Evaluation of the Learning Quality of the Agricultural Industrial Technology Study Program Using Customer Satisfaction Index (CSI) And Importance-Performance Analysis (IPA)
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https://doi.org/10.61255/jupiter.v4i3.1441Keywords:
Learning Quality, Customer Satisfaction Index (CSI), Importance-Performance Analysis (IPA), Agricultural Industrial TechnologyAbstract
Purpose: This study analyzes the learning process quality in the Agricultural Industrial Technology Program at Universitas Negeri Makassar by evaluating satisfaction, analyzing gaps, and mapping priority attributes to provide data-driven management recommendations. Methods: This descriptive quantitative survey involved 121 active students, split into pilot and main groups. Content validity was verified using Aiken’s V with 5 experts. Construct validity was tested via Confirmatory Factor Analysis (CFA) in JASP, and reliability via Cronbach's Alpha. Data analysis integrated the Customer Satisfaction Index (CSI) and Importance-Performance Analysis (IPA). Findings: Aiken's V confirmed content validity (V ≥ 0.87). CFA eliminated 5 weak items, leaving 40 valid items with excellent reliability (alpha = 0.958). Indicator CSI scores reflected "Satisfied" and "Very Satisfied" categories (70.08%–84.40%). The grand mean of performance (X = 3.99) fell below importance (Y = 4.46), yielding a -0.47 gap. The IPA matrix identified two critical Quadrant I (Top Priority) attributes: lab staff responsiveness to technical glitches (Item 18) and flexible personal tutoring for struggling students (Item 34). Research Implications: These findings direct study program management to bypass high-cost overhauls, reallocating those resources to optimize laboratory staff responsiveness and more personalized student mentoring. Additionally, the CSI baseline indicates that student satisfaction remains anchored by strong pedagogy, proving that interventions must target specific technical and administrative bottlenecks. Originality: This study hybridizes the SERVQUAL framework with the latest National Higher Education Standards (Permendiktisaintek No. 39/2025), statistically reinforced by CFA to map academic dynamics in a developing engineering program.
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