The idea of supply chain management (SCM) is covering its perspective in the form of flow of material and information from the business to customers. Its application in the field of tourism is also very much significant. The objective of present study is to analyze the empirical association between the supply chain management and tourism industry from the context of hotel industry in Indonesia. For this purpose, a questionnaire-based approach is followed while taking the demographic factors regarding age, gender and qualification. A sample of 272 respondents is finally accepted for the empirical examination between supply chain and its implication in tourism industry. Both descriptive and regression analysis are conducted. To analyze the factor of supply chain, sixteen items are considered from the existing literature while considering the strategic supplier partnership, information sharing, and information quality as the key indicators. The factor of tourism is measured through four different proxies. The practical implications of the study are taken both the tourists and key policymakers while dealing with the SCM and its integration with those hotels dealing with the tourism and related services. This study contributes towards the future trends in the form of integration for SCM and tourism industry.

Singular Spectrum Analysis (SSA) is a time series method used to decompose the original time series into a sum of a small number of components that can be interpreted such as trends, oscillatory components, and noise. The purpose of this study is to compare the accuracy of the forecast between the SSA and ARIMA methods to obtain the best method in predicting the number of foreign tourist arrivals to Indonesia. The data used in this study is data on the number of arrival of foreign tourists to Indonesia through the Batam entrance. The forecasting results obtained using the SSA method will be compared with the ARIMA method to assess its superiority. The level of forecasting accuracy generated by each method is measured by the criteria of Mean Absolute Percentage Error (MAPE). The results of the study show that the ARIMA method produces better forecast accuracy than the SSA method for forecasting the number of tourist arrivals through the Batam's entrance. The MAPE value obtained from the results of forecasting using the ARIMA method is 9.83. The MAPE value obtained from the results of forecasting using the SSA method is 10.98.