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THE INFLUENCE OF SOCIAL INTERACTION, KNOWLEDGE SHARING, AND PERCEPTIONS OF WORKLOAD ON TEACHER'S READINESS FOR CHANGE AT SMA XYZ-NORTH JAKARTA Arief Wibowo; Abdulah Rakhman
JURNAL KOMUNIKASI DAN BISNIS Vol. 11 No. 1 (2023): Jurnal Komunikasi dan Bisnis Vol. 11 No. 1 Tahun 2023
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Institut Bisnis dan Informatika Kwik Kian Gie

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46806/jkb.v11i1.927

Abstract

This study aimed to examine the influence of the variables of social interaction, knowledge sharing, and perceived workload on readiness for change among teachers at SMA XYZ in North Jakarta. The research method used is a quantitative research method. The number of respondents in this study were 38 teachers. The sample used is all teachers who are currently working at SMA XYZ in North Jakarta. The sampling technique is based on nonprobability sampling using the questionnaire method, namely by providing a list of questions directly to the respondents. The analysis method uses Structural Equation Modeling - Partial Least Square (SEM-PLS) with the WarpPLS 7.0 program. The conclusion of this study is that Social Interaction has a negative and significant effect on Readiness for change, Knowledge Sharing has a positive and significant effect on Readiness for change, and Workload Perception has a positive and significant effect on Readiness for Change for teachers at SMA XYZ in North Jakarta.
KLASTERISASI DATA HASIL STUDI PELACAKAN TENTANG KARIR DAN PEKERJAAN LULUSAN PERGURUAN TINGGI MENGGUNAKAN ALGORITMA K-MEANS Joko Sutrisno; Arief Wibowo; Bayu Satria Pratama
J-Icon : Jurnal Komputer dan Informatika Vol 11 No 2 (2023): Oktober 2023
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v11i2.12031

Abstract

Higher education has a responsibility to produce quality graduates. One indicator of the quality of graduates is the status of getting a job, the condition of the suitability of the field of work with the educational program pursued, and the waiting period to get the job. What is being done to find out these conditions is to conduct a tracer study for graduates. This study analyzes data from a college graduate tracking study about careers and jobs using a data mining clustering algorithm, namely K-Means. The results showed that the analysis of the tracking study data formed several graduate clusters with an evaluation value of the Davies-Bouldin Index (DBI) reaching 0.287 in the first trial and 0.291 in the second trial. The clusters formed consist of groups of graduates with status still needing to be working or currently working. The profile of graduates from each cluster can be identified in the form of a relatively short waiting period of less than six months to get a first job or a relatively slow waiting period of more than one year. Another cluster specification that is formed is about the profile of graduates with the level of compatibility between the education attained and the field of work carried out. The results of this study serve as feedback for study program managers to measure the quality of graduates and the improvements in the educational process that need to be made.