ANALISIS KETENAGAKERJAAN MAHASISWA SISTEM INFORMASI ANGKATAN 2023(STUDI KASUS: PEKERJAAN ORANG TUA MAHASISWA)

Authors

  • tri wahyuni tri wahyuni universitas Islam Indragiri Author
  • Nurnita universitas Islam Indragiri Author
  • Khairul Khatimah universitas Islam Indragiri Author
  • Yesti Andini universitas Islam Indragiri Author
  • Muhammad Suratman universitas Islam Indragiri Author
  • Muhammad Bintang Juliawan universitas Islam Indragiri Author
  • Achmad Isya Alfassa universitas Islam Indragiri Author

Keywords:

Employment, Student, Analysis

Abstract

This study analyzes the parental employment of Information Systems students class of 2023 at a higher education institution in Indonesia. With a sample of 63 students, this study aims to identify and describe the types of parental employment and examine the dominant occupations overall and in each class. The data collection method used an online survey distributed to each class.

The results showed that the most dominant occupation was farmer (42.2%), followed by trader (20.3%), civil servant (15.6%), entrepreneur (10.9%), and other occupations (10.9%). Analysis by class revealed that farmers were consistently the dominant occupation in all classes, with the highest number in class A (10 people), followed by class C (9 people), and class B (8 people).

These findings provide important insights into the socio-economic background of Information Systems students and can contribute to the development of more responsive educational policies. This study also emphasizes the importance of the agricultural sector in the context of students' parents' occupation, which may affect students' career orientation and academic achievement in the future.

Downloads

Download data is not yet available.

References

Rahmawati, R., Suyanto, T., & Ridhoi, R. (2019). Pengaruh Status Sosial Ekonomi Orang Tua terhadap Motivasi Belajar dan Prestasi Akademik Mahasiswa. Jurnal Pendidikan: Teori, Penelitian, dan Pengembangan, 4(11), 1534-1543.

Purwanto, A., Asbari, M., Fahlevi, M., Mufid, A., Agistiawati, E., Cahyono, Y., & Suryani, P. (2021). Impact of Work From Home (WFH) on Indonesian Teachers Performance During the Covid-19 Pandemic: An Exploratory Study. International Journal of Advanced Science and Technology, 29(5), 6235-6244.

Wibowo, A. (2018). Pengaruh Latar Belakang Keluarga dan Lingkungan Sosial terhadap Orientasi Karir Mahasiswa. Jurnal Ekonomi dan Bisnis, 21(2), 203-218.

Nugroho, A. D., & Hartati, R. M. (2020). Analisis Hubungan Pekerjaan Orang Tua dengan Pilihan Jurusan dan Aspirasi Karir Mahasiswa. Jurnal Bimbingan Konseling Indonesia, 5(1), 18-23.

Suryani, E., & Ginting, P. (2020). Hubungan antara Latar Belakang Keluarga, Pengalaman Belajar, dan Employability Skill Mahasiswa Perguruan Tinggi di Indonesia. Jurnal Pendidikan Ekonomi dan Bisnis, 8(1), 43-56.

Al Fassa, A. I., & Kesumawati, A. (2020). Segmentation of Karhutla Hotspot Point of Indragiri Hilir Regency 2015 and 2016 using Self Organizing Maps (Soms). In Proceedings Ofthe International Conference on Mathematics and Islam (ICMIs 2018). UIN Mataram Indonesia and ADMAPETA (Asosiasi dosen matematika dan pendidikan/Tadris Matematika), Mataram, Indonesia (pp. 336-341).

Imani, N., Alfassa, A. I., & Yolanda, A. M. (2023). Analisis Cluster Terhadap Indikator Data Sosial Di Provinsi Nusa Tenggara Timur Menggunakan Metode Self Organizing Map (Som). Jurnal Gaussian, 11(3), 458-467.

Alfassa, A. I. (2022). Statistika Kependudukan Untuk Rencana Kebijakan Kependudukan Daerah. DEMOS: Journal of Demography, Ethnography and Social Transformation, 2(2), 76-85.

Alfassa, A. I. (2023). Bayesian Statistics for Study Population Statistics and Demography. Journal of Statistical Methods and Data Science, 1(1), 17-24.

Alfassa, A. I., & Dewi, A. (2024). Communication management on forest and land fires mitigation awareness based on community. In E3S Web of Conferences (Vol. 506, p. 04002). EDP Sciences.

Al Fassa, A. I. (2018). Aplikasi Self Organizing Maps dan Webgis dengan menggunakan R dan QGIS untuk Analisis Kependudukan 100 Negara di Dunia.

Alfassa, A. I., Sudrajat, S., & Marwasta, D. (2023). Development of official statistics models for analysis of population sectoral data in Indragiri Hilir Regency. In E3S Web of Conferences (Vol. 468, p. 06007). EDP Sciences.

Downloads

Published

2024-07-24

Issue

Section

Articles

Most read articles by the same author(s)

<< < 8 9 10 11 12 13 14 > >> 

Similar Articles

You may also start an advanced similarity search for this article.