Forecasting typhoid fever incidence in the Cordillera administrative region in the Philippines using seasonal ARIMA models

2017 ◽  
Author(s):  
Olive R. Cawiding ◽  
Gina May R. Natividad ◽  
Crisostomo V. Bato ◽  
Rizavel C. Addawe
Keyword(s):  
Typhoid Fever ◽  
The Philippines ◽  
Arima Models ◽  
Administrative Region ◽  
Seasonal Arima Models

scholarly journals Development of Seasonal ARIMA Models for Traffic Noise Forecasting

2017 ◽  
Vol 125 ◽  
pp. 05013 ◽  
Author(s):  
Claudio Guarnaccia ◽  
Nikos E. Mastorakis ◽  
Joseph Quartieri ◽  
Carmine Tepedino ◽  
Stavros D. Kaminaris
Keyword(s):  
Traffic Noise ◽  
Arima Models ◽  
Seasonal Arima Models

scholarly journals A CASE STUDY OF ISLAMIC DACWAH ACTIVITIES IN CORDILLERA ADMINISTRATIVE REGION, PHILIPPINES AMONG MUSLIM MINORITY

2019 ◽  
Vol 7 (4) ◽  
pp. 559-571
Author(s):  
Marlon Pontino Guleng ◽  
Razaleigh Muhamat Kawangit ◽  
Abur Hamdi Usman
Keyword(s):  
Social Sciences ◽  
The Philippines ◽  
Quantitative Methodology ◽  
Muslim Society ◽  
Administrative Region ◽  
The Social ◽  
Muslim Minority ◽  
The Government ◽  
High Level

Purpose of the Study: The curves of Islamic dacwah activities in the Philippines have faced ebbs and flows due to various internal and external constraints. In Cordillera Administrative Region (CAR), lots of responses had been received by the Islamic organization from the local Muslim societies on the dacwah activities which require further reform in a way of diversifying the dacwah efforts in the whole region. This research aims of identifying the response of Muslim society towards the Islamic dacwah activities in the Philippines. Methodology: In this study, quantitative methodology research was applied and the data were analyzed using Statistical Package for the Social Sciences (SPSS) for Windows version 21 with a total number of 272 respondents. Main Findings: The results showed the responses towards the Islamic dacwah activities in a Muslim society (mean=3.71); Muslim family and friends (mean=3.51) were at high level. However, findings regarding the responses from the government (mean=3.13) and non-Muslim society (mean=3.15) were at moderate level. Implications: The findings are essential for Islamic da’wah organizations to redesign and formulate various dacwah programs in order to ensure better implication on the societies.

scholarly journals Forecasting tourist arrivals in South Africa

2010 ◽  
Vol 10 (1) ◽  
Author(s):  
Andrea Saayman ◽  
Melville Saayman
Keyword(s):  
South Africa ◽  
Emerging Market ◽  
Arima Model ◽  
The United States ◽  
Interesting Case ◽  
Percentage Error ◽  
Business Success ◽  
Arima Models ◽  
Time Series Modelling ◽  
Seasonal Arima Models

Purpose: The aim of this paper is to model and forecast tourism to South Africa from the country's main intercontinental tourism markets. These include Great Britain, Germany, the Netherlands, the United States of America and France. Problem investigated: Tourism to South Africa has grown substantially since the first democratic elections in 1994. It is currently the third largest industry in the country and a vital source of foreign exchange earnings. Tourist arrivals continue to grow annually, and have shown some resilience to a number of emerging market crises, including the terrorist attacks in the USA. Business success, marketing decisions, government's investment policy as well as macroeconomic policy are influenced by the accuracy of tourism forecasts, since the tourism product comprises a number of services that cannot be accumulated. Accurate forecasts of tourism demand are paramount to ensure the availability of such services when demanded. In addition, the seasonal nature of tourism leads to a pattern of excess capacity followed by shortage in capacity. Method: Since univariate time series modelling has proved to be a very successful method for forecasting tourist arrivals, it is also the method employed in this paper. The naïve model is tested against a standard ARIMA model, as well as the Holt-Winters exponential smoothing and seasonal-non-seasonal ARIMA models. Forecasting accuracy is assessed using the mean absolute percentage error, root mean square error and Theill's U of the various models. Monthly tourist arrivals from 1994 to 2006 are used in the analysis, and arrivals are forecasted for 2007. Findings: The results show that seasonal ARIMA models deliver the most accurate predictions of arrivals over three time horizons, namely three months, six months and 12 months. Value: This paper is the first tourist arrivals forecast using South African data for the country as a whole, and therefore it forms an interesting case study as a long haul and growing tourist destination. Conclusion: The univariate forecasts provide fairly accurate forecasts of tourist arrivals in South Africa, especially over the short run. As such, it is understandable why it remains a popular approach to forecast tourist arrivals. However, this method does not make provision for assessing the influence of external events and therefore its policy application is limited.

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