A Multiagent System (MAS) for the Generation of Initial Centroids for kmeans Clustering Data Mining Algorithm based on Actual Sample Datapoints

2010 ◽  
Vol 1 (2) ◽  
pp. 85-95
Author(s):  
Dost Muhammad Khan ◽  
Nawaz Mohamudally
Keyword(s):  
Data Mining ◽  
Multiagent System ◽  
Data Mining Algorithm ◽  
Actual Sample ◽  
Mining Algorithm ◽  
Clustering Data

scholarly journals Analisis K-Means Clustering pada Data Sepeda Motor

2020 ◽  
Vol 5 (1) ◽  
pp. 10
Author(s):  
Rozzi Kesuma Dinata ◽  
Safwandi Safwandi ◽  
Novia Hasdyna ◽  
Nur Azizah
Keyword(s):  
Data Mining ◽  
Euclidean Distance ◽  
Cluster System ◽  
Data Mining Algorithm ◽  
Average Value ◽  
Mining Algorithm ◽  
Clustering Data ◽  
Distance Formula

K-Means is a data mining algorithm that can be used to grouping or clustering data. This research using k-means for clustering the data of motorcycle based on consumer needs. The dataset used in this research is Honda and Yamaha motorcycle which taken from the dialers in Dewantara District, Aceh. The data tested by grouping 300 data of motorcycle with different attributes into 3 clusters, which are cheap, normal, and expensive. The distribution of the data we separate it using 45 data in 15 times of test. Each test used 3 different data randomly selected on each test. To calculate the distance of each motorcycle data that have been inputted to each centroid, we used the Euclidean Distance formula. Data in this cluster system can be used as a recommendation for users in selecting the motorcycle that they interest the most. The results of the performance on each test finished in 15 times shown that  the average value of Precision by 76%, Recall by 76% and  the accuracy by 81%.

scholarly journals A product-centric data mining algorithm for targeted promotions

2020 ◽  
Vol 54 ◽  
pp. 101940 ◽  
Author(s):  
Raymond Moodley ◽  
Francisco Chiclana ◽  
Fabio Caraffini ◽  
Jenny Carter
Keyword(s):  
Data Mining ◽  
Data Mining Algorithm ◽  
Mining Algorithm

scholarly journals Life-cycle Asset Management in Residential Developments Building on Transport System Critical Attributes via a Data-mining Algorithm

Buildings ◽  
2018 ◽  
Vol 9 (1) ◽  
pp. 1 ◽  
Author(s):  
Umair Hasan ◽  
Andrew Whyte ◽  
Hamad Al Jassmi
Keyword(s):  
Data Mining ◽  
Life Cycle ◽  
Built Environment ◽  
Transport System ◽  
Asset Management ◽  
Public Transport ◽  
Categorical Variables ◽  
Data Mining Algorithm ◽  
Large Set ◽  
Mining Algorithm

Public transport can discourage individual car usage as a life-cycle asset management strategy towards carbon neutrality. An effective public transport system contributes greatly to the wider goal of a sustainable built environment, provided the critical transit system attributes are measured and addressed to (continue to) improve commuter uptake of public systems by residents living and working in local communities. Travel data from intra-city travellers can advise discrete policy recommendations based on a residential area or development’s public transport demand. Commuter segments related to travelling frequency, satisfaction from service level, and its value for money are evaluated to extract econometric models/association rules. A data mining algorithm with minimum confidence, support, interest, syntactic constraints and meaningfulness measure as inputs is designed to exploit a large set of 31 variables collected for 1,520 respondents, generating 72 models. This methodology presents an alternative to multivariate analyses to find correlations in bigger databases of categorical variables. Results here augment literature by highlighting traveller perceptions related to frequency of buses, journey time, and capacity, as a net positive effect of frequent buses operating on rapid transit routes. Policymakers can address public transport uptake through service frequency variation during peak-hours with resultant reduced car dependence apt to reduce induced life-cycle environmental burdens of buildings by altering residents’ mode choices, and a potential design change of buildings towards a public transit-based, compact, and shared space urban built environment.

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