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INDONESIA
E-Jurnal Matematika
Published by Universitas Udayana
ISSN : 23031751     EISSN : -     DOI : -
Core Subject : Education,
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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Articles 9 Documents
Search results for , issue "Vol 11 No 3 (2022)" : 9 Documents clear
IMPLEMENTASI FUZZY C-MEAN DAN ALGORITMA PARTICLE SWARM OPTIMIZATION UNTUK CLUSTERING KABUPATEN/KOTA DI INDONESIA BERDASARKAN INDIKATOR INDEKS PEMBANGUNAN MANUSIA I KADEK SONA DWIGUNA; G.K. GANDHIADI; LUH PUTU IDA HARINI
E-Jurnal Matematika Vol 11 No 3 (2022)
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.2022.v11.i03.p380

Abstract

This research is aimed to determine conduct clustering in accordance with the conditions of districts / cities throughout Indonesia based on the IPM indicator and to determine the performance comparison of Fuzzy C-Means using particle swarm optimization compared to ordinary fuzzy c mean. The study uses 514 district / city data in Indonesia based on four IPM indicators. The research show 4 clusters that describe the condition of the Indonesian region and based on the results of cluster validation shows that there are differences in the ordinary Fuzzy C-Means mean algorithm and Fuzzy C-Means using particle swarm optimization.
IDENTIFIKASI FAKTOR YANG MEMENGARUHI GINI RATIO DI INDONESIA GUSTI AYU MADE CANDRA RINI; NI LUH PUTU SUCIPTAWATI; IDA AYU PUTU ARI UTARI
E-Jurnal Matematika Vol 11 No 3 (2022)
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.2022.v11.i03.p376

Abstract

Inequality in income distribution is one of the problems that are often experienced by some countries in the world. Income inequality in Indonesia is measured by an indicator named Gini Ratio. BPS Indonesia noted that in March 2021, the Gini Ratio in Indonesia was 0,384. This figure shows that Indonesia belongs to the category of moderate income inequality, which means that income in Indonesia is not well distributed or there is an inequality in income distribution. For this reason, the inequality that occurs needs to be decreased by recognizing the factors that affect it. The purpose of this study was to determine the factors that significantly affect the Indonesia’s Gini Ratio in 2016-2020 by applying panel data regression. The results show that the model chosen to represent the Indonesia’s Gini Ratio in 2016-2020 is a fixed time effect model with of 40,282%, which is significantly be affected by the human development index, population, open unemployment rate, percentage of poor people, and average hourly wage for worker.
PENGGUNAAN SIMULASI MONTE CARLO DALAM ESTIMASI VALUE AT RISK (VaR) PORTOFOLIO YANG DIBENTUK DARI INDEKS HARGA SAHAM MULTINASIONAL NABILA NUR JANNAH; KOMANG DHARMAWAN; LUH PUTU IDA HARINI
E-Jurnal Matematika Vol 11 No 3 (2022)
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.2022.v11.i03.p381

Abstract

Investment is buying an asset that is expected in the future can be resold and get a high profit value. There are two factors that must be considered when you want to invest in stocks, namely the rate of return on stocks and risk factors. By forming a portfolio is expected to minimize a risk. Value at Risk (VaR) is a form of measurement of risk when making investments. In this study VaR will be calculated using the Monte Carlo Simulation method and the Historical method. This study aims to find out var portfolio estimates involving JCI and DJIA stock indices from two different countries as well as to find out the differences between VaR using Historical and VaR using Monte Carlo Simulations. From the stock index data obtained further determined the value of the parameters, namely the expected return and standard deviation values used to calculate the value of the VaR Portfolio, while the confidence increase used in this study was 99% and with a period of 1 or the next day. Based on the results of the VaR value study using the Monte Carlo Simulation method and the Historical method, the Historical method obtained results of 3,650,506 and 1,029,103. The results showed that VaR values using the Monte Carlo Simulation method got greater results than using the Historical method, because the Monte Carlo Simulation performed repeated iterations by including random number generators.
METODE ANALISIS REGRESI SPASIAL DALAM MEMODELKAN KASUS COVID-19 DI INDONESIA NI MADE PUSPASARI; NI LUH PUTU SUCIPTAWATI; MADE SUSILAWATI
E-Jurnal Matematika Vol 11 No 3 (2022)
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.2022.v11.i03.p377

Abstract

Covid-19 is an infectious disease caused by Severe Acute Respiratory Syndrome Coronavirus 2. The transmission of Covid-19 has negative impact on every aspect. This study aimed to determine the factors that significantly affect the number of Covid-19 cases in Indonesia. Spatial regression analysis was used as the research method. The results obtained that on the dependent variable there is a spatial dependence, so the selected model is Spatial Autoregressive Model (SAR) with an AIC value of 759.09 and an value of 58.49%. The significant influencing factor is proportion of the population over 50 years old and open unemployment rate.
FAKTOR-FAKTOR YANG MELATARBELAKANGI KEPUTUSAN BELANJA ONLINE PADA APLIKASI E-COMMERCE NI KADEK DWI ARISYA AFRILIANTI; MADE SUSILAWATI; I GUSTI AYU MADE SRINADI
E-Jurnal Matematika Vol 11 No 3 (2022)
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.2022.v11.i03.p382

Abstract

The existence of the COVID-19 Pandemic since 2020 has forced the central government to impose large-scale social restrictions (PSBB) in the various region in Indonesia. This restriction aims to minimize the spread of the COVID-19 virus, but this causes results in many people losing their jobs. This study uses confirmatory factor analysis to examine the factors behind online shopping decisions at stores in e-commerce applications. The results of this study aim to determine what factors are behind the decision of buyers to shop online in e-commerce applications. The research variable consists of eight dimensions: product, price, place, promotion, customer service, convenience, security, and trust, with 33 indicators. The sample in this study was the people of Denpasar City, totaling 232 respondents who had shopped online at least three times in the last six months. The results of the factor analysis obtained that it is true that there are eight factors behind online shopping decisions at shops in e-commerce applications by people in Denpasar City. These results can be considered for online entrepreneurs to increase sales results by sellers and as a reference by buyers in determining what can be regarded as in online shopping.
ANALISIS PERBANDINGAN METODE EXPONENTIAL APPROACH DAN METODE IMPROVED ZERO POINT UNTUK MEMINIMUMKAN BIAYA PENDISTRIBUSIAN NI KADEK JIANTARI; G.K. GANDHIADI; RATNA SARI WIDIASTUTI
E-Jurnal Matematika Vol 11 No 3 (2022)
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.2022.v11.i03.p378

Abstract

The purpose of this study is to do a comparative of the minimum cost of distributing mountea drinks using the exponential approach and the improved zero point method. The exponential approach method is a direct method where the allocation in this method depends on the number of zeros that appear in the transportation table. In the case of an unbalanced transportation problem, a dummy line (column) will appear where the cost on the line (column) is zero, which will greatly affect the optimum results of the given exponential approach method. The improved zero point method is an improved method from the zero point method, which is very useful for solving all types of transportation problems. This method provides an optimal solution without the help of other modified methods. Based on the results of the research, it was shown that the distribution cost of mountea drinks from the wholesale center in the Lunyuk sub-district using an exponential approach and an improved zero point obtained a cost of 10,392,276 Rupiah before the optimization, while the while the comparative distribution cost of the mountea drinks from the wholesale center in the Lunyuk sub-district after the optimization using an exponential approach and an improved zero point obtained a cost same of 8.552.560 Rupiah.
PENERAPAN FUZZY TIME SERIES DALAM MERAMALKAN JUMLAH WISATAWAN DI MASA PANDEMI COVID19 BESSE HELMI MUSTAWINAR; NURUL FUADY ADHALIA H; MARWAN SAM
E-Jurnal Matematika Vol 11 No 3 (2022)
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.2022.v11.i03.p374

Abstract

Tourism is one of Indonesia’s assets to promote economic growth. This sector became one of the largest contributors to national foreign exchange. The number of foreign tourist visits is an indicator of the contribution of tourism which has experiencing the upward trend in annually until the Covid19 happened. In this study, forecasting the number of foreign tourists is needed as a plan to improve the quality of tourism during the pandemic. We used Fuzzy Time Series (FTS) Cheng method. The actual data processed comes from the Central Statistics Agency from April 2020 through December 2021. Based on forecasting results, the performance of the forecasting model is in the very good category with Mean Absolute Percentage Error (MAPE) value is 5.06%. It means that our predictions are on average 5.06% away from the actual values they were aiming for. In other side, we have forecasting accuracy value is 94.94% which means that the forecast values were close to the actual. Keywords: Tourist, FTS, Cheng Methods
MEMODELKAN PRODUK DOMESTIK REGIONAL BRUTO DI INDONESIA MENGGUNAKAN REGRESI DATA PANEL SPASIAL NI KADEK AYU PUJI ASTUTI; NI LUH PUTU SUCIPTAWATI; MADE SUSILAWATI
E-Jurnal Matematika Vol 11 No 3 (2022)
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.2022.v11.i03.p379

Abstract

Gross regional domestic product (GRDP) is one of the important indicators to determine economic conditions in a region. The magnitude of the growth rate of GRDP is developed by the progress of regional economic development, both carried out by the government and the private sector in order to improve the welfare of the population. The purpose of this study is to examine the business sector that has the most significant influence on GRDP in Indonesia by applying spatial panel data regression. The results show that the best model in modeling GRDP in Indonesia is the spatial lag common effect which has an value of 83,13% while the independent variables that are significant to the increase in GRDP can be divided into two, namely significant positive and significant negative effects. The variables that have a significant and positive effect on GRDP are agriculture, forestry, and fisheries , mining and quarrying electricity and gas supply, water supply, waste management, waste and recycling, construction, financial services and insurance, real estate, and other services. wholesale and retail trade; car and motorcycle repair, transportation and warehousing, company services education services .
PENERAPAN METODE DOUBLE EXPONENTIAL SMOOTHING UNTUK MERAMALKAN PRODUKSI DAN KONSUMSI DOMESTIK BERAS DI INDONESIA PUTRI NUR PRASETIA; ANITA TRISKA; JULITA NAHAR
E-Jurnal Matematika Vol 11 No 3 (2022)
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.2022.v11.i03.p375

Abstract

Rice is one of the most important commodities in Indonesia since it is one of the staple foods.Therefore, it becomes one of Indonesian government concerns by setting a goal of 46,8 million tons of rice supply in 2024. Despite 29,67% of the population earns their living from agriculture, forestry, and fisheries, the domestic production of rice could not meet its demand many times. Hence, the forecasting of the production and domestic consumption of rice is needed to know whether the domestic production is able to meet the demand. In this study, the rice production and domestic consumption were forecasted using the Double Exponential Smoothing (DES) method. The DES was chosen due to the pattern of the data shows the trends without seasonality. The accuracy of the forecasting was measured by Mean Absolute Percentage Error (MAPE) and Durbin-Watson statistic test. The yielded forecasts showed that the production rate is lower than the domestic consumption’s so that it would not meet the demand. It was concluded that the DES suitable to be used to forecast production and domestic consumption of rice in Indonesia since its MAPE are 6,48% and 5,91%, respectively. Moreover, the Durbin-Watson statistic showed that there was no autocorrelations on the errors of both data.

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