A lot consideration has take into account to get an effective production activity in a manufacture such as the knowledge and skill of the operator of machine, the quality of machine, time schedulling of production process quantity of product that has to be finish\u00a0 on schedule, the condition of room and other facilities, and so on, If we fail to manage those condition, it may cause the unstable and ineffective production and this will end up with customs’s dissatisfaction. In this research we were focusing on how to optimize the production process by determining total amount of products, total machine that can be used in one production, time of production and setting the priorities based on those conditions. This optimization will be automatically executed by the web based dessicion support system and this desicion support system adopted the ID3 method.<\/p>\n
The ID3 method, a learning method by building a desicion tree, is used to gain the optimization ,in our case, to optimize the quantity of product , duration of production, number of machine that will be used for each customer’s order. Decision Tree Learning methods (ID3) is a method of learning that is very popular and widely used in artifical Intelligents fields. By building IF THEN statement, calculating entropy and information gain, we can build decision tree. This decision tree is used to get the optimization number of machine that will process the production, quantity of order that will be produced on catain duration of time.<\/p>\n
Dibuat oleh : Youllia Indrawaty N., Mira Musrini B., Taufik Hidayat<\/p>\n
E-mail:\u00a0 youllia@itenas ac.id<\/p>\n
Kata Kunci : Decision Tree Leaming (TD3), scheduling the production process, information gain, priorities,entropy.<\/p>\n
Keterangan : \u00a0Makalah ini\u00a0 dimuat\u00a0 pada Proceedings Of 2013 ICOI The International Conference On Organizational Innovation July 2 \u2013 4, 2013<\/p>\n