Analysis of Food Security Factors in Indonesia using SEM-GSCA with the Alternating Least Squares Method

Abstract

An economic recession, characterized by prolonged economic decline, increased unemployment, and decreased spending, is projected to occur globally in 2023, potentially impacting production capacity within the food sector. Experts have identified various contributing factors such as shifts in global trade dynamics and geopolitical tensions, highlighting the need to understand the broader global economic context leading to this recession. To achieve this goal, in this research SEM is used to analyze the relationship between variables that influence food security. Furthermore, GSCA is used to handle complex structural models and non-normal data distribution. Special considerations include the use of ALS methods to estimate parameters effectively and consistently. The findings of this research are the important role of availability, access and utilization in shaping food security in Indonesia, with a contribution of 98% of the overall influence shown by the model. These insights help governments design targeted interventions to improve food security, especially amidst challenges posed by a potential global economic downturn. Implementing strategies to increase availability, increase access and optimize utilization is very important in maintaining food security amidst economic uncertainty.

Keywords

• structural equation modeling
• generalized structured component analysis
• alternating least squares.