Transformasi Manajemen Layanan Pendidikan Nonformal melalui Pendekatan Data-Driven OEE: Perspektif Manajemen Strategis

Masduki Asbari

doi:10.4444/jisma.v4i4.1256

Authors

Masduki Asbari Universitas Insan Pembangunan Indonesia, Indonesia https://orcid.org/0000-0003-2460-9171

DOI:

https://doi.org/10.4444/jisma.v4i4.1256

Keywords:

OEE, Overall Equipment Effectiveness, operational effectiveness, non-formal education, service management

Abstract

This study analyzes the operational effectiveness of private tutoring services by adapting the Overall Equipment Effectiveness (OEE) concept from the manufacturing sector to non-formal education. A descriptive qualitative research design with a case study was conducted on 20 students during one operational period; data were collected through observations of learning activities, schedule documentation, and learning evaluation records. The results showed Availability of 90%, Performance of 89%, and Quality of 90%, resulting in a total OEE value of 72%. This figure indicates that service effectiveness is relatively good but still far from the world-class measure often emphasized in the OEE literature for educational services, which generally ranges around 85% or more, thus providing room for concrete improvement. The novelty of the study lies in adapting the OEE concept to non-formal educational services, specifically private tutoring, making it a data-driven operational measurement tool that can be operated by PNFI managers for continuous improvement. Practically, these findings encourage increased data-driven schedule planning, pedagogical competency enhancement, learning differentiation, and the implementation of a performance dashboard to encourage evidence-based corrective actions. The main research questions answered are how OEE adapted from TPM can operationally measure the effectiveness of private tutoring services in non-formal education; what sources of time loss (waste) affect Availability and Performance; how instructional differentiation and teacher capacity building are related to quality improvement; and how the use of performance dashboards and learning analytics strengthens data-driven decision-making for service quality improvement.

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