PENERAPAN METODE NAÃVE BAYES PADA PROTOTIPE APLIKASI PENDETEKSI HELM KESELAMATAN KERJA
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Institusion
Politeknik Negeri Jember
Author
Palmasugra, Gilang Rizqi
Subject
458 - Teknik Informatika
Datestamp
2022-08-11 02:30:26
Abstract :
Occupational Health and Safety (OHS) is one of principals and effort to ensure, protect and secure any aspect of worker activities by doing accident preventions and complication that caused in work activity. OHS are essentials thing that any company or business must have and must be applicated. In purpose to know who and what action can be applied to prevent accident in workplace, an effort is required to enforce discipline against the rules that listed in the OHS regulations. OHS observation are an action to know whether safety score where meet its requirement or not. On these observations, some checks were conducted to check any safety attribute were meet its requirement based on every company or bussiness level. Therefore, an observation prototype of application was developed spesifically to detect the presence of attributes, in this case, a safety helmet. This application prototype uses a Naïve Bayes Classifier as a method that can detect any usages of safety helmet at accuracy up to 50.8% based on training data and detections. It is hoped that it can help in enforcing disciplines on the use of OHS attributes, one of which is a safety helmet.
Occupational Health and Safety (OHS) is one of principals and effort to ensure, protect and secure any aspect of worker activities by doing accident preventions and complication that caused in work activity. OHS are essentials thing that any company or business must have and must be applicated. In purpose to know who and what action can be applied to prevent accident in workplace, an effort is required to enforce discipline against the rules that listed in the OHS regulations. OHS observation are an action to know whether safety score where meet its requirement or not. On these observations, some checks were conducted to check any safety attribute were meet its requirement based on every company or bussiness level. Therefore, an observation prototype of application was developed spesifically to detect the presence of attributes, in this case, a safety helmet. This application prototype uses a Naïve Bayes Classifier as a method that can detect any usages of safety helmet at accuracy up to 50.8% based on training data and detections. It is hoped that it can help in enforcing disciplines on the use of OHS attributes, one of which is a safety helmet.
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