Prior researchers indicate that mental load is one of the most important contributors to a traffic accident. The aim of the paper is to investigate the impact and the correlation of road condition and driving experience on driver’s mental workload. The driving test consists of 3 road complicity situation (urban road, highway, rural road) with 26 drivers with average 21 years old in different experience level (average 4.08 years’ experience). NASA TLX questioner is used as subjective driver’s mental load measurement with three dimensions relate to the demands imposed on the subject (Mental, Physical and Temporal Demands) and three to the interaction of a subject with the task (Effort, Frustration, and Performance). There are 3 cameras placed on the left side, right side and front car to identify the road condition. According to experiment, it was found that drivers felt that frustration level, business, and mental-demand factors dominate the impact on high-level workload (96.15%). Highway road conditions provide an average overall workload score of 62 (OWS) which was better compared to city road (OWS = 69) and rural road (OWS = 66). Based on street complexity, it is necessary to improve road conditions that resemble highway road by reducing potential hazard.

Redesain Produk Berfokus Pada Customer Requirements Dengan Integrasi Axiomatic Design dan House of Quality

Industry 4.0 is a term for the digital revolution in industrial area appearing from a comprehensive and computerized network. Digital platforms can be an impressive and beneficial media for industry to get closer with the customers. While many big companies have attempted to figure on the potential and risks of digitalization along have introduced an innovation process for their business models, small and medium enterprises (SMEs) have not utilized this optimally. Currently SMEs are known as the bedrock of most economies, especially in developing countries. The aim of this study was to optimize the digital platform that had been developed as SME business media through risk analysis for the sustainability constructing. The SWOT analysis and failure mode and effect analysis (FMEA) approach were used to assess the identified and analysed risks before determining the appropriate mitigation plan. The study expected SMEs to fulfil the challenges and opportunities from Industry 4.0 for elevating national economic stability.

The dairy cattle productivity is very depending on the quality of their environment and physiological aspect. Hence, the purpose of the paper is to looking for the relationship model of physiological, environmental and milk productivity by using artificial intelligence (AI). The model will be useful for the user to decide the best cow treatment in order to gain the best milk production. The research is started with literature review and early survey of cattle physiological, environment factors and milk productivity. The next step is measuring the environment data (temperature, wind speed, and relative humidity) and measuring physiological aspect (heart rate, body temperature) correlated with milk productivity in 500 pairs of data. All the data are collected and stored into the database and then trained and validated using Back Propagation Neural Network (BPNN) with Genetic Algorithm (GA) optimization. The initial BPNN architectures are selected in 2 hidden layer, delta bar delta learning rule, sigmoid transfer function and epoch 10000. As a result, the system successfully developed an intelligent tool to predict milk production in any levels of environment and physical condition. Based on sensitivity analysis, the relative humidity, heart rate, environment and cow body temperature are categorized in strong impact, beside that are in weak impact on milk production.

The aim of the study was to investigate the financial behavior of employees regarding financial literacy and spending habits based on gender. The cluster sampling was used in this study and 60 employees consist of 30 male and 30 females were chosen and the analytical method used is different test of independent sample t-test for normally distributed data, while Mann-Whitney test for distributed data is not normal. The result showed that financial literacy behavior and spending habits between male and female employees were not different. Male and female employees had low level of financial literacy and they had tight spending habits the study also found that male and female employees did not have appropriate knowledge to manage their financial especially in managing investment and loan. This result in increasingly tight spending which caused they still have to deal with the monthly instalment payment in the long run.