[5-1015-D] Other Categories (2)

[5-1015-D-04] Development of Agro-industrial Worker Trust Assessment System for Sustainable Ergonomic Program in Food Small and Medium-sized Enterprises

*Mirwan Ushada¹, Nur Achmad Sulistyo Putro², Titis Wijayanto³, Fitri Trapsilawati³, Nafis Khuriyati¹ (1. Universitas Gadjah Mada, Department of Agro-industrial Technology(Indonesia), 2. Universitas Gadjah Mada, Department of Computer Science and Electronics(Indonesia), 3. Universitas Gadjah Mada, Department of Mechanical and Industrial Engineering(Indonesia))

Keywords:Bird swarm algorithm, Collective trust, Environmental ergonomics, Individual trust, Kansei Engineering

Ergonomic program has not yet fully gained the worker trust in food Small Medium-sized Enterprises (SMEs) due to the gap between ergonomics and financial amenities. The tangible financial amenities as wages, incentives, and insurance have been more attractive than the intangible ergonomics program in the form of a comfortable workplace environment (Environmental ergonomics), efficient work methods and optimum workload. Trust could be defined as an abstractive (Kansei) human factor which is characterized by uncertainty and vulnerability to support their individual and collective decision. Trust influence the attractiveness of ergonomic program to worker as individual and worker union as the collective. The abstractive communication between 1 (one) individual worker and other partners in same union is possible to be simulated in an artificial bird swarm algorithm. Kansei engineering was selected to model the individual trust due to the reliability for modeling the abstractive human factors. Artificial swarm intelligence was selected to simulate the collective trust due to capability to model non-linear of human factors. The research goal was to develop an agro-industrial worker trust assessment system for sustainable ergonomic program in food SMEs. The research objective was: 1) To predict the worker individual trust using Kansei Engineering; 2) To simulate the worker collective trust using bird swarm algorithm. The system is expected to assist the SME’s management for developing trust evidence-based ergonomic policy. Generally, the system is expected to support the Sustainable Development Goals numbers 3 (Good health & well-being) and number 9 (Industry, innovation and infrastructure). The system was tested on the database of worker human factors in Food SMEs. The inputs of the system was extracted from database as: 1) Workload; 2) Workplace temperature; 3) Relative humidity; 4) Light intensity; 5) Incentive. The output was individual and collective trust. The agro-industrial worker trust assessment system consists of 7 sub-systems. In the Sub-system 1, measurement is carried out to obtain the worker mood states, heart rate and workplace environment parameters. In Sub-system 2, the manager obtain measurement result in Sub-system 1 as the input to determine integrated workload and workplace temperature set point. If the workload indicated the normal status, then the workplace temperature is set. If the workload status indicated under or over load, then the system provides feedback for the manager to evaluate the existing ergonomic program. In Sub-system 3, the temperature was set in an air conditioner to create the comfortable workplace environment (Environmental ergonomics). In Sub-system 4, the work incentive is determined based on integrated workload (Sub-system 2) and environmental ergonomics (Sub-system 3). The individual trust index is determined in Sub-system 5. If the index indicated the status of trust, the system proceeds the status to the Sub-system 6. If the index indicated distrust, the system provides feedback to the manager to evaluate the existing ergonomic program. The Sub-system 6 processes the individual trust in Sub-system 5 using the Bird Swarm Algorithm in Kansei Engineering (BISAKE). The algorithm simulated the worker union to behave like a bird swarm in determining whether an individual trust is satisfied or not against their mentality constraints of prior knowledge, familiarity, agreement and preference. Finally, in the Sub-system 7, the collective trust was validated. The simulation result indicated that worker trust index could be assessed based on workload status, a percentage of incentive and workplace environmental cost per month. Furthermore, this assessment could make the trust data more manageable to store, retrieve and enable interchange in big data system for sustainable ergonomic program in food SMEs.