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All Journal Pelita Eksakta UNP Journal of Statistics and Data Science
Mira Meilisa
Universitas Negeri Padang
Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Physics Social Sciences Other

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Strengthening Data Literacy and Packaging Efficiency in Food MSMEs through Statistical Approaches in Koto Tangah District, Padang Mira Meilisa; Hariyadi Hariyadi; Fitri Kurnia; Dytchia Septi Kesuma; Ade Usra Berli; Rahmat Jordan; Praja Purnama Nusa; Muhammad Farhan Al Azfar
Pelita Eksakta Vol 9 No 1 (2026): Pelita Eksakta, Vol. 9, No. 1
Publisher : Fakultas MIPA Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/pelitaeksakta/vol9-iss1/333

Abstract

Micro, Small, and Medium Enterprises (MSMEs) play a crucial role in the Indonesian economy, particularly in the food sector. However, many food MSMEs face challenges in managing supply risks, business data recording, and product packaging. This service program aims to strengthen data literacy, improve packaging efficiency, and assist in meeting business legalities for five food SMEs in Parupuk Tabing, Koto Tangah, Padang. Through the Participatory Action Research (PAR) approach, this program focuses on three main interventions: (1) data recording and stock management training, (2) introduction to vacuum packaging technology, and (3) fulfilling business legality requirements by obtaining NIB, PIRT, and halal certification.The results show significant changes, including increased business legality (all MSMEs now have NIB and PIRT), the use of vacuum packaging, and the implementation of regular recordkeeping. This program demonstrates that, in the context of MSMEs with limited data, the statistical approach begins with record-keeping habits and simple information systems as a foundation for further analysis.
Analysis Analysis of The Influence of Job Resources and Leadership Quality on Job Satisfaction Using Structural Equation Modeling Azizah Apriyerni; Nisa Ulhusna; Rahmadani; Mira Meilisa
UNP Journal of Statistics and Data Science Vol. 4 No. 1 (2026): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol4-iss1/469

Abstract

Job Satisfaction is a essential factor influencing employee performance, commitment, and organizational sustainability. Low levels of Job Resources and suboptimal Leadership Quality are common causes of decreased job satisfaction across various institutions. This study aims to analyze the effect of job resources and leadership quality on Jjob Satisfaction using the Structural Equation Modeling (SEM) method. The research data were obtained from a Likert-scale survey (1-8) consisting of three latent variabless and their respective indicators, and wer analyzed through Confirmatory Factor Analysis (CFA) and Structural Model assesment. The result of the CFA indicate that all indicators meet the criteria for validity and reliability, with factor loadings above 0.50, a Composite Reliability (CR) value of 0.9667, and an Average Variance Extracted (AVE) value of 0.6769. the Goodness of Fit evaluation shows that the final model is highly acceptable, as reflected by a low Chi-square/df value, RMSEA = 0.005, and CFI, TLI, GFI, and NFI value of 1.000. the Structural analysis further demonstrates that Job Resources have a positive and significant impact on Job Satisfaction. Simultaneously, both variables contribute significantly to explaining variations in Job Satisfaction. This study highlights that enhancing Job Resources and improving Leadership Quality are crucial strategies to strengthen employee Job Satisfaction. The findings provide empirical insight that can assist organizations in developing more effective and sustainable human resource management policies
Co-Authors Ade Usra Berli Azizah Apriyerni Dytchia Septi Kesuma Fitri Kurnia Hariyadi Hariyadi Muhammad Farhan Al Azfar Nisa Ulhusna Praja Purnama Nusa Rahmadani Rahmat Jordan