NIK Data Enrichment and Interactive Visualization

Enrich and gain insights from data associated with the Nomor Induk Kependudukan (NIK) system.

  • Schedule

    28 – 30 November 2023

    18.30 – 21.30 (WIB)

  • Online-Interactive Learning

    Via Zoom

  • Investment

    Rp. 1.500.000

Course Summary

In today’s data-driven world, the ability to harness and derive insights from various data sources is a highly sought-after skill. The Nomor Induk Kependudukan (NIK) system in Indonesia serves as a rich source of information about its citizens, and understanding and utilizing this data can yield numerous benefits across diverse domains.

This 3-days workshop is designed to equip participants with the skills and knowledge necessary to enrich and gain insights from data associated with the Nomor Induk Kependudukan (NIK) system, visualize these insights using Plotly, and present interactive visualizations in a dashboard format using Streamlit. NIK is the unique identification number assigned to Indonesian citizens, and this course will focus on leveraging this data for meaningful analysis and visualization.

Learning Outcomes

  • Enrich and get insights from NIK (Nomor Induk Kependudukan)
  • Visualize insights in the form of interactive plots using Plotly
  • Present interactive visualizations in a dashboard using Streamlit


  • Working with Conda Environment
  • Introduction to Python for data science
  • Data manipulation and processing with Python Pandas
  • Introduction to graph and graph terminology
  • Graph types: weighted & Unweighted graph
  • Overview of graph implementation in Python
  • Data pre-processing for graph implementation in Python
  • Graph building and graph visualization
  • Finding optimal routes based on overall costs
  • Finding optimal routes based on scale priority : weighted sum model


This testimonial video is taken after our previous Online Data Science Series: Time Series Analysis for Business Forecasting.


Our learning format is online-interactive, you will feel the interactive experience as if you were present in a physical classroom. You can access the class using your Zoom account on pre-defined dates.


    Zoom recording, course Books (PDF & HTML files), the dataset for practice, reference notes, and working files are accessible through our Learning Management System account.


    Show current and prospective employers of your mastery in computer vision with a signed certificate of completion.


    Be a part of our data-passionate community with 5000+ members and 1000+ alumni.


Workshops in this series are tailored to casual programmers and non-programmers that are taking their first steps into data science. It assumes no prior knowledge or academic background, and attendees will be introduced to the beautiful art of writing R / Python code to produce data visualization and build machine learning models. The workshop has a gentle learning slope that is designed with non-technical professionals and academics in mind.

Yes, you can still attend the workshop as it is a beginner-friendly workshop.

Our system will send you an email containing a link and details to join a Google Classroom.

Online learning will be conducted via Zoom.us, Link to join the Zoom Class will be announced via Google Classroom.

Learning materials can be obtain via Google Classroom

Yes, you will receive a certificate of completion.


Diva Kartika

Diva is a Data Science Instructor at Algoritma, known for her diverse expertise and contributions to the field. Graduating with a degree in Physics from the University of Indonesia, she combines academic rigor with four years of experience in Python for Data Science. Diva strongly believes that effective data visualization is the key to connecting people with data, a conviction that has driven her to create data visualization materials for prestigious organizations like Bank Indonesia and Komisi Pemilihan Umum.

In addition to her instructional role, Diva’s impact extends to practical tools. She has developed a Nomor Induk Kependudukan (NIK) data enrichment tool, offered as a Python package for everyone to utilize.