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الرئيسية > Principal Component Analysis T...>الوصف

Principal Component Analysis Technique for Finding the Best Applicant for a Job: Case Study at Cihan University-Erbil

المصدر: مجلة جامعة جيهان أربيل للعلوم الإنسانية والاجتماعية
الناشر: جامعة جيهان أربيل
المؤلف الرئيسي: Jameel, Abbood M. (Author)
مؤلفين آخرين: Al-Salami, Qusay H. (Co-Author)
المجلد/العدد: مج7, ع1
محكمة: نعم
الدولة: العراق
التاريخ الميلادي: 2023
الصفحات: 121 - 125
ISSN: 2709-8648
رقم MD: 1431766
نوع المحتوى: بحوث ومقالات
اللغة: الإنجليزية
قواعد المعلومات: EduSearch, HumanIndex
مواضيع:
مسابقات التوظيف | موظفو الجامعات | تحليل البيانات | الجامعات العراقية
كلمات المؤلف المفتاحية:
Allocating Scores and Ranks | Eigen Values and Eigen Vectors | Matrices | Multivariate Analysis | Principal Component Analysis
رابط المحتوى:

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المستخلص: This paper focuses on the use of principal component analysis (PCA) technique in choosing the best applicant for a job in Cihan University-Erbil. Cihan University has a panel of judges (University staff) to help in choosing the applicants for a job by evaluating or rating each one on different scale of preference and different type of characteristics. This process usually creates complicated multivariate data structure, which consists of 25 applicants for a job rated by a panel of judges on 17 characteristics (25 rows, applicants, and 17 columns, characteristics). PCA plays a crucial role in conducting impactful research as it offers a potent technique for analyzing multivariate data. Researchers can utilize this method to extract valuable information that aids decision-makers in problem-solving. To ensure the appropriateness of data for PCA, certain testing procedures are necessary. In this study, two tests, namely, the Kaiser-Meyer-Olkin measure of sampling adequacy and Bartlett’s test of sphericity, were performed, and their significance is vital. The findings indicate that the data employed in this research are suitable for PCA. Scoring and ranking procedures as extra tools were used to see that applicant No. (1) Is the first accepted for a job, applicant No. (17) Is the second, applicant No. (12) Is the third, and so on.
ISSN: 2709-8648

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