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  <timestamp>20261008000209</timestamp>
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  <journal>
   <journal_metadata language="en">
    <full_title>Fusion: Practice and Applications</full_title>
    <abbrev_title>FPA</abbrev_title>
    <issn media_type="print">2770-0070</issn>
    <issn media_type="electronic">2692-4048</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2021</year>
    </publication_date>
    <journal_volume>
     <volume>6</volume>
    </journal_volume>
    <issue>2</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Weather Forecasting for Batu Pahat Using Neural Network</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Chan</given_name>
      <surname>Weng</surname>
      <affiliations>
       <institution>
        <institution_name>Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, BatuPahat, Johor, Malaysia</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Rozaida B.</given_name>
      <surname>Ghazali</surname>
      <affiliations>
       <institution>
        <institution_name>Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, BatuPahat, Johor, Malaysia</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Salama A.</given_name>
      <surname>Mustafa</surname>
      <affiliations>
       <institution>
        <institution_name>Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, BatuPahat, Johor, Malaysia</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>A.Noori</given_name>
      <surname>Kareem</surname>
      <affiliations>
       <institution>
        <institution_name>Computer Engineering Department, Bilad Alrafidain University College, Ba’aqubah, Diyala, 32001, Iraq</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Bashar A.</given_name>
      <surname>Khalaf</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Medical Instruments Engineering Techniques, Bilad Alrafidain University College, Ba’aqubah 32001, Diyala, Iraq</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>Nowadays, weather forecasting plays a vital role in human activities. The complexity of data gathering in the meteorology department and high technical costs lead to inaccurate weather forecasting. Due to minimize this problem, an application using an artificial neural network (ANN) has been developed to forecast weather conditions using the Matlab compiler. This application will help users to define the weather conditions daily well and make early preparation to encounter uncertainty. This application performs in Multilayer Perceptron (MLP) using the back-propagation (BP) algorithm. The data is undergoing training and testing based on actual data obtained from the Malaysian Meteorological Department. The result will show in graph plotting for the training and testing process. Predictive accuracy for each step of stimulation will measure using Mean Square Error (MSE) graph in this application. Therefore, this application will be able to assist the Malaysian Meteorological Department to forecast weather, so our government and people have sufficient time to prepare and solve.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2021</year>
    </publication_date>
    <pages>
     <first_page>64</first_page>
     <last_page>71</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">831</item_number>
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     <doi>10.54216/FPA.060204</doi>
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