TELKOMNIKA Telecommunication, Computing, Electronics and Control
Parallel classification and optimization of telco trouble ticket dataset

Dublin Core

Title

TELKOMNIKA Telecommunication, Computing, Electronics and Control
Parallel classification and optimization of telco trouble ticket dataset

Subject

Classification
Hadoop
Optimization
Spark
Trouble ticket

Description

In the big data age, extracting applicable information using traditional machine
learning methodology is very challenging. This problem emerges from the
restricted design of existing traditional machine learning algorithms, which do
not entirely support large datasets and distributed processing. The large

volume of data nowadays demands an efficient method of building machine-
learning classifiers to classify big data. New research is proposed to solve

problems by converting traditional machine learning classification into a
parallel capable. Apache Spark is recommended as the primary data processing
framework for the research activities. The dataset used in this research is
related to the telco trouble ticket, identified as one of the large volume datasets.
The study aims to solve the data classification problem in a single machine
using traditional classifiers such as W-J48. The proposed solution is to enable
a conventional classifier to execute the classification method using big data
platforms such as Hadoop. This study’s significant contribution is the output
matrix evaluation, such as accuracy and computational time taken from both
ways resulting from hyper-parameter tuning and improvement of W-J48
classification accuracy for the telco trouble ticket dataset. Additional
optimization and estimation techniques have been incorporated into the study,
such as grid search and cross-validation method, which significantly improves
classification accuracy by 22.62% and reduces the classification time by
21.1% in parallel execution inside the big data environment.

Creator

Fauzy Che Yayah, Khairil Imran Ghauth, Choo-Yee Ting

Source

http://journal.uad.ac.id/index.php/TELKOMNIKA

Date

Sep 20, 2020

Contributor

peri irawan

Format

pdf

Language

english

Type

text

Files

Collection

Tags

,Repository, Repository Horizon University Indonesia, Repository Universitas Horizon Indonesia, Horizon.ac.id, Horizon University Indonesia, Universitas Horizon Indonesia, HorizonU, Repo Horizon , ,Repository, Repository Horizon University Indonesia, Repository Universitas Horizon Indonesia, Horizon.ac.id, Horizon University Indonesia, Universitas Horizon Indonesia, HorizonU, Repo Horizon , ,Repository, Repository Horizon University Indonesia, Repository Universitas Horizon Indonesia, Horizon.ac.id, Horizon University Indonesia, Universitas Horizon Indonesia, HorizonU, Repo Horizon , ,Repository, Repository Horizon University Indonesia, Repository Universitas Horizon Indonesia, Horizon.ac.id, Horizon University Indonesia, Universitas Horizon Indonesia, HorizonU, Repo Horizon , ,Repository, Repository Horizon University Indonesia, Repository Universitas Horizon Indonesia, Horizon.ac.id, Horizon University Indonesia, Universitas Horizon Indonesia, HorizonU, Repo Horizon ,

Citation

Fauzy Che Yayah, Khairil Imran Ghauth, Choo-Yee Ting, “TELKOMNIKA Telecommunication, Computing, Electronics and Control
Parallel classification and optimization of telco trouble ticket dataset,” Repository Horizon University Indonesia, accessed April 3, 2025, https://repository.horizon.ac.id/items/show/3826.