Evaluation of an Operational Management Information System for Culinary MSMEs on an Android Point-of-Sale Platform with a Daily Summary Workflow and Order Grouping-Based Order Integration

Abstract

Manual recording of transactions and daily recaps at Kedai Lumpia Super MSME has the potential to cause inconsistencies in operational data. This study aims to evaluate an operational management information system for culinary MSMEs through an Android-based Point of Sale with a daily recap flow and order grouping-based ordering integration. This study uses a case study approach and software engineering method, while the system development follows the Iterative Waterfall model. Requirement data were collected through observation, interviews, manual transaction document analysis, and literature review. The evaluation was conducted using scenario-based User Acceptance Testing to assess feature suitability with operational needs, the System Usability Scale to measure application usability, and operational efficiency comparison to examine workflow changes. The UAT results from seven respondents showed that 10 scenarios were accepted or 66.67%, 5 scenarios were accepted with revisions or 33.33%, and no scenario was rejected. The SUS results from 30 respondents produced a total score of 2547.5 with an average score of 84.92, categorized as Very Good and Grade A. The efficiency comparison showed that transaction recording time decreased from approximately 2 minutes to approximately 1 minute, while daily recap preparation decreased from 30-60 minutes to 5-15 minutes. This study contributes to the evaluation of daily operational workflows in POS systems for culinary MSMEs, which not only record transactions but also group orders and support daily recaps in a structured manner.