Analysis of Determinants of Women's Empowerment in the Tourism Sector in Penglipuran Village Using a Bayesian Network

This study aims to identify and analyze the factors that influence women's empowerment in the tourism sector in Penglipuran Village, Bali. Penglipuran Village, known for its cleanliness, local wisdom, and awig-awig rules that govern the social life of its community, has great potential in empowering women so that they can be involved in tourism. Although tourism is growing rapidly, women's involvement in this sector has not been optimal, for example, the lack of product innovation and business sustainability is still an obstacle in improving their competitiveness. This is because women's empowerment is still not effectively implemented. Data collection was conducted through interviews, questionnaires, and FGDs. There were 20 institutional and stakeholder respondents in the FGD. This research uses the Bayesian Networks method to analyze the causal relationship between influential economic variables, such as social capital, education, awig-awig, gender equality, access to resources, skills, infrastructure and local policy support. The results of this study show that there are several potential influences on women's empowerment, such as gender equality, awig-awig, education, social capital, and government regulations. Determining five main nodes as target nodes with a 100% probability of success in improving women's empowerment is 9%. By utilizing the Bayesian Belief Network, this study shows that gender equality, awig-awig, education, social capital, and government regulations are important factors, along with other variables, such as infrastructure and skills, that influence women's empowerment in Penglipuran Village.

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Publication Details

Journal
E-Journal of Tourism
Published
2024-09-30
DOI
https://doi.org/10.24922/eot.v11i2.118941
Primary Topic
Livestock Farming and Management
Type
article
Field-Weighted Citation Impact
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article

Analysis of Determinants of Women's Empowerment in the Tourism Sector in Penglipuran Village Using a Bayesian Network

Ida Ayu Nyoman Saskara, Luh Putu Pita Maha Dianita
E-Journal of Tourism
Livestock Farming and Management
article

Analysis of Determinants of Women's Empowerment in the Tourism Sector in Penglipuran Village Using a Bayesian Network

Ida Ayu Nyoman Saskara, Luh Putu Pita Maha Dianita
article en

Abstract

This study aims to identify and analyze the factors that influence women's empowerment in the tourism sector in Penglipuran Village, Bali. Penglipuran Village, known for its cleanliness, local wisdom, and awig-awig rules that govern the social life of its community, has great potential in empowering women so that they can be involved in tourism. Although tourism is growing rapidly, women's involvement in this sector has not been optimal, for example, the lack of product innovation and business sustainability is still an obstacle in improving their competitiveness. This is because women's empowerment is still not effectively implemented. Data collection was conducted through interviews, questionnaires, and FGDs. There were 20 institutional and stakeholder respondents in the FGD. This research uses the Bayesian Networks method to analyze the causal relationship between influential economic variables, such as social capital, education, awig-awig, gender equality, access to resources, skills, infrastructure and local policy support. The results of this study show that there are several potential influences on women's empowerment, such as gender equality, awig-awig, education, social capital, and government regulations. Determining five main nodes as target nodes with a 100% probability of success in improving women's empowerment is 9%. By utilizing the Bayesian Belief Network, this study shows that gender equality, awig-awig, education, social capital, and government regulations are important factors, along with other variables, such as infrastructure and skills, that influence women's empowerment in Penglipuran Village.

E-Journal of Tourism
Openalex Percentile: Top 61%
Livestock Farming and Management
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