Abstract
Damage to the lathe is difficult to detect and difficult handling so it must be taken to the lathe service workshop first so it wastes time and effort. For example damage to the shaft, pegs, slicing, gear, carrier axis, and clasp tool. This is what drives to build an expert system to detect lathe damage. So it makes it easier to detect and handle the lathe damage quickly. The purpose of this thesis is the creation of an application to detect damage to the lathe by K-Nearest Neighbour method for the lathe. The system implemented with PHP language and MySQL Database and this system can be used on desktop device System have feature detection type of damage, data of symptoms of damage, damage data, and damage detection process. The system is tested using the black box and 70.454% system test result which means the system is running well.Keywords: Expert System, K - Nearest Neighbors, Machine Tool.Damage to the lathe is difficult to detect and difficult handling so it must be taken to the lathe service workshop first so it wastes time and effort. For example damage to the shaft, pegs, slicing, gear, carrier axis, and clasp tool. This is what drives to build an expert system to detect lathe damage. So it makes it easier to detect and handle the lathe damage quickly. The purpose of this thesis is the creation of an application to detect damage to the lathe by K-Nearest Neighbour method for lathe.System implemented with PHP language and MySQL Database and this system can be used on desktop device System has feature detection type of damage, data of symptoms of damage, damage data and damage detection process. The system is tested using black box and 70.454% system test result which means the system is running well.Keywords: Expert System, K - Nearest Neighbors, Machine Tool.
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