Analisis Dan Visualisasi Data Kepegawaian Menggunakan Clustering di Badan Penanggulangan Bencana Daerah (BPBD) Kota Surabaya

Putri, Armalia Kusuma and Putri, Winna Dhestyan (2026) Analisis Dan Visualisasi Data Kepegawaian Menggunakan Clustering di Badan Penanggulangan Bencana Daerah (BPBD) Kota Surabaya. Project Report (Praktek Kerja Lapang dan Magang). Fakultas Ilmu Komputer, Surabaya.

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Abstract

The Internship Program (Praktik Kerja Lapangan / PKL) is an essential component of the Merdeka Belajar Kampus Merdeka (MBKM) initiative, which provides students with real-world work experience. This internship was conducted at the Regional Disaster Management Agency (Badan Penanggulangan Bencana Daerah / BPBD) of Surabaya City, focusing on the analysis and visualization of employee data using the Clustering method. The primary issue addressed was the limitation of manually processing employee data via spreadsheets, which hampers the efficiency of data-driven decision-making. Using a Python-based approach and leveraging libraries such as Pandas, Seaborn, and Matplotlib, the project involved data cleaning, analysis of employee attributes (age, education, years of service, and status), and segmentation through the PCA algorithm. The results were presented in the form of visualizations and cluster groupings that are easy to interpret and are expected to support workforce planning, including training, placement, and career development strategies. This project demonstrates that the application of data science in the public sector can improve human resource management efficiency and support more informative and objective decision-making. The outcomes also represent a tangible contribution from students toward strengthening data-driven governance within BPBD Surabaya.

Item Type:

Monograph (Project Report (Praktek Kerja Lapang dan Magang))

Contributors:

Contribution	Contributors	NIDN/NIDK	Email
Thesis advisor	Hindrayani, Kartika Maulida	NIDN0009099205	kartika.maulida.ds@upnjatim.ac.id
Thesis advisor	Wara, Shindi Shella May	NUPTK1850774675230252	shindi.shella.fasilkom@upnjatim.ac.id

Subjects:

Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science

Divisions:

Faculty of Computer Science > Departemen of Data Science

Depositing User:

Armalia Kusuma Putri

Date Deposited:

16 Sep 2026 06:32

Last Modified:

16 Sep 2026 09:22

URI:

https://repository.upnjatim.ac.id/id/eprint/60210