Competency Characteristics of Graduates Viewed from User Satisfaction Using Nonhierarchical Clusters
This study aims to classify graduates based on the similarity of competency characteristics by referring to the indicators of graduate user satisfaction. The indicators are implementation of Islamic values; integrity, ethics, and morals; expertise based on knowledge (professionalism); foreign langua...
| Main Authors: | , |
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| Format: | Article |
| Language: | Arabic |
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State Institute of Islamic Studies Imam Bonjol Padang
2021-11-01
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| Series: | Al-Ta'lim |
| Subjects: | |
| Online Access: | https://journal.tarbiyahiainib.ac.id/index.php/attalim/article/view/671 |
| _version_ | 1827300591187001344 |
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| author | Muhammad Ikhsan Ghozali Heri Retnawati |
| author_facet | Muhammad Ikhsan Ghozali Heri Retnawati |
| author_sort | Muhammad Ikhsan Ghozali |
| collection | DOAJ |
| description | This study aims to classify graduates based on the similarity of competency characteristics by referring to the indicators of graduate user satisfaction. The indicators are implementation of Islamic values; integrity, ethics, and morals; expertise based on knowledge (professionalism); foreign language skills; ability to use ICT; communication; teamwork; and self-development. The survey was aimed at graduates of five study programs totaling 211 people. Determination of respondents using the purposive sampling technique. Data was collected through a questionnaire containing statements about the eight indicators. Data analysis uses descriptive and multivariate statistics with the non-hierarchical cluster method or K-Means cluster analysis, assisted with SPSS (Statistical Package for Social Science) software. The results show that based on the similarity of competency characteristics, graduates are grouped into three clusters, namely Cluster 1 with 13.27% with characteristics of graduates with low competence, Cluster 2 with 32.7% with characteristics of graduates with high competence, and Cluster 3 with 54.03% with the characteristics of graduates with moderate competence. Thus, a strategic program that is systematic, comprehensive, and continuous is needed to develop human resources to shape the quality mentality and competence of students and to be competitive with students and by the needs of the workforce or users. For this reason, it is necessary to develop an e-tracer system that is integrated with the campus web and to strengthen synergistic cooperation with stakeholders, including users. |
| first_indexed | 2024-04-24T16:07:42Z |
| format | Article |
| id | doaj.art-6f6b9e84d9034be4911ccd1fec450f0d |
| institution | Directory Open Access Journal |
| issn | 1410-7546 2355-7893 |
| language | Arabic |
| last_indexed | 2024-04-24T16:07:42Z |
| publishDate | 2021-11-01 |
| publisher | State Institute of Islamic Studies Imam Bonjol Padang |
| record_format | Article |
| series | Al-Ta'lim |
| spelling | doaj.art-6f6b9e84d9034be4911ccd1fec450f0d2024-03-31T20:05:23ZaraState Institute of Islamic Studies Imam Bonjol PadangAl-Ta'lim1410-75462355-78932021-11-0128326127210.15548/jt.v28i3.671351Competency Characteristics of Graduates Viewed from User Satisfaction Using Nonhierarchical ClustersMuhammad Ikhsan Ghozali0Heri Retnawati1Universitas Negeri Yogyakarta and IAIN Syaikh Abdurrahman Siddik Bangka BelitungUniversitas Negeri YogyakartaThis study aims to classify graduates based on the similarity of competency characteristics by referring to the indicators of graduate user satisfaction. The indicators are implementation of Islamic values; integrity, ethics, and morals; expertise based on knowledge (professionalism); foreign language skills; ability to use ICT; communication; teamwork; and self-development. The survey was aimed at graduates of five study programs totaling 211 people. Determination of respondents using the purposive sampling technique. Data was collected through a questionnaire containing statements about the eight indicators. Data analysis uses descriptive and multivariate statistics with the non-hierarchical cluster method or K-Means cluster analysis, assisted with SPSS (Statistical Package for Social Science) software. The results show that based on the similarity of competency characteristics, graduates are grouped into three clusters, namely Cluster 1 with 13.27% with characteristics of graduates with low competence, Cluster 2 with 32.7% with characteristics of graduates with high competence, and Cluster 3 with 54.03% with the characteristics of graduates with moderate competence. Thus, a strategic program that is systematic, comprehensive, and continuous is needed to develop human resources to shape the quality mentality and competence of students and to be competitive with students and by the needs of the workforce or users. For this reason, it is necessary to develop an e-tracer system that is integrated with the campus web and to strengthen synergistic cooperation with stakeholders, including users.https://journal.tarbiyahiainib.ac.id/index.php/attalim/article/view/671non-hierarchical cluster analysisk-means cluster analysischaracteristics of graduate competence. |
| spellingShingle | Muhammad Ikhsan Ghozali Heri Retnawati Competency Characteristics of Graduates Viewed from User Satisfaction Using Nonhierarchical Clusters Al-Ta'lim non-hierarchical cluster analysis k-means cluster analysis characteristics of graduate competence. |
| title | Competency Characteristics of Graduates Viewed from User Satisfaction Using Nonhierarchical Clusters |
| title_full | Competency Characteristics of Graduates Viewed from User Satisfaction Using Nonhierarchical Clusters |
| title_fullStr | Competency Characteristics of Graduates Viewed from User Satisfaction Using Nonhierarchical Clusters |
| title_full_unstemmed | Competency Characteristics of Graduates Viewed from User Satisfaction Using Nonhierarchical Clusters |
| title_short | Competency Characteristics of Graduates Viewed from User Satisfaction Using Nonhierarchical Clusters |
| title_sort | competency characteristics of graduates viewed from user satisfaction using nonhierarchical clusters |
| topic | non-hierarchical cluster analysis k-means cluster analysis characteristics of graduate competence. |
| url | https://journal.tarbiyahiainib.ac.id/index.php/attalim/article/view/671 |
| work_keys_str_mv | AT muhammadikhsanghozali competencycharacteristicsofgraduatesviewedfromusersatisfactionusingnonhierarchicalclusters AT heriretnawati competencycharacteristicsofgraduatesviewedfromusersatisfactionusingnonhierarchicalclusters |