Papers by Fauzy Che Yayah
TELKOMNIKA, 2021
In the big data age, extracting applicable information using traditional machine learning methodo... more 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.
Projek ini dibangunkan adalah bertujuan untuk menghasilkan satu permainan video berkomputer yang ... more Projek ini dibangunkan adalah bertujuan untuk menghasilkan satu permainan video berkomputer yang berasakan pengaturcaraan DirectX dengan melibatkan pengubahsuaian grafik dan bunyi permainan video berkomputer yang asal iaitu Doom. Antaramuka yang dihasilkan berkemampuan untuk beroperasi di dalam persekitaran Windows 95 atau Windows 98. Permainan video berkomputer ini telah meningkatkan lagi keupayaan permainan video berkomputer yang asal disamping memberi kemudahan kepada pengguna yang berumur 12 tahun terutamanya kanak-kanak. Bahasa utama konsol permainan video ini juga telah ditukarkan kepada Bahasa Melayu untuk memberikan kefahaman di dalam pengendalian permainan video berkomputer ini. Permainan video berkomputer yang telah dinamakan sebagai Musnah yang bermaksud Doom di dalam Bahasa Inggeris
TELKOMNIKA (Telecommunication Computing Electronics and Control)
Journal of Computer Science & Computational Mathematics
Nowadays, adopting big data is a reality. Telecommunication company or telco must find the right ... more Nowadays, adopting big data is a reality. Telecommunication company or telco must find the right solution to store all information available across the organization to maximize revenue using the analytics. The solution must be able to harness the large volume, variety, and velocity of the data available. One of the challenging actions is how to perform decision making and analysis in real-time. Some of the operational decisions may not comply with the corporation policy which makes it hard to keep up with the modern evolving business environment. Telco needs a platform to improve the business process and sustainable and profitable growth. The significant impacts should involve improvements of the customer experience and more reliable network quality, thereby reducing the customer churn rate. Big data and machine learning represent today's trends for the analytics. With big data analytics, the service provider can utilize the full potential of their data set by correlating, processing, and deciphering the hidden information from it. The conventional machine learning tools without big data are becoming inadequate as the trends shift towards distributed and real-time processing. The service provider needs the solution big data-driven which supports them to achieve timely manner and more accurate insights via the predictive analytics, text mining, and optimization. This paper also explains the characteristics of big data, and several uses of case implementing machine learning inside the big data platform related to telco operation such as mobile fraud detection. A well-known big data processing framework such as Hadoop indicated that there is an integration with machine learning tools such as Mahout, H2O.ai, R-Hadoop components, and KNIME. The advantages of these tools are evaluated based on their scalability, ease of use and extensibility features.
Journal of Computer Science & Computational Mathematics
Nowadays, adopting big data is a reality. Telecommunication company or telco must find the right ... more Nowadays, adopting big data is a reality. Telecommunication company or telco must find the right solution to store all information available across the organization to maximize revenue using the analytics. The solution must be able to harness the large volume, variety, and velocity of the data available. One of the challenging actions is how to perform decision making and analysis in real-time. Some of the operational decisions may not comply with the corporation policy which makes it hard to keep up with the modern evolving business environment. Telco needs a platform to improve the business process and sustainable and profitable growth. The significant impacts should involve improvements of the customer experience and more reliable network quality, thereby reducing the customer churn rate. Big data and machine learning represent today's trends for the analytics. With big data analytics, the service provider can utilize the full potential of their data set by correlating, processing, and deciphering the hidden information from it. The conventional machine learning tools without big data are becoming inadequate as the trends shift towards distributed and real-time processing. The service provider needs the solution big data-driven which supports them to achieve timely manner and more accurate insights via the predictive analytics, text mining, and optimization. This paper also explains the characteristics of big data, and several uses of case implementing machine learning inside the big data platform related to telco operation such as mobile fraud detection. A well-known big data processing framework such as Hadoop indicated that there is an integration with machine learning tools such as Mahout, H2O.ai, R-Hadoop components, and KNIME. The advantages of these tools are evaluated based on their scalability, ease of use and extensibility features.
Journal of Computer Science & Computational Mathematics
Nowadays, adopting big data is a reality. Telecommunication company or telco must find the right ... more Nowadays, adopting big data is a reality. Telecommunication company or telco must find the right solution to store all information available across the organization to maximize revenue using the analytics. The solution must be able to harness the large volume, variety, and velocity of the data available. One of the challenging actions is how to perform decision making and analysis in real-time. Some of the operational decisions may not comply with the corporation policy which makes it hard to keep up with the modern evolving business environment. Telco needs a platform to improve the business process and sustainable and profitable growth. The significant impacts should involve improvements of the customer experience and more reliable network quality, thereby reducing the customer churn rate. Big data and machine learning represent today's trends for the analytics. With big data analytics, the service provider can utilize the full potential of their data set by correlating, processing, and deciphering the hidden information from it. The conventional machine learning tools without big data are becoming inadequate as the trends shift towards distributed and real-time processing. The service provider needs the solution big data-driven which supports them to achieve timely manner and more accurate insights via the predictive analytics, text mining, and optimization. This paper also explains the characteristics of big data, and several uses of case implementing machine learning inside the big data platform related to telco operation such as mobile fraud detection. A well-known big data processing framework such as Hadoop indicated that there is an integration with machine learning tools such as Mahout, H2O.ai, R-Hadoop components, and KNIME. The advantages of these tools are evaluated based on their scalability, ease of use and extensibility features.
Computer and Network Technology - Proceedings of the International Conference on ICCNT 2009, 2010
Uploads
Papers by Fauzy Che Yayah