Freshwater problems in coastal areas include the process of salt intrusion which occurs due to decreasing groundwater levels below sea level which can cause an increase in salt levels in groundwater so that the water cannot be used for water purposes, human consumption and agricultural needs. The main objective of this research is to implementation of RWH to fulfill clean water needs in tropical coastal area in Tanah Merah Village, Indragiri Hilir Regency, with the aim of providing clean water to coastal communities. The approach method used based on fuzzy logic (FL). The model input data includes the effective area of the house’s roof, annual rainfall, roof runoff coefficient, and water consumption based on the number of families. The BWS III Sumatera provided the rainfall data for this research, which was collected from the Keritang rainfall monitoring station during 2015 and 2021. The research findings show that FL based on household scale RWH technology is used to supply clean water in tropical coastal areas that the largest rainwater contribution for the 144 m² house type for the number of residents in a house of four people with a tank capacity of 29 m² is 99.45%.

Introduction: With the adoption of the rural rehabilitation strategy in recent years, China’s rural tourist industry has entered a golden age of growth. Due to the lack of management and decision-support systems, many rural tourist attractions in China experience a “tourist overload” problem during minor holidays or Golden Week, an extended vacation of seven or more consecutive days in mainland China formed by transferring holidays during a specific holiday period. This poses a severe challenge to tourist attractions and relevant management departments. Objective: This study aims to summarize the elements influencing passenger flow by examining the features of rural tourist attractions outside China’s largest cities. Additionally, the study will investigate the variations in the flow of tourists. Method: Grey Model (1,1) is a first-order, single-variable differential equation model used for forecasting trends in data with exponential growth or decline, particularly when dealing with small and incomplete datasets. Four prediction algorithms—the conventional GM(1,1) model, residual time series GM(1,1) model, single-element input BP neural network model, and multi-element input BP network model—were used to anticipate and assess the passenger flow of scenic sites. Result: The multi-input BP neural network model and residual time series GM(1,1) model have significantly higher prediction accuracy than the conventional GM(1,1) model and unit-input BP neural network model. A multi-input BP neural network model and the residual time series GM(1,1) model were used in tandem to develop a short-term passenger flow warning model for rural tourism in China’s outskirts. Conclusion: This model can guide tourists to staggered trips and alleviate the problem of uneven allocation of tourism resources.

Papua, one of the provinces in Indonesia, is recognized for its limited infrastructure and high poverty rates. This limitation undoubtedly emphasizes the government’s special attention toward augmenting foreign and domestic investments by expanding industrial sectors to absorb more labor, thereby aiming to enhance the region’s economic performance. The focus of the study seeks to assess the extent to which foreign and domestic investments, industrial employment, and the proliferation of industries in Papua contribute to increasing the Gross Development Product (GDP) and reducing poverty. By employing secondary data from 2016 to 2022 and utilizing the Regression Data Panel method, it encompasses 29 districts. The findings reveal that domestic investment, employment in the industrial sector, and the number of industries significantly influence poverty rates. However, as conclusion, foreign investment, surprisingly, demonstrates no substantial impact on economic performance. This unexpected result might be attributed to issues linked with the inadequate quality of financial performance, which doesn’t align with the available investment funds. Utilizing the analytical network process (ANP), the study outlines two primary strategies. The first involves prioritizing investment expansion by focusing on both domestic and foreign investments. The second strategy emphasizes industrial revitalization through augmenting the number of industries and enhancing labor participation in the industrial sector.