GARMENT EMPLOYEE PRODUCTIVITY PREDICTION USING RANDOM FOREST

Clothing also means clothing is needed by humans. Besides the need for clothing in terms of function, clothing sales or business is also very potent. About 75 million people worldwide are directly involved in textiles, clothing, and footwear. In this case, a common problem in this industry is that the actual productivity of apparel employees sometimes fails to reach the productivity targets set by the authorities to meet production targets on time, resulting in huge losses. Experiments were conducted using the random forest model, linear regression, and neural network by looking for the values ​​of the correlation coefficient, MAE, and RMSE. This aims to predict the productivity of garment employees with data mining techniques that apply machine learning and look for the minimum MAE value. The results of testing the proposed algorithm on the garment worker productivity dataset obtained the smallest MAE, namely the random forest algorithm, namely 0.0787, linear regression 0.1081, and 0.1218 neural networks

Garment worker rights and the fashion industry’s response to COVID-19

In this commentary, we examine the fashion industry’s early responses to COVID-19. Looking across fashion’s global production networks, we argue the fashion industry’s response has been rapid, yet highly inequitable, reflecting—and further entrenching—existing inequalities in the industry.

Social Distancing Challenges for Marginal Communities during COVID-19 Pandemic in Bangladesh

This study presents the challenges of marginal communities in maintaining social distances during the COVID-19 pandemic. We focused on garment worker communities in Bangladesh. The current living conditions put the community at high risk due to the contagious nature of COVID-19. The study involved 55 garment workers (32 female) living in three different regions--Ashulia, Gazipur, and Mirpur of Bangladesh. Through a qualitative research method, three critical aspects were studied. First, the inability to maintain social distancing in the community living in close proximity. Second, there is a lack of concern about healthcare among the community and, finally, the absence of preparation for crisis management. The research work proposes policy level intervention for better healthcare in the light of the pandemic that can be helpful in the coming days.