Abstract

This research aims to measure the productivity level using the objective Matrix (OMAX) approach method based on raw material usage data, available operator hours data, and operator hours data. As well as determining the causes of decreased productivity using a cause-and-effect diagram (Fishbone Diagram). Based on the calculation of the productivity index for the period from January to June 2022, it was 39.89%. While the highest productivity occurs in May with a value of 480 and the lowest productivity is in March with a total yield of 116. Based on the achievement of the lowest productivity ratio score is found in ratio 2, namely, labour productivity with a total score of 15 and the lowest total score is in January, March and May. Changes in performance values indicate that the level of productivity is not yet good, it is necessary to improve the factors that influence it. The causal diagram shows that the machine damage factors also affect the operator’s working hours, which become ineffective. In terms of productivity, we must require pretty good machine maintenance so that production can run smoothly and machine maintenance on a regular basis. The workforce greatly influences the occurrence of low productivity due to inexperienced and unskilled operators and sufficient training for operators must be needed to increase the productivity of the company.
 Keywords: Objective Matrix (OMAX), Productivity, Clean Water.

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