صورة الغلاف

Ftir of halal and non-halal adulterations prediction analytics using induction decision tree (id3) algorithm

Advanced analytical practices such as data mining or predictive analytics are concepts that are increasingly vital in the area of large data sets. Voluminous data are collected over the years and it is important to assess the data quality for the value of information. Large amounts...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Arief, Akbar, Kartiwi, Mira, Jaswir, Irwandi
التنسيق: مقال
اللغة:English
منشور في: IIUM Press 2020
الموضوعات:
QA Mathematics
T Technology (General)
الوصول للمادة أونلاين:http://irep.iium.edu.my/86368/1/86368_Ftir%20of%20halal%20and%20non-halal%20adulterations.pdf
http://irep.iium.edu.my/86368/
https://journals.iium.edu.my/kict/index.php/jisdt/article/view/150/102
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spelling my.iium.irep.863682020-12-18T09:27:34Z http://irep.iium.edu.my/86368/ Ftir of halal and non-halal adulterations prediction analytics using induction decision tree (id3) algorithm Arief, Akbar Kartiwi, Mira Jaswir, Irwandi QA Mathematics T Technology (General) Advanced analytical practices such as data mining or predictive analytics are concepts that are increasingly vital in the area of large data sets. Voluminous data are collected over the years and it is important to assess the data quality for the value of information. Large amounts of data can contain knowledge in the form of patterns. What knowledge an organization especially the high-paced halal industry can get once data quality is assessed and data mining technique is applied? In this research, we have two objectives. Number one is to assess the data quality on the unstructured data collected from the Fourier-transform Infrared Spectroscopy (FTIR) instrument and number two is to identify patterns of halal and non-halal samples which have been analyzed using the FTIR instrument from International Institute for Halal Research & Training (INHART) laboratory. Total Data Quality Management (TDQM) methodology is used in this research where field observation, interview with the stakeholders, and data auditing will be our main objectives. Decision tree for data mining technique is used and this will be done by classifying the sample set based on its halalness. IIUM Press 2020-11-30 Article PeerReviewed application/pdf en http://irep.iium.edu.my/86368/1/86368_Ftir%20of%20halal%20and%20non-halal%20adulterations.pdf Arief, Akbar and Kartiwi, Mira and Jaswir, Irwandi (2020) Ftir of halal and non-halal adulterations prediction analytics using induction decision tree (id3) algorithm. Journal of Information Systems and Digital Technologies, 2 (2). pp. 42-57. E-ISSN 2682-8790 https://journals.iium.edu.my/kict/index.php/jisdt/article/view/150/102
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
topic QA Mathematics
T Technology (General)
spellingShingle QA Mathematics
T Technology (General)
Arief, Akbar
Kartiwi, Mira
Jaswir, Irwandi
Ftir of halal and non-halal adulterations prediction analytics using induction decision tree (id3) algorithm
description Advanced analytical practices such as data mining or predictive analytics are concepts that are increasingly vital in the area of large data sets. Voluminous data are collected over the years and it is important to assess the data quality for the value of information. Large amounts of data can contain knowledge in the form of patterns. What knowledge an organization especially the high-paced halal industry can get once data quality is assessed and data mining technique is applied? In this research, we have two objectives. Number one is to assess the data quality on the unstructured data collected from the Fourier-transform Infrared Spectroscopy (FTIR) instrument and number two is to identify patterns of halal and non-halal samples which have been analyzed using the FTIR instrument from International Institute for Halal Research & Training (INHART) laboratory. Total Data Quality Management (TDQM) methodology is used in this research where field observation, interview with the stakeholders, and data auditing will be our main objectives. Decision tree for data mining technique is used and this will be done by classifying the sample set based on its halalness.
format Article
author Arief, Akbar
Kartiwi, Mira
Jaswir, Irwandi
author_facet Arief, Akbar
Kartiwi, Mira
Jaswir, Irwandi
author_sort Arief, Akbar
title Ftir of halal and non-halal adulterations prediction analytics using induction decision tree (id3) algorithm
title_short Ftir of halal and non-halal adulterations prediction analytics using induction decision tree (id3) algorithm
title_full Ftir of halal and non-halal adulterations prediction analytics using induction decision tree (id3) algorithm
title_fullStr Ftir of halal and non-halal adulterations prediction analytics using induction decision tree (id3) algorithm
title_full_unstemmed Ftir of halal and non-halal adulterations prediction analytics using induction decision tree (id3) algorithm
title_sort ftir of halal and non-halal adulterations prediction analytics using induction decision tree (id3) algorithm
publisher IIUM Press
publishDate 2020
url http://irep.iium.edu.my/86368/1/86368_Ftir%20of%20halal%20and%20non-halal%20adulterations.pdf
http://irep.iium.edu.my/86368/
https://journals.iium.edu.my/kict/index.php/jisdt/article/view/150/102
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