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  <titleInfo>
    <title>Investigation of human error using technique for human error rate prediction (therp) in aquaculture industry</title>
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  <name type="personal">
    <namePart>Adam Eiman Bin Samsuddin,		 						 	,	</namePart>
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    <dateIssued encoding="marc">2025</dateIssued>
    <copyrightDate encoding="marc">2025</copyrightDate>
    <issuance>monographic</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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  <physicalDescription>
    <extent>xiii, 77 pages : illustrations ;</extent>
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  <abstract>The aquaculture industry in Malaysia has rapidly expanded in recent years, creating new economic opportunities but also exposing workers to significant occupational hazards. Among these, human error has emerged as a critical factor influencing safety and operational efficiency. This study investigates the occurrence and impact of human error in aquaculture operations using the Technique for Human Error Rate Prediction (THERP). Key processing activities are receiving, packing, and cold room operations were analysed through Hierarchical Task Analysis (HTA) to identify error-prone tasks and estimate their human error probabilities (HEPs). A structured methodology incorporating Human Reliability Analysis (HRA), task-specific event trees, and expert validation through Focus Group Discussions (FGD) was employed to ensure both qualitative and quantitative rigor. The results provide insight into the likelihood of human error in critical tasks and offer a foundation for targeted interventions aimed at improving safety culture, reducing accidents, and enhancing productivity in the aquaculture sector.</abstract>
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  <note type="statement of responsibility">Adam Eiman Bin Samsuddin</note>
  <note>Faculty of Industrial Sciences and Technology</note>
  <note>Final Year Report (Bachelor Degree Of Occupational Safety And Health) -- Universiti Malaysia Pahang Al-Sultan Abdullah - 2025</note>
  <note>Include bibliographical reference</note>
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    <name type="corporate">
      <namePart>Faculty of Industrial Sciences and Technology</namePart>
    </name>
    <topic>Dissertations</topic>
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  <subject authority="lcsh">
    <topic>Universities and colleges</topic>
    <topic>Dissertations</topic>
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    <topic>Theses</topic>
    <topic>Dissertations</topic>
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  <identifier type="isbn">THE0010963 (Local)</identifier>
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    <recordCreationDate encoding="marc">260812</recordCreationDate>
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