Penerapan Supervised Emerging Patterns Untuk Multi Atribut Pada Data Online Izin Usaha Pertambangan di Indonesia (Studi Kasus: EITI Indonesia)
Abstract: Indonesian EITI
(Extractive Industries Transparency Initiative) is an organization under
Ministry of Economic Coordination which used to increase the transparency of
extractive industry in Indonesia. EITI Indonesia manage a lot of data about
mining, one of the managed data is data Mining Business License in Indonesia.
The data has many records that require large storage allocation and difficult
process data that is used by the EITI for decision making. .This data Mining
Business License will be used for the processing of data mining that aims to
help look for interesting patterns to determine a learning and two itemsets
(attributes) that exist. Application Data Mining with Emerging Patterns
Supervised methods will be used as a solution for managing data such large, so
it is easy to produce a decision in the form of an interesting pattern
information to determine the transparency of mining license in Indonesia.
System development methods using CRISP-DM. The design of data mining
applications using the programming language Java, NetBeans and MySQL database
tools used to build a technology Supervised Emerging Patterns in multi-attribute
decision making.
Penulis: yohana tri utami,
Spit Warnars Harco Leslie Hendric
Kode Jurnal: jptkomputerdd160567
