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PENGGUNAAN ALGORITHMA APRIORI DATA MINING UNTUK MENGETAHUI TINGKATKESETIAAN KONSUMEN (BRAND LOYALITY) TERHADAP MEREK KENDERAAN BERMOTOR (STUDI KASUS DEALER HONDA RUMBAI)

open access: yesDigital Zone: Jurnal Teknologi Informasi dan Komunikasi, 2016
AbstrakAlgoritma yang umum digunakan dalam proses pencarian frequent itemset (data yang paling sering muncul) adalah Apriori. Tetapi Algoritma Apriori mempunyai memiliki kekurangan yaitu membutuhkan waktu yang lama dalam proses pencarian frequent itemset.
Wirdah Choiriah
doaj   +3 more sources

Efficient Mining of Frequent Itemsets Using Only One Dynamic Prefix Tree

open access: yesIEEE Access, 2020
Frequent itemset mining is a fundamental problem in data mining area because frequent itemsets have been extensively used in reasoning, classifying, clustering, and so on.
Jun-Feng Qu   +5 more
doaj   +1 more source

ETP-Mine: An Efficient Method for Mining Transitional Patterns [PDF]

open access: yes, 2010
A Transaction database contains a set of transactions along with items and their associated timestamps. Transitional patterns are the patterns which specify the dynamic behavior of frequent patterns in a transaction database.
Bhaskar, A., Kumar, B. Kiran
core   +2 more sources

An Efficient Rigorous Approach for Identifying Statistically Significant Frequent Itemsets [PDF]

open access: yes, 2009
As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is becoming a major challenge in data mining applications.
Kirsch, Adam   +5 more
core   +3 more sources

Implementasi Algoritma FP-Growth dengan Closure Table untuk Penemuan Frequent Itemset pada Keranjang Belanja

open access: yesMajalah Ilmiah Teknologi Elektro, 2018
Algoritma FP-growth adalah algoritma data mining yang digunakan untuk menemukan frequent itemset pada data keranjang belanja. Frequent itemset adalah kelompok barang yang sering dibeli bersamaan dalam satu keranjang belanja. Analisa frequent itemset akan
I Gusti Agung Indrawan   +2 more
doaj   +1 more source

Video Mining with Frequent Itemset Configurations [PDF]

open access: yes, 2006
We present a method for mining frequently occurring objects and scenes from videos. Object candidates are detected by finding recurring spatial arrangements of affine covariant regions. Our mining method is based on the class of frequent itemset mining algorithms, which have proven their efficiency in other domains, but have not been applied to video ...
Quack, Till   +2 more
openaire   +2 more sources

Re-mining item associations: methodology and a case study in apparel retailing [PDF]

open access: yes, 2010
Association mining is the conventional data mining technique for analyzing market basket data and it reveals the positive and negative associations between items.
Atan, Tankut   +4 more
core   +1 more source

Frequent Itemset Mining and Association Rules [PDF]

open access: yes, 2006
With the advent of mass storage devices, databases have become larger and larger. Point-of-sale data, patient medical data, scientific data, and credit card transactions are just a few sources of the ever-increasing amounts of data. These large datasets provide a rich source of useful information.
Imberman S., Tansel A.U.
openaire   +3 more sources

An Efficient Spark-Based Hybrid Frequent Itemset Mining Algorithm for Big Data

open access: yesData, 2022
Frequent itemset mining (FIM) is a common approach for discovering hidden frequent patterns from transactional databases used in prediction, association rules, classification, etc. Apriori is an FIM elementary algorithm with iterative nature used to find
Mohamed Reda Al-Bana   +2 more
doaj   +1 more source

Peak-Jumping Frequent Itemset Mining Algorithms [PDF]

open access: yes, 2006
We analyze algorithms that, under the right circumstances, permit efficient mining for frequent itemsets in data with tall peaks (large frequent itemsets). We develop a family of level-by-level peak-jumping algorithms, and study them using a simple probability model. The analysis clarifies why the jumping idea sometimes works well, and which properties
Dexters, Nele   +2 more
openaire   +2 more sources

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