Big Data Analysis Using Hadoop Framework and Machine Learning as Decision Support System (DSS) (Case Study: Knowledge of Islam Mindset)

被引:0
|
作者
Nurhayati [1 ]
Busman [2 ]
Amrizal, Victor [1 ]
机构
[1] Syarif Hidaytullah State Islamic Univ Jakarta, Fac Sci & Technol, Dept Informat Engn, Jl Ir H Djuanda 95 Ciputat, Southt Tangerang 15412, Banten, Indonesia
[2] STIE Gotong Royong Jakarta, Dept Management, Jakarta, Indonesia
关键词
Framework; Hadoop Distributed File System (HDFS); Big Data; Machine Learning; DSS;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Big Data is a popular term which use to visualize exponential grow and un-structural and structural data storage. Therefore we need to analyses big data accurately in real time to make better accurate result. One of the ways to do it is by using HDFS (Hadoop File Distributed File System). Another one, the big data processing can be done by using machine learning. Machine learning performs data processing based on science and engineer curiosity. The development at UIN and its diverse students and their mindset about Islam are also diverse. We need a Technical to process data to get corrected information about that. This research based on above background which called Big Data Analytics with Hadoop Framework and Machine learning to observe mindset of students and lecturers for DSS. This research used unsupervised learning method for collected data from paper-based questionnaire and online-based questionnaire. The process is by using, K-Mean algorithm as one of unsupervised learning algorithm. We cluster data with major denominations in Islam (sunni and shia). Finally, the goal of data processing resulted table and graph of volume, variety, velocity from the mindset of islam literacy from despondence. We will analyze in big data environment using Hadoop and machine learning algorithm for Decision Support System (DSS) for top management to develop academic environtment at UIN Jakarta.
引用
收藏
页码:43 / 48
页数:6
相关论文
共 50 条
  • [31] Tension in big data using machine learning: Analysis and applications
    Wang, Huamao
    Yao, Yumei
    Salhi, Said
    TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2020, 158
  • [32] Decision Based Model for Real-Time IoT Analysis Using Big Data and Machine Learning
    Hina Jamil
    Tariq Umer
    Celal Ceken
    Fadi Al-Turjman
    Wireless Personal Communications, 2021, 121 : 2947 - 2959
  • [33] Decision Based Model for Real-Time IoT Analysis Using Big Data and Machine Learning
    Jamil, Hina
    Umer, Tariq
    Ceken, Celal
    Al-Turjman, Fadi
    WIRELESS PERSONAL COMMUNICATIONS, 2021, 121 (04) : 2947 - 2959
  • [34] From knowledge-based to big data analytic model: a novel IoT and machine learning based decision support system for predictive maintenance in Industry 4.0
    Rosati, Riccardo
    Romeo, Luca
    Cecchini, Gianalberto
    Tonetto, Flavio
    Viti, Paolo
    Mancini, Adriano
    Frontoni, Emanuele
    JOURNAL OF INTELLIGENT MANUFACTURING, 2023, 34 (01) : 107 - 121
  • [35] From knowledge-based to big data analytic model: a novel IoT and machine learning based decision support system for predictive maintenance in Industry 4.0
    Riccardo Rosati
    Luca Romeo
    Gianalberto Cecchini
    Flavio Tonetto
    Paolo Viti
    Adriano Mancini
    Emanuele Frontoni
    Journal of Intelligent Manufacturing, 2023, 34 : 107 - 121
  • [36] A novel approach for decision support system in cricket using machine learning
    Jha, Sudan
    Routray, Sidheswar
    Abdeljaber, Hikmat A. M.
    Ahmad, Sultan
    INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY, 2022, 69 (01) : 86 - 92
  • [37] Football training evaluation using machine learning and decision support system
    Qiangqiang Xu
    Xin He
    Soft Computing, 2022, 26 : 10939 - 10946
  • [38] Review on enhancing clinical decision support system using machine learning
    Masood, Anum
    Naseem, Usman
    Rashid, Junaid
    Kim, Jungeun
    Razzak, Imran
    CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY, 2024,
  • [39] Football training evaluation using machine learning and decision support system
    Xu, Qiangqiang
    He, Xin
    SOFT COMPUTING, 2022, 26 (20) : 10939 - 10946
  • [40] Machine Learning in Capital Markets: Decision Support System for Outcome Analysis
    Rosati, Riccardo
    Romeo, Luca
    Goday, Carlos Alfaro
    Menga, Tullio
    Frontoni, Emanuele
    IEEE ACCESS, 2020, 8 (08): : 109080 - 109091