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Journal : Tibuana : Journal of Applied Industrial Engineering

APPLICATION of MANUFACTURING SYSTEMS TO CALCULATE PRODUCTION TARGET NEEDS PRIDE CHAIR DESIGN Imron Rosyadi N R; Matsaini
Tibuana Vol 4 No 01 (2021): Tibuana
Publisher : UNIPA PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/tibuana.4.01.3173.23-27

Abstract

A process in a company or industry will never be separated from the name of the production, production is an important part of the running of a company or industry. This research aims to provide input to the company to be able to calculate the need for future production targets based on previous production data so that the company can prepare all production needs. Production can also be interpreted as an activity to increase the use of goods and benefits in fulfilling daily activities. In practice, a person or business entity that carries out production activities is called a producer. Producers produce goods to be sold to meet the needs of others and theirindividuals. Production activities, there is an activity of processing raw materials into semi-finished materials, and then proceeding from semi-finished materials to finished materials. Therefore, a separate focus is needed to determine the amount of production, output, and input that is done. One thing that can be done is knowing up to calculating the needs of all processes to the production target. While the focus of production activities from the production system to inventory is First, forecasting is important and foremost. Second, inventory control is very important in the production system for inventory, especially in planning the purchase and delivery of raw materials and components. Third, the production of large quantities of inventory items is more structured.
Application of K-Means Clustering for Detection Downy Mildew at Madura Corn Plant Using Digital Image Processing Imron Rosyadi NR; Erwin Prasetyowati; Badar Said; Syaiful Arifin; Mohammad Syafiir Ridoni
Tibuana Vol 6 No 2 (2023): Tibuana
Publisher : UNIPA PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/tibuana.6.2.7845.147-152

Abstract

The development and cultivation of corn is necessary in line with the increasing consumption of food ingredients and industrial needs, especially food products made from corn. In the development of maize in Indonesia, the main obstacle is the disturbance of Plant Pest Organisms (OPT), especially diseases, one of which is downy mildew. This disease can be identified by a change in color, so we need a way to find out the difference between the color of healthy leaves and the color of leaves that have changed due to downy mildew. One solution that can be used is image processing. Therefore the aim of this study was to detect downy mildew based on leaf color in corn plants based on digital image processing, to produce precise and objective results. The algorithm used is the K-Means Clustering algorithm. This study uses 50 images of training data and 25 images of test data. Based on the simulation of downy mildew disease identification using K-Means Clustering it achieves an accuracy rate of 85%.