Purpose: This study aims to investigate whether AIS data can be used as a supporting indicator or as an initial signal to describe Indonesia's export-import conditions in real-time. Research design, data, and methodology: This study performs several stages of data selection to obtain indicators from AIS that truly reflect export-import activities in Indonesia. Also, investigate the potential of AIS indicators in producing forecasts of the value and volume of Indonesian export-import using conventional statistical methods and machine learning techniques. Results: The six preprocessing stages defined in this study filtered AIS data from 661.8 million messages to 73.5 million messages. Seven predictors were formed from the selected AIS data. The AIS indicator can be used to provide an initial signal about Indonesia's import-export activities. Each export or import activity has its own predictor. Conventional statistical methods and machine learning techniques have the same ability both in forecasting Indonesia's exports and imports. Conclusions: Big data AIS can be used as a supporting indicator as a signal of the condition of export-import values in Indonesia. The right method of building indicators can make the data valuable for the performance of the forecasting model.

Purpose: The research aims to analyze the export performance of processed seaweed, its competitiveness, and determinants on seven main destination countries. Research design, data and methodology: The study uses data of seven main destination countries of Indonesian processed seaweed from 2010 to 2019. For competitiveness analysis, the study uses Revealed Comparative Advantage, Export Product Dynamics, and X-Model of Potential Export Product. Results: The study reveals that the export performance has decreased on all five countries except for Japan and USA. The X-Model analysis shows that the market classification has increased or been stable in every country except for Germany and France. GDP per capita of each destination country and competitiveness index have positive and significance effect while other factors have negative and significance effect. Conclusions: In 2019, Indonesia's processed seaweed market in Japan, United States, and France are on potential market, while Singapore and Italy are on optimistic market. In the future, Indonesia's processed seaweed export can be focused more on countries that have a good market potential. To improve the export volume, GDP per capita of destination country, and competitiveness index of Indonesian processed seaweed should be higher, while export price, economic distance, and real exchange rate should be lower.

Purpose: This study aims to determine the effect of broadband access, education level, population numbers, and investment on the unemployment rate in Indonesia. Research design, data, and methodology: This study uses panel data from 34 provinces from 2016 to 2019. The analysis uses the fixed-effect model for panel data with the Feasible Generalized Least Square (FGLS) estimation method. Results: Broadband access has a negative and significant effect on the unemployment rate. Mean years of school, population, and foreign direct investment also have a negative and significant impact on the unemployment rate. In contrast, the domestic direct investment variable has a positive and significant effect. Conclusion: The availability of broadband access in an area allows easier and faster access to information. The ease of access to such information can affect producing goods and services, encouraging innovation and employment growth, and reducing the unemployment rate. This research recommends that the government intensify the Indonesia Broadband Plan policy to accelerate the development and equitable distribution of broadband access in all regions of Indonesia.

Purpose: This research aims to analyze the quality and characteristics of foreign tourists to Indonesia. Research design, data and methodology: The indicator used to see the quality of foreign tourists is their expenditure while in Indonesia. The data used is secondary data and the statistical analysis used is panel data regression to see the effect of Economic Distance, GDP per capita, Average Length of Stay and Exchange Rate on the quality of Foreign Tourists from 2010 to 2019. Results: Foreign tourists to Indonesia are dominated by young tourists, male and stay about 8.87 days. Their expenditure is relatively low, mostly spent on accommodation, food and beverage. The variables of average length of stay, exchange rate, economic distance, and GDP per capita have a significant and positive effect on the quality of foreign tourists to Indonesia. Conclusions: The number of foreign tourists visiting Indonesia in 2010-2019 tends to increase where the majority of tourists come from countries that are geographically close to Indonesia, young tourists, and male. The quality of tourists in terms of spending is still relatively low. The characteristics of foreign tourists and economic indicators used in the study have a positive effect on improving the quality of tourists.