the factors that affect the resistance of asphalt are aggregate of 6987.57 tons, temperature of 155? C, compaction speed 5 km/h, hardening time for 4 hours after paving before the opening of traffic at normal speed, thickness of 6.27 cm thick bitumen from the aggregate surface, body weight that is weighing 7 ton. Dimensions of factors is an area of ??5.598m.
MENAKSIR VALUE AT RISK (VAR) PORTOFOLIO PADA INDEKS SAHAM DENGAN METODE PENDUGA VOLATILITAS GARCH INTAN AWYA WAHARIKA; KOMANG DHARMAWAN; NI MADE ASIH
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.p022

Abstract

Value at Risk (VaR) is a concept which was used to measure a risk on risk management. VaR explained the worst amount of financial loss in a financial product with the horizon and certain degree of believe. In the calculation of VaR, it was needed a prediction in volality, volality from a series of time which can be homokedasticity (constant) or heterokedasticity (ever changed). Changed volality can be found on the stock and stock index. One of the method which was done in modeling of changed volality was GARCH. In this research, GARCH was used to estimate VaR’s Value from IHSG and LQ45 to be sold in Jakarta Stock Exchange on 4 January to 23 August 2012 (650 observations) VaR can be calculated with a periode of horizon, 1 day, 10 days, and 22 days with the degree of believe 95%
SISTEM PAKAR PENDIAGNOSA PENYAKIT MENULAR PADA ANJING KADEK RISNA WITARI; I G.K. GANDHIADI; 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.p027

Abstract

The closeness of the relationship between dogs and human makes the dog can be trained, played together, lived together with human and are invited to socialize with human and other dogs. But, despite its this relationship, the dogs can also have a contagious disease that may be harmful to human. Diagnostic expert system for infectious disease in dogs for as web-based system with the media android used as a tool for diagnosing infectious diseases in dogs based on physical characteristics or symptoms that can be seen or felt without through examination of the specifics. The diagnostics final results are expected to be a reference for further examination and handling of dogs that contract the disease is detected to prevent the disease for humans. This expert system uses a forward chaining inference method and Certainty Factor to infer.

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