scholarly journals FOREIGN TOURIST ARRIVAL FORECASTING TO BALI USING CASCADE FORWARD BACKPROPAGATION

Kursor ◽  
2020 ◽  
Vol 10 (4) ◽  
Author(s):  
Ayu Nikki Asvikarani ◽  
I Made Widiartha ◽  
Made Agung Raharja
Keyword(s):  
Good Accuracy ◽  
Consumer Price Index ◽  
Activation Function ◽  
Decision Makers ◽  
Foreign Tourist ◽  
Tourism Sector ◽  
Tourism Potential ◽  
Hidden Neurons ◽  
Sigmoid Activation Function ◽  
Better Than

Bali has a recognized tourism potential in the world arena. In order to improve the quality and development of the tourism sector in the midst of global competition, it is necessary to formulate appropriate strategies by decision makers such as private parties and government. In support of more accurate decision making, the authors make a system of forecasting the number of foreign tourist visits to Bali Province using Cascade Forward Backpropagation (CFB) method with coverage of Australia, Japan, and United Kingdom which are the top 3 countries with the highest foreign tourist arrival to Bali in that years. Factors used as input in forecasting include the number of visits of foreign tourists the previous year, the population of countries of origin of foreign tourists, Gross Domestic Product at current prices of countries of origin of foreign tourists, and Relative Consumer Price Index Origin of foreign tourists. In this study, optimization of activation function parameters, hidden neurons, and learning rate to obtain forecasting results with the lowest error rate. Forecasting results using the CFB method produces a fairly good accuracy with MAPE range of 6 - 30% where the activation function tanh work better than sigmoid activation function.

Prediction Of The Number Of Tourists To Visit Bali Province Using Backpropagation Artificial Neural Network (Case Study: Data 1990-2016)

2020 ◽  
Vol 8 (3) ◽  
pp. 243
Author(s):  
I Gusti Agung Ngurah Panji Palguna ◽  
I Made Widiartha
Keyword(s):  
Price Index ◽  
Good Accuracy ◽  
Consumer Price Index ◽  
Activation Function ◽  
Study Data ◽  
Tourist Destination ◽  
Tourism Sector ◽  
Backpropagation Method ◽  
Case Study Data

Bali Island is the most popular tourist destination in Indonesia. The total number of foreign tourists visiting Indonesia through the entrance of Ngurah Rai Airport reached 40% as of October 2016, with the value of Bali's foreign exchange receipts for Indonesia from the tourism sector amounting to 70 Trillion Rupiah. Minister of Tourism (Menpar) Arief Yahya always uses the password "Bali" in promoting destinations throughout the world. Because in tourism, Bali is a gate that is passed by 40 percent of foreign tourists (tourists) to Indonesia. In support of more accurate decision making, the author makes a system of forecasting numbers of foreign tourists visiting Bali Province by taking a sample of Japan. Factors that are used as input to make predictions include the number of tourists visiting before, the population of the country of origin of foreign tourists, Gross Domestic Product, and the Relative Consumer Price Index of the countries of origin of foreign tourists. In this research, optimization of the activation function, hidden neuron, and learning rate parameters is performed. Forecasting results using the backpropagation method produce a pretty good accuracy with an accuracy of Mean Square Error = 0.0050558, and test data accuracy of MSE = 0.031695. ANN architecture in the training process is then used to calculate predictions of visits by foreign tourists in the testing process

scholarly journals PERAMALAN KUNJUNGAN WISATAWAN MANCANEGARA KE PROVINSI BALI MENGGUNAKAN METODE ARTIFICIAL NEURAL NETWORK

2020 ◽  
Vol 9 (4) ◽  
pp. 213
Author(s):  
I KETUT RESTU WIRANATA ◽  
G.K. GANDHIADI ◽  
LUH PUTU IDA HARINI
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Back Propagation ◽  
Activation Function ◽  
Network Algorithms ◽  
Tourism Sector ◽  
Forecasting System ◽  
Artificial Neural ◽  
Tourism Potential ◽  
Sigmoid Activation Function

Bali has an increasing tourism potential. This is evidenced by the increasing number of foreign tourist visits to Bali Province each year. Although Bali's tourism trends have continued to increase over the past few years, efforts to improve the quality of Bali tourism need to be made. One way is to do forecasting. To support improvement efforts in Bali's tourism sector, the author created a forecasting system for foreign tourists to Bali province using artificial neural network methods with back propagation algorithms. Artificial Neural Networks with back propagation algorithms are neural network algorithms by finding optimal weight values. The forecast results using the binary sigmoid activation function were obtained by 489,862 foreign tourists in November 2019 with MAPE at 1.62% and 487,342 foreign tourists in December 2019 with MAPE of 11.78%. The forecast results using the bipolar sigmoid activation function were obtained by 493,200 foreign tourists in November 2019 with MAPE of 0.95% and 484,090 foreign tourists in December 2019 with MAPE of 12.37%.

scholarly journals Extreme Learning Machine with sigmoid activation function on large data

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3523-3526
Keyword(s):  
Efficient Algorithm ◽  
Large Data ◽  
Activation Function ◽  
Large Data Sets ◽  
Data Sets ◽  
Data Set ◽  
Learning Machine ◽  
Sigmoid Activation Function ◽  
State Of Art ◽  
Better Than

This paper describes an efficient algorithm for classification in large data set. While many algorithms exist for classification, they are not suitable for larger contents and different data sets. For working with large data sets various ELM algorithms are available in literature. However the existing algorithms using fixed activation function and it may lead deficiency in working with large data. In this paper, we proposed novel ELM comply with sigmoid activation function. The experimental evaluations demonstrate the our ELM-S algorithm is performing better than ELM,SVM and other state of art algorithms on large data sets.

Prediction of Humid Air Heat Exchanger Performance Using Artificial Neural Networks

1999 ◽  
Author(s):  
Arturo Pacheco-Vega ◽  
Mihir Sen ◽  
K. T. Yang ◽  
Rodney L. McClain
Keyword(s):  
Neural Network ◽  
Heat Exchanger ◽  
Activation Function ◽  
Humid Air ◽  
The Neural Network ◽  
Artificial Neural ◽  
Fin Tube ◽  
Experimental Values ◽  
Sigmoid Activation Function ◽  
Better Than

Abstract In the present study we apply an artificial neural network to predict the operation of a humid air-water fin-tube compact heat exchanger. The network configuration is of the feedforward type with a sigmoid activation function and a backpropagation algorithm. Published experimental data, corresponding to humid air flowing over the heat exchanger tubes and water flowing inside them, are used to train the neural network. After training with known experimental values of the humid-air flow rates, dry-bulb and wet-bulb inlet temperatures for various geometrical configurations, the j-factor and heat transfer rate predictions of the network were tested against the experimental values. Comparisons were made with published predictions of power-law correlations which were obtained from the same data. The results demonstrate that the neural network is able to predict the performance of this heat exchanger much better than the correlations.

SCORING MODELING BASED ON NEURAL NETWORKS FOR DETERMINING A BANK BORROWER'S RATING

2020 ◽  
Vol 2020 (10) ◽  
pp. 54-62
Author(s):  
Oleksii VASYLIEV ◽  
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Network Architecture ◽  
Statistical Data ◽  
Activation Function ◽  
Decision Making Process ◽  
Neural Network Architecture ◽  
Acceptable Accuracy ◽  
The Neural Network ◽  
Sigmoid Activation Function

The problem of applying neural networks to calculate ratings used in banking in the decision-making process on granting or not granting loans to borrowers is considered. The task is to determine the rating function of the borrower based on a set of statistical data on the effectiveness of loans provided by the bank. When constructing a regression model to calculate the rating function, it is necessary to know its general form. If so, the task is to calculate the parameters that are included in the expression for the rating function. In contrast to this approach, in the case of using neural networks, there is no need to specify the general form for the rating function. Instead, certain neural network architecture is chosen and parameters are calculated for it on the basis of statistical data. Importantly, the same neural network architecture can be used to process different sets of statistical data. The disadvantages of using neural networks include the need to calculate a large number of parameters. There is also no universal algorithm that would determine the optimal neural network architecture. As an example of the use of neural networks to determine the borrower's rating, a model system is considered, in which the borrower's rating is determined by a known non-analytical rating function. A neural network with two inner layers, which contain, respectively, three and two neurons and have a sigmoid activation function, is used for modeling. It is shown that the use of the neural network allows restoring the borrower's rating function with quite acceptable accuracy.

Strategi Pengembangan Pariwisata Pasca Bencana Tsunami di Kabupaten Lampung Selatan

2020 ◽  
Vol 2 (2) ◽  
pp. 243-257
Author(s):  
Sofyan Sofyan ◽  
◽  
Dian Kagungan ◽  
Nana Mulyana ◽  
◽  
...  
Keyword(s):  
Development Process ◽  
Descriptive Analysis ◽  
Tourism Development ◽  
Data Presentation ◽  
Analysis Techniques ◽  
Tsunami Disaster ◽  
Tourist Destinations ◽  
Tourism Sector ◽  
Descriptive Approach ◽  
Tourism Potential

Lampung is one of the provinces that has a considerable tourism potential in which each region has tourism potential with its own unique attraction in South Lampung regency. However, the Tsunami disaster that struck the coastal areas of Banten and South Lampung on 22 Desemeber 2018, impacted the decline in the number of tourists visiting the archipelago and abroad to tourist destinations by the end of year 2018. Based on the problems raised above, the purpose of this research is to describe and analyze the strategy conducted by the Tourism and culture Office of South Lampung Regency in the effort to develop tourism sector in South Lampung district after Tsunami disaster. This type of research is qualitative research with a descriptive approach. The research informant is determined purpossive. Data collection techniques are conducted with observations, interviews and documentation. Data analysis techniques are carried out with data reduction, data presentation, drawing conclusions and data triangulation. Data is presented and in a descriptive analysis. Based on the results of the research is known that the Tourism and culture Department of South Lampung district has a strategy to develop tourism potential in South Lampung regency. In determining a strategy for tourism development in South Lampung District after the Tsunami disaster pay attention to four basic factors. These four factors are strengths, weaknesses, opportunities and threats with some sectors involved in the tourism development process. The conclusion of this research is based on the SWOT anilisis which produces four strategies i.e. SO strategy, WO Strategy, Strategy ST, and WT strategy

scholarly journals The Relative Success of WTO Dispute Settlement and What Planet Would the EU Investment Court System Be On? A Rejoinder to AJIL Unbound Comments

AJIL Unbound ◽  
2015 ◽  
Vol 109 ◽  
pp. 316-318
Author(s):  
Joost Pauwelyn
Keyword(s):  
World Trade ◽  
Public Perception ◽  
Dispute Settlement ◽  
Decision Makers ◽  
The Other ◽  
Court System ◽  
Wto Dispute Settlement ◽  
The Many ◽  
Better Than ◽  
The Eu

I am extremely grateful, and humbled, by the wealth of comments received on my AJIL article through this AJIL Unbound Symposium. One of the many points I take away from these reactions is, indeed, that my analysis offers a snapshot and that many of the critiques now leveled against Investor-State Dispute Settlement (ISDS) are, in Catherine Rogers’s words, “effectively recycled versions of criticisms that were originally leveled against the WTO and its decision-makers.” (Freya Baetens makes a similar point.)In this rejoinder, I would only like to make two points. Firstly, many commentators seem to think that in this article I took the normative position that World Trade Organization (WTO) dispute settlement is “better” than ISDS. Although I did point to the current discrepancy in public perception of the respective regimes, I purposefully avoided expressing any personal, normative position on one being “better” than the other (but apparently not explicitly enough).

scholarly journals The Performance of the Serbian Hotel Industry / Performanse Hotelskog Poslovanja U Srbiji

2013 ◽  
Vol 10 (2) ◽  
pp. 24-31
Author(s):  
Saša I. Mašić
Keyword(s):  
Economic Crisis ◽  
Business Performance ◽  
Operating Performance ◽  
National Level ◽  
Hotel Industry ◽  
National Average ◽  
Significant Decline ◽  
Foreign Tourist ◽  
The City ◽  
Better Than

AbstractThe aim of this paper is to determine operating performance of hotel companies in Serbia. The analysis was conducted on a sample that included approximately 31.35% of the total available hotel capacity in Serbia for the period from 2004 to 2011. The sample was designed to be representative of the hotel distribution by territory and category. Business performance of hotel companies was analyzed using TREVPAR and GOPPAR indicators both at the national level, for tourism clusters and the largest Serbian cities. The results show that hotel companies in Serbia, on average, achieved low TREVPAR and GOPPAR values. In 2011, the average TREVPAR of companies in Serbia was 28 EUR, and GOPPAR approximately 3.7 EUR. The study registered a significant decline in the value of these indicators for the period from 2008 to 2011, primarily as a result of the economic crisis. Results significantly better than the national average were achieved by hotel companies from Belgrade that had a mean TREVPAR value of 46.2 EUR and GOPPAR value of 8.6 EUR. During the analyzed period, the largest increase in the value of the analyzed indicators was registered in the city of Kragujevac as a result of significant investments made by the car manufacturer “Fiat” and its sub-contractors. These investments have led to a significant increase in the number of foreign tourist arrivals and consequently to an increase in business performance of hotel companies in Kragujevac.

scholarly journals Mapping Of Village Tourism Potential In The Framework Of Implementing Community-Based Tourism

2020 ◽  
Author(s):  
Meilan Sugiarto ◽  
Herri Sofyan ◽  
Herlina Jayadianti ◽  
Rudi Wibowo
Keyword(s):  
Local Governments ◽  
Positive Impact ◽  
Local Communities ◽  
Local Economy ◽  
Community Based ◽  
Community Ownership ◽  
Tourism Management ◽  
The Poor ◽  
Tourism Sector ◽  
Tourism Potential

There Improvements in the local economy, especially for the poor through open and sustainable tourism management, are believed to be achieved through the empowerment of the tourism sector. Mapping the potential of village tourism in the Triharjo village area is one of the essential things. Identification and mapping of village tourism potential needed in order to implementation community-based tourism (CBT). This research aims to identifying and mapping the potential of village tourism in order to produce a profile of village tourism potential and identify opportunities for developing village tourism potential. The object of this study is Triharjo village, Pandak District, Bantul Regency, Yogyakarta. This research was conducted with a qualitative approach. Collecting data in this study used several research instruments, such as in-depth interviews, focus group discussions (FGD), observations, and document studies. Based on research finding while the communities and local governments of Triharjo village recognize that not all village tourism potentials are well managed. The results of the mapping of village tourism potential provide them that the involvement of local communities in the planning and management of a village tourism potential is needed and have a positive impact on the longterm. The empowerment of the local economy, especially the poor, is believed to be achieved through the empowerment of the tourism sector. Community-based tourism emphasizes community ownership and active participation, provides education to local communities, promotes and protection of culture and the environment.

Sign in / Sign up

Export Citation Format

Share Document