Cognitive-Oriented Serious Game Design for Manufacturing Production-Flow Problem Solving Using Mini Drone Assembly - Sari, Handini Fatma; Ratnasari, Chanifah Indah; Mulyati, Rina (MALCOM: Indonesian Journal of Machine Learning and Computer Science, 2026)
Manufacturing production-flow problem-solving requires Industrial Engineering students to understand how queues, work-in-process (WIP), bottlenecks, quality control, rework, and system stability interact to determine production performance. Yet conventional materials rarely allow students to observe how a single decision affects the whole system. This study aims to produce a refined, cognitive-oriented serious game design that explicitly links cognitive problem-solving, simplified production-flow rules, and game-system interaction across four progressive levels, and to evaluate it formatively as a basis for further development. Using Design-Based Research, the design was represented through Figma-based static mockups covering level progression, rule-based production behavior, feedback, and performance reports, operationalizing an Observe–Diagnose–Predict–Adjust–Stabilize–Reflect loop. Two game-design experts and five Industrial Engineering students evaluated the design through researcher-guided walkthroughs. Expert judgment produced an overall mean of 2.86 out of 5, indicating refinement needs in dynamic-system behavior and feedback. In contrast, prospective users gave 3.74 out of 5, with the strongest perception in cognitive support. Consistent with its formative objective, these results were not treated as evidence of learning effectiveness but were directly used to refine production-flow rules, feedback, and level structure, producing a four-level design artifact that provides a basis for future prototype development and effectiveness testing.