2016International Journal of Scientific and Research PublicationsRequires access

Determinants of Socio-Demography and Household Livelihood (A Study in Iluta and Limehe Timur Village, Gorontalo Regency)

Sri Endang Saleh, Muhammad Baiquni, Hadi Sabari Yunus

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Abstract

This research aims at analyzing livelihood assets and strategies in relation to socio-demography of households around Limboto Lake. Assets as livelihoods resource for inhabitants living around Limboto lake consist of human capital, natural capital, social capital, physical capital, and financial capital. The research took place in Iluta Village And Limehe Timur Village around Limboto Lake, Gorontalo Regency. It employed survey on 97 households of farmers and fishermen. Data were analyzed in descriptive and quantitative manner to determine the livelihood assets selected by households and were illustrated into an asset pentagon. The research results showed that the correlation between socio-demographic variable and livelihood assets was weak, which R-square value was 0.2532. The correlation of the influence socio-demographic variables (X1) and Livelihood Assets (X2) on Livelihoods Strategy (Y) was good. This correlation was indicated by the R-square value of 0.7055, meaning that variations on Livelihood Strategies (Y) were able to be explained by socio-demographic variables (X1), and Livelihood Assets (X2) by 70.55 percent, while the remaining 29.45 percent was influenced by other variables that were not included in the model.

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What this paper is about

This research aims at analyzing livelihood assets and strategies in relation to socio-demography of households around Limboto Lake. Assets as livelihoods resource for inhabitants living around Limboto lake consist of human capital, natural capital, social capital, physical capital, and financial capital. The research took place in Iluta Village And Limehe Timur Village around Limboto Lake, Gorontalo Regency. It employed survey on 97 households of farmers and fishermen. Data were analyzed in descriptive and quantitative manner to determine the livelihood assets selected by households and were illustrated into an asset pentagon. The research results showed that the correlation between socio-demographic variable and livelihood assets was weak, which R-square value was 0.2532. The correlation of the influence socio-demographic variables (X1) and Livelihood Assets (X2) on Livelihoods Strategy (Y) was good. This correlation was indicated by the R-square value of 0.7055, meaning that variations on Livelihood Strategies (Y) were able to be explained by socio-demographic variables (X1), and Livelihood Assets (X2) by 70.55 percent, while the remaining 29.45 percent was influenced by other variables that were not included in the model.

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Available abstract

This research aims at analyzing livelihood assets and strategies in relation to socio-demography of households around Limboto Lake. Assets as livelihoods resource for inhabitants living around Limboto lake consist of human capital, natural capital, social capital, physical capital, and financial capital. The research took place in Iluta Village And Limehe Timur Village around Limboto Lake, Gorontalo Regency. It employed survey on 97 households of farmers and fishermen. Data were analyzed in descriptive and quantitative manner to determine the livelihood assets selected by households and were illustrated into an asset pentagon. The research results showed that the correlation between socio-demographic variable and livelihood assets was weak, which R-square value was 0.2532. The correlation of the influence socio-demographic variables (X1) and Livelihood Assets (X2) on Livelihoods Strategy (Y) was good. This correlation was indicated by the R-square value of 0.7055, meaning that variations on Livelihood Strategies (Y) were able to be explained by socio-demographic variables (X1), and Livelihood Assets (X2) by 70.55 percent, while the remaining 29.45 percent was influenced by other variables that were not included in the model.

Key concepts: Livelihood, Capital asset, Socioeconomics, Descriptive statistics, Asset (computer security), Social capital, Geography, Capital (architecture)

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