Workshop Analisis Data Menggunakan R Programming Dalam Pemenuhan Kompetensi Mahasiswa Kesehatan Masyarakat Menghadapi Transformasi Digital

https://doi.org/10.53579/segantang.v2i2.196

Authors

  • Hendra D Sitanggang Program Studi Ilmu Kesehatan Masyarakat, Fakultas Kedokteran dan Ilmu Kesehatan, Universitas Jambi
  • Ismi Nurwaqiah Ibnu Program Studi Ilmu Kesehatan Masyarakat, Fakultas Kedokteran dan Ilmu Kesehatan, Universitas Jambi
  • Rina Nofri Enis Bagian Anatomi Fakultas Kedokteran dan Ilmu Kesehatan Universitas Jambi
  • Puspita Sari Program Studi Ilmu Kesehatan Masyarakat, Fakultas Kedokteran dan Ilmu Kesehatan, Universitas Jambi
  • Evy Wisudariani Program Studi Ilmu Kesehatan Masyarakat, Fakultas Kedokteran dan Ilmu Kesehatan, Universitas Jambi

Keywords:

workshop, R Programming, big data, data analysis

Abstract

The development and advancement of technology in the health sector impact the availability of large amounts of data that continue to grow, including unstructured data. The ability to analyze this big data needs to be a concern so that data can be utilized in policymaking. One of the data analysis tools that can be used is R programming. Therefore, this community service aims to increase student competence in data analysis using R Programming through structured training. The target of this activity is students of the Public Health Science Study Program, FKIK Jambi University, totaling 46 students. The community service team delivered the training material. This activity was carried out using the training method, which was carried out for five meetings with a duration of 3 x 45 minutes per meeting. The training material consists of basic concepts of data analysis, introduction to R Programming, data preparation, and data analysis. In this activity, knowledge measurement was also carried out before and after training. The results of community service activities show an increase in the knowledge of teachers and education personnel, where the average pre-test was 34.57 and the post-test was 91.30. This increase was statistically significant using the Wilcoxon test (p<0.001). This activity is hoped to improve students' data analysis skills, especially in using the R programming language.

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Published

30-12-2024