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PERAMALAN INDEKS HARGA PROPERTI RESIDENSIAL MENGGUNAKAN METODE BAYES PUTU GDE BUDHA WIRYADANA; I WAYAN SUMARJAYA; I KOMANG GDE SUKARSA
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.p324

Abstract

Residential property is a property in the form of building which serves as residence or house. House has function as a place whether to take a rest, to take cover and to get together with family. Residential property price indices (RPPIs) forecasting has aim as a development planning by the developer to avoid shortages or excess of home supplies. This research aims to model and predict the RPPIs using the Bayes method for 2020 to 2021. The data used in this research is the data from RPPIs of Denpasar city from 2012 in the first quarter to 2019 in the fourth quarter. Then, the method which is used is Bayes method with autoregression (AR) model in forecasting RPPIs. Therefore, it obtained mean absolute percentage error (MAPE) for forecasting the next one period with () equal to 0,4049416%. For the result of RPPIs forecasting in Denpasar city from 2020 the first quarter to 2021 the fourth quarter has an insignificant increase with an average difference for each quarter increased by 0,3568%.
PEMODELAN PENYEBARAN KASUS DEMAM BERDARAH DENGUE (DBD) DI KOTA DENPASAR DENGAN METODE SPATIAL AUTOREGRESSIVE (SAR) NI MADE SURYA JAYANTI; I WAYAN SUMARJAYA; MADE SUSILAWATI
E-Jurnal Matematika Vol 6 No 1 (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.i01.p146

Abstract

One of spatial regression model is Spatial Autoregressive (SAR), which assumes that the autoregressive process only on the dependent variable only by considering the spatial effects. There are two aspects of spatial effects, that is spatial dependence and spatial heterogeneity. One of the problems which considers spatial effect is the spread of Dengue Hemorrhagic Fever (DHF). Denpasar City is an endemic DHF disease because there have been DHF cases in three consecutive years or more. The purpose of this research is to estimate the spread of DHF in  Denpasar City along with the factors that affect it. The results show that the factors that influence the spread of DHF are neighborhood, area and the role of Jumantik at the every village in Denpasar City.
PENENTUAN HARGA JUAL OPSI BARRIER TIPE EROPA DENGAN METODE ANTITHETIC VARIATE PADA SIMULASI MONTE CARLO LUH HENA TERECIA WISMAWAN PUTRI; KOMANG DHARMAWAN; I WAYAN SUMARJAYA
E-Jurnal Matematika Vol 7 No 2 (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.i02.p187

Abstract

The purpose of this research is to compare the selling price of down and out barrier option when the prices are simulated by the Antithetic Variate Monte Carlo and the standar Monte Carlo. Barrier options are path dependent options and the payoff depend on whether the underlying asset price touched the barrier or not during the life of the option. In this research, we conducted simulations against the closing price of the shares of PT Adhi Karya using Standard Monte Carlo simulation and the Monte Carlo-Antithetic Variate simulation. After the simulation, we obtained that the option prices using Antithetic Variate produces a cheaper price than the standar one. We also found that the analytic solution has a smaller error on its confidence interval compare to the Monte Carlo Standar.
PERAMALAN VOLATILITAS DAN ESTIMASI VALUE AT RISK (VaR) SAHAM BLUE CHIP PADA SEKTOR PERBANKAN NI KADEK JULIARINI; I WAYAN SUMARJAYA; KARTIKA SARI
E-Jurnal Matematika Vol 10 No 4 (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.i04.p343

Abstract

Investment is an activity to invest an asset to obtain a greater profit. The investment there's in great demand by investors are stock investments. Based on market capitalization, stocks are classified into first-tier, second-tier, and third-tier stocks. Stocks that have the highest market capitalization are first-tier or blue-chip stocks. Blue-chip stocks are stocks that are classified as main shares on the listing board on the IDX. Before investing, it's important to know the level of investment risk in order to make the right investment decisions. The purpose of this study is to determine the risk of investing in blue-chip stocks namely BRI, BCA, and Bank Mandiri through volatility forecasting using the GARCH, EGARCH, or TGARCH models. The data used is the daily closing price of shares for the period of 25 May 2005 to 21 May 2021 which was obtained through the Yahoo Finance website. Based on the research results, it's known that Bank Mandiri has the highest investment risk and BCA has the lowest investment risk. Based on these results, it can be suggested that investors who like risk can choose to invest in Bank Mandiri shares, and those who don't like risk can invest in BCA shares.
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.
KAUSALITAS KONTRIBUSI INDUSTRI PARIWISATA DAN JUMLAH KUNJUNGAN WISATAWAN TERHADAP PERTUMBUHAN EKONOMI COKORDA BAGUS YUDISTIRA; I WAYAN SUMARJAYA; LUH PUTU IDA HARINI
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.p222

Abstract

Bali is known as one of the most popular tourism destination in the world. The number of tourist visit to Bali increases every year. In 2010, there roughly 7 millions tourist visits to Bali and reach up to 14 million people by the end of 2017. This increased in number may affect the growth of tourism industries and economic growth in Bali Province. This study aims to analyze the patterns of causal relationship between tourism industry receipts, tourist visits, and economic growth in Bali based on time series data using vector autoregressive (VAR) model. The results conclude the following: (i) foreign tourist visits is significantly affect economic growth. In addition, economic growth, domestic tourist visits, and foreign tourist visits are significantly impact to tourism industry receipts, (ii) economic growth would affect the tourism industry receipts in the next four consecutive months, (iii) the forecasting result of economic growth with VAR model is highly accurated with MAPE 2%.
MODEL DINAMIS AUTOREGRESSIVE DISTRIBUTED LAG (STUDI KASUS: PENGARUH KURS DOLAR AMERIKA DAN INFLASI TERHADAP HARGA SAHAM TAHUN 2014-2018) MAHMUDATUL AQIBAH; NI LUH PUTU SUCIPTAWATI; I WAYAN SUMARJAYA
E-Jurnal Matematika Vol 9 No 4 (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.i04.p304

Abstract

The aim of this research is to determine the dynamic model equation of autoregressive distributed lag by using koyck method, to find out the effect of log US dollar exchange rate and log inflation on log stock price in 20142018, and to forecast value of log stock price on January 2019August 2019. The data used in 20142018. The data was transformed into logarithm format. Time series plot of log US dollar exchange rate, log inflation, and log stock price suggest that the fluctuation in the data, for instance, both upward and downward trends, during the period. We obtained that the Koyck transformation could changed the lag distribution model into autoregressive distributed lag (ARDL) dynamic model. Furthermore, the log of US dollar exchange rate and log inflation have negative effect on log stock price in particular period. We measured forecasting accuracy using mean absolute prediction error (MAPE) and concluded that ARDL forecasting using Koyck model shows a significant increase in stock price.
PERAMALAN MENGGUNAKAN METODE BACKPROPAGATION NEURAL NETWORK MADE NITA DWI SAWITRI; I WAYAN SUMARJAYA; NI KETUT TARI TASTRAWATI
E-Jurnal Matematika Vol 7 No 3 (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.i03.p213

Abstract

The purpose of the study is to forecast the price of rice in the city of Denpasar in 2017 using backpropagation neural network method. Backpropagation neural network is a model of artificial neural network by finding the optimal weight value. Artificial neural networks are information processing systems that have certain performance characteristics similar to that of human neural networks. This analysis uses time series data of rice prices in the city of Denpasar from January 2001 until December 2016. The results of this research, concludes that the lowest rice price is predicted in July 2017 at Rp9791.5 while the highest rice price in April 2017 for Rp9839.4.
PERAMALAN JUMLAH PENUMPANG PESAWAT BANDARA I GUSTI NGURAH RAI MENGGUNAKAN EXPONENTIAL SMOOTHING DAN RUEY-CHYN TSAUR WILDAN FATTURAHMAN MUJTABA; I GUSTI AYU MADE SRINADI; I WAYAN SUMARJAYA
E-Jurnal Matematika Vol 10 No 4 (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.i04.p346

Abstract

Bali province is a tourist destination island with good transportation. Airplane is the most used transportation to go to Bali. Convenience of the airline passengers are the most important thing for I Gusti Ngurah Rai Airport Authorithy. An exact forecast method is needed to predict the numbers of passenger in the future. There are two types of forecasting methods; triple exponential smoothing and Fuzzy Time Series Ruey-Chyn Tsaur, however based on the research Fuzzy Time Series Ruey-Chyn Tsaur is better than triple exponential smoothing due to a small error MAPE (Mean Absolute Percentage Error) of 2,4% and plot is close to actual data.
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%.
Co-Authors ADE KUSUMA DEWI Ade Widyaningsih ALEXANDER HIRO WIBISONO ANAK AGUNG ISTRI AGUNG CANDRA ISWARI AULIA ATIKA PRAWIBTA SUHARTO Chairun Nisa Chrisna Anzella Jacob COKORDA BAGUS YUDISTIRA DESAK AYU WIRI ASTITI Dewa Ken Budiputra DIAN RAHMAN EKA N. KENCANA FITRI ANANDA DITA SARASWITA G. K. Gandhiadi GILANG BIMASAKTI ANDHIKA GUSTI AYU PUTU YULIANDARI HERLINA HIDAYATI I GEDE DICKY ARYA BRAMANTA I GEDE MAHA HENDRA PRATAMA I Gusti Ayu Made Srinadi I GUSTI AYU MEIGAYONI LESTARI I Ketut Darmana I KETUT PUTRA ADNYANA I KOMANG GDE SUKARSA I MADE BUDIANTARA PUTRA I Nyoman Sama I Nyoman Widana I Putu Eka Nila Kencana I PUTU GEDE DIAN GERRY SUWEDAYANA I Wayan Suirta IRENE MAYLINDA PANGARIBUAN JUITA HARYATI SIDADOLOG JULIANTARI JULIANTARI KADEK DITA SUGIARI Kartika Sari Kartika Sari KASTIN DWILEN PONG SUMAE Ketut Jayanegara KHOSYI RUKITO KOMANG CANDRA IVAN Komang Dharmawan KOMANG KOKOM SUCAHYATI DEWI P LUH GEDE UDAYANI LUH HENA TERECIA WISMAWAN PUTRI LUH PUTU ARI DEWIYANTI LUH PUTU IDA HARINI MADE NITA DWI SAWITRI Made Susilawati MAHMUDATUL AQIBAH MIRA AYU NOVITA SARI NATASYA WIDIA PUTRI NI KADEK JULIARINI NI KADEK YUNI DEWIANTARI Ni Ketut Linda Aryani Ni Ketut Tari Tastrawati NI KOMANG DEBY ARIANI Ni Luh Putu Ayu Fitriani Ni Luh Putu Diah Ayu Candrasuari Ni Luh Putu Suciptawati Ni Made Asih NI MADE LASTI LISPANI NI MADE RARA KESWARI Ni Made Sri Wahyuni NI MADE SURYA JAYANTI NI PUTU AYU DEWI CAHYANTARI NI PUTU DEVIYANTI NI PUTU MEILING UTAMI NI PUTU MIRAH SRI WAHYUNI NI PUTU NIA IRFAGUTAMI NI PUTU WIDYA ISWARI DEWI NI PUTU YULIKA TRISNA WIJAYANTI NI WAYAN DIAH SIHMAWATI Ni Wayan Merry Nirmala Yani NI WAYAN UCHI YUSHI ARI SUDINA NOVIAN ENDI GUNAWAN NUR FAIZA NURMA ALIYUWANINGSIH NYOMAN KRISHNA PRATIWI DANGIN PUTU AMANDA SETIAWANI PUTU EKA ARIWIJAYANTHI PUTU GDE BUDHA WIRYADANA RAMADHAN LENGGU RAMLI RENALDO EVIPANIA SITI RAHAYU NINGSIH TJOK GDE SAHITYAHUTTI RANANGGA Tjokorda Bagus Oka TRISNA RAMADHAN ULYATIL AENI VINSENTIA REVICA BELLA ROSSARY WILDAN FATTURAHMAN MUJTABA WIMAS ASTARI YUDA