Training Planning Strategy in the Context of Leather Puppet Craft Training

Abstract

Leather puppet (wayang kulit) craft training is a form of strategic intervention to preserve cultural heritage and strengthen the creative economy sector in Indonesia. To ensure effective and efficient training, a planning approach is needed that goes beyond the conventional and incorporates quantitative analysis and intelligent systems. This service project proposes a training planning strategy using an interdisciplinary approach involving Operations Research, Design of Experiments (DoE), Simulation, Metaheuristic Algorithms, and Data Mining.

The study began with the identification of key training variables such as duration, number of participants, initial competency level, teaching materials, and instructor resources. Using the DoE approach, various variable combinations were systematically tested to identify the optimal training design. Simulation was then employed to model the dynamics of training implementation and evaluate implementation scenarios. To predict training needs and participant behavior, Data Mining techniques were applied to historical community art training data. In the final stage, Metaheuristic algorithms such as Genetic Algorithm and Simulated Annealing were used to solve complex, large-scale scheduling and resource allocation problems.

The integration of these approaches resulted in a 27% improvement in training efficiency, along with increased participant satisfaction and quality of output. This initiative demonstrates that the application of quantitative and data-driven methods in traditional craft training planning can offer significant added value. The model can be replicated in other training programs based on local wisdom or within other creative industry sectors.