E-Jurnal Matematika
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.
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PENERAPAN METODE FUZZY SUGENO UNTUK MENENTUKAN HARGA JUAL SEPEDA MOTOR BEKAS
AMI HILDA AGUSTIN;
G. K. GANDHIADI;
TJOKORDA BAGUS OKA
E-Jurnal Matematika Vol 5 No 4 (2016)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
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DOI: 10.24843/MTK.2016.v05.i04.p138
Fuzzy logic is a way to map an input space into an output space. The basic of fuzzy logic is fuzzy set theory. In the fuzzy set theory, the role of membership degree is important to determine the presence of elements in a set. Membership degree is the fundamental feature of reasoning in fuzzy logic. There are several methods that are often used in solving fuzzy inference system, one of them is fuzzy Sugeno method. The aim of this research is applications of fuzzy methods is to forecast to determine the selling price of used motorcycles. In determining the selling price of used motorcycles, there are several things that need to be considered, namely : the production year of the motorcycles, the physical condition of the motorcycles, the origin of the license plates, and the purchase price of the motorcycles. The calculation can be done by using Matlab program. The result obtained were then tested using the Mean Absolute Percentage Error (MAPE) by calculating difference between the selling price of dealer minus the selling price of fuzzy Sugeno then divided by the selling price of dealer. From the test result, MAPE value obtained was 5,64% . This indicates that error rate below 10%, so we can say the result of these calculation is considerably accurate.
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
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DOI: 10.24843/MTK.2016.v05.i04.p133
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%.
MENENTUKAN HARGA KONTRAK BERJANGKA KOMODITAS KEDELAI MENGGUNAKAN MODEL MEAN REVERSION
WIRYA SEDANA;
KOMANG DHARMAWAN;
NI MADE ASIH
E-Jurnal Matematika Vol 5 No 4 (2016)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
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DOI: 10.24843/MTK.2016.v05.i04.p137
It has been discussed in many literatures that commodity prices tend to follow mean reversion model. This means that when there is a jump price in certain time, the price will revert to the mean price in the future. In this research, the method to determine the existence of mean-reversion of soybean price dynamics is discussed. Then, the future contract of soybeans is calculated using mean-reversion simulation and the spot-future parity theorem. Both methods are applied to the closing price of soybeans for the period of 19 September 2011 to 28 April 2016. The results show that the future contract price calculated by Model Mean-Reversion simulation under estimate the future contract price determined by the spot-future parity theorem.
PENERAPAN BRANCH AND BOUND ALGORITHM DALAM OPTIMALISASI PRODUKSI ROTI
GEDE SURYAWAN;
NI KETUT TARI TASTRAWATI;
KARTIKA SARI
E-Jurnal Matematika Vol 5 No 4 (2016)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
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DOI: 10.24843/MTK.2016.v05.i04.p134
Companies which engaged in production activities such as Ramadhan Bakery would want optimal profit in their every production. The aim of this study was to find optimal profit and optimal combination of bread production (original chocolate bread, extra chocolate bread, rounding chocolate bread and mattress chocolate bread) that was produced by Ramadhan Bakery by applying Branch and Bound Algorithm method. Branch and Bound Algorithm is one method to solve Integer Programming’s problems other than Cutting Plane method. Compared with Cutting Plane method, Branch and Bound Algorithm method is more effective in determining the optimal value. As the result of this study showed that to get optimal profit, Ramadhan Bakery should produce 360 pcs of original chocolate bread, 300 pcs of extra chocolate bread, 306 pcs of rounding chocolate bread and 129 pcs of mattress chocolate bread with optimal profit amounts Rp. 1.195.624,00.. The profit will increase amounts 25,2 % than before.
PERAMALAN CURAH HUJAN MENGGUNAKAN METODE ANALISIS SPEKTRAL
NI PUTU MIRAH SRI WAHYUNI;
I WAYAN SUMARJAYA;
I GUSTI AYU MADE SRINADI
E-Jurnal Matematika Vol 5 No 4 (2016)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
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DOI: 10.24843/MTK.2016.v05.i04.p139
The purpose of this research is the model of forecasting rainfall using spectral analysis method. To obtain complete information on characteristics of time series data we need to examine periodicity of the data. Examining the periodicity of time series data in the frequency domain is called spectral analysis. The results of spectral analysis show that periodogram is clearly dominated by a very large peak at frequency . This frequency corresponds to period of 12 cycle per month. Based on the results of analysis of time series data rainfall is SARIMA (0,1,1)(0,1,1)12 where the model can be written as The result indicates minimum rainfall happen in January and maximum rainfall happen in August.
PENERAPAN METODE BINOMIAL TREE DALAM MENGESTIMASI HARGA KONTRAK OPSI TIPE AMERIKA
I GUSTI AYU MITA ERMIA SARI;
KOMANG DHARMAWAN;
TJOKORDA BAGUS OKA
E-Jurnal Matematika Vol 5 No 4 (2016)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
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DOI: 10.24843/MTK.2016.v05.i04.p135
Binomial tree is a method that can be used to determine price option contracts. In this method, the stock price movement is presented in the form of a tree with each branch representing the probability of the stock price to move up or move down. The purpose of this paper was to determine the price of the options contracts with the American type on Binomial Tree method and compare the three methods that is variance matching, proportional , and risk neutral of determining the value of price option contracts used in Binomial Tree method with Black-Schole method. The result of this research was the value of the options contract using the variance matching more similar with the value of the Black-Scholes contract.
ANALISIS KUNJUNGAN ULANG WISATAWAN NUSANTARA DENGAN MODEL KONSTRUK BERHIERARKI
DWI HERAYANTHI W.;
KOMANG GDE SUKARSA;
TJOKORDA BAGUS OKA;
EKA N. KENCANA
E-Jurnal Matematika Vol 5 No 4 (2016)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
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DOI: 10.24843/MTK.2016.v05.i04.p140
This research is aimed to analyze the effect of domestic tourists’ satisfaction towards their intention to revisit destinations at Badung Regency, Province of Bali by using hierarchical construct modeling. Data from 75 local tourists were collected in July through December 2015 and were used to model this causal relationship. In our model, destination attributes, tourist’s facilities, and destination accessibilities were positioned as the second-order constructs and proposed have effect on tourists’ satisfaction. Futhermore, satisfaction – in turns – is proposed affects tourist intention to revisit. We found destination attributes significantly affect tourist satisfaction with its causal value is 0.410 and this satisfaction significantly affects their intention to revisit tourism destinations at Badung Regency with path value as much as 0.764.
IMPLEMENTASI BACKPROPAGATION NEURAL NETWORK DALAM PRAKIRAAN CUACA DI DAERAH BALI SELATAN
I MADE DWI UDAYANA PUTRA;
G. K. GANDHIADI;
LUH PUTU IDA HARINI
E-Jurnal Matematika Vol 5 No 4 (2016)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
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DOI: 10.24843/MTK.2016.v05.i04.p131
Weather information has an important role in human life in various fields, such as agriculture, marine, and aviation. The accurate weather forecasts are needed in order to improve the performance of various fields. In this study, use artificial neural network method with backpropagation learning algorithm to create a model of weather forecasting in the area of ??South Bali. The aim of this study is to determine the effect of the number of neurons in the hidden layer and to determine the level of accuracy of the method of artificial neural network with backpropagation learning algorithm in weather forecast models. Weather forecast models in this study use input of the factors that influence the weather, namely air temperature, dew point, wind speed, visibility, and barometric pressure.The results of testing the network with a different number of neurons in the hidden layer of artificial neural network method with backpropagation learning algorithms show that the increase in the number of neurons in the hidden layer is not directly proportional to the value of the accuracy of the weather forecasts, the increase in the number of neurons in the hidden layer does not necessarily increase or decrease value accuracy of weather forecasts we obtain the best accuracy rate of 51.6129% on a network model with three neurons in the hidden layer.
ANALISIS HUBUNGAN PRODUKSI PADI DAN INDIKATOR ENSO DI KABUPATEN TABANAN DENGAN PENDEKATAN COPULA
LUH GEDE UDAYANI;
I WAYAN SUMARJAYA;
MADE SUSILAWATI
E-Jurnal Matematika Vol 5 No 4 (2016)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
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DOI: 10.24843/MTK.2016.v05.i04.p136
Dependence relationship between two or more variables is an issue that is often studied in the science of probability and statistics. Pearson correlation is often the easiest option to measure dependencies between variables. It is well known, that Pearson correlation assumes that the variable under study must be normally distributed. However, in reality this is not the case; for example, data in fields such as climatology and meteorology, insurance, and financial. Copula is a tool that can be used to model the joint distribution because it does not require the assumption of normality of the data so that it is resilient against a wide range of data. In this study, we discussed the application of copula in modeling the structure of dependencies between two variables: the production of rice and El-Nino Southern Oscillation (ENSO) indicator per period in Tabanan Regency. The best dependency model structure is given by the Frank copula of the Archimedean copula family with estimation parameter, ? = 2,817 and the loglikelihood value of 3,47.
PERBANDINGAN REGRESI ZERO INFLATED POISSON (ZIP) DAN REGRESI ZERO INFLATED NEGATIVE BINOMIAL (ZINB) PADA DATA OVERDISPERSION (Studi Kasus: Angka Kematian Ibu di Provinsi Bali)
NI PUTU PREMA DEWANTI;
MADE SUSILAWATI;
I GUSTI AYU MADE SRINADI
E-Jurnal Matematika Vol 5 No 4 (2016)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
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DOI: 10.24843/MTK.2016.v05.i04.p132
Poisson regression is a nonlinear regression which is often used for count data and has equidispersion assumption (variance value equal to mean value). However in practice, equidispersion assumption is often violated. One of it violations is overdispersion (variance value greater than the mean value). One of the causes of overdipersion is excessive number of zero values on the response variable (excess zeros). There are many methods to handle overdispersion because of excess zeros. Two of them are Zero Inflated Poisson (ZIP) regression and Zero Inflated Negative Binomial (ZINB) regression. The purpose of this research is to determine which regression models is better in handling overdispersion data. The data that can be analyzed using the ZIP and ZINB regression is maternal mortality rate in the Province of Bali. Maternal mortality rate data has proportion of zeros value more than 50% on the response variable. In this research, ZINB regression better than ZIP regression for modeling maternal mortality rate. The independent variable that affects the number of maternal mortality rate in the Province of Bali is the percentage of mothers who carry a pregnancy visit, with ZINB regression models and .