Open AccessPerengkingan Pengetahuan Dalam Time Series Data Mining dengan J-Measure
Author(s) -
Relita Buaton,
Muhammad Zarlis,
Herman Mawengkang,
Syahril Effendi
Publication year - 2019
Publication title -
prosiding seminar nasional riset information science (senaris)
Language(s) - English
Resource type - Journals
ISSN - 2686-0260
DOI - 10.30645/senaris.v1i0.130
Subject(s) - measure (data warehouse) , computer science , data mining , database transaction , euclidean distance , representation (politics) , data warehouse , time series , transaction data , database , artificial intelligence , machine learning , politics , political science , law
Computer system development is increasing very rapidly in generating and collecting data that can be seen in terms of the application of computerized systems that continuously improve transaction data in the business world and in government systems, as well as the ability of hardware to store data with large capacity, increasing interest in mining data in accordance with technological developments, including problems related to computer science and data representation which are considered effective and efficient solutions. In this study the technique used is processing time series data, some of the knowledge produced is then ranked so that priority knowledge is obtained with a high level of confidence. Proximity distance using j-measure euclidean and cracking. Based on the results of cracking found rules based on the level of confidence that can be used as a decision support