1. Apa Itu COMPUTATIONAL THINKING?

What Is Computational Thinking?

Computational thinking is a way to formulate problems, identify their underlying causes, and plan solutions that are effective, efficient, and as optimal as possible. It is a general problem-solving skill—not programming itself—though it can help people decide when computers or other tools could assist.

Why computational thinking matters

• It supports stronger foundational skills. The presenter cites 2018 PISA results, saying Indonesian students’ average score was 371, compared with an ASEAN average of 413. He argues that improving students’ thinking skills can help strengthen basic skills.
• It underlies other forms of communication and learning. The video describes thinking and reasoning as foundations for speaking and listening, literacy, numeracy, and digital and information literacy.
• It connects with higher-order thinking. The presenter relates it to Bloom’s Taxonomy and skills such as applying, analyzing, evaluating, and creating.
• It is relevant in a technology-driven world. As automation, cyber-physical systems, and AI become more widespread, computational thinking can help people adapt and solve problems.
• It is included in Indonesia’s education curriculum. The presenter says computational thinking is intended to be developed from an early age, including through Informatics education.

What computational thinking involves

Computational thinking trains people to ask questions such as:

• Could a person solve this problem more easily, or could a computer or other tool help?
• Have I encountered a similar problem before, and can I recognize a useful pattern?
• How should I organize a large amount of data to make the problem easier to solve?
• Can I create a general solution that works for different inputs?
• What ordered steps will solve the problem?
• What computational strategy or tools might be useful?
• What constraints, trade-offs, or obstacles need to be considered?

The video highlights four components, abbreviated as ADAP:

• Decomposition: Break a complex problem into smaller parts.
• Abstraction: Focus on the information that matters and set aside irrelevant details.
• Pattern recognition: Find similarities or recurring structures in problems.
• Algorithms: Develop ordered steps for solving a problem.

The presenter says these components will be covered in more detail in a later video.

Everyday examples

• Making chili sauce: If demand grows, consider how to make larger batches faster, perhaps using a blender. Then think about shelf life, packaging, automation, and sales.
• Dealing with mosquitoes: Choose a response suited to the situation. A single mosquito might be swatted; many mosquitoes may call for another solution. An extreme response, like burning down the house, would create worse problems.
• Choosing a route: A map app may recommend the quickest route, but road conditions and comfort may make a slightly longer route preferable. The best choice depends on the constraints and priorities.
• Recipes, concept maps, and data: Computational thinking can help organize steps or information, including when working with spreadsheets or programming.

These examples illustrate that computational thinking helps people choose solutions that fit the problem rather than simply selecting the fastest or most obvious option.

How to develop the skill

The presenter emphasizes that computational thinking requires practice, not just learning a definition. Suggested approaches include:

• Solving problems using practice questions, including puzzles designed to develop computational thinking.
• Analyzing data.
• Using modeling and simulation.
• Practicing programming once the underlying problem-solving approach is understood.
• Working through the sample puzzles shown in the video. These include a color-and-button puzzle, a dam-building task that asks for the quickest arrangement of logs, and an ice-cream pattern puzzle.

Main takeaway

Computational thinking is a foundational, widely applicable approach to problem-solving. It helps people clarify a problem before acting, select an appropriate strategy, and consider whether tools or computation can make the solution more effective and efficient.

The presenter’s guiding idea is: solve the problem first, then write the code if coding is needed.

Speakers and sources featured or referenced

• Sandhika Galih — presenter and narrator.
• PISA — the international student assessment discussed in connection with 2018 results.
• OECD — identified as the organization behind PISA.
• UNESCO — referenced for a diagram about foundational human communication skills.
• Bloom’s Taxonomy — referenced in relation to levels of thinking.
• Indonesia’s Merdeka Curriculum — discussed in connection with computational thinking and Informatics education.
• Bebras — cited as a source of computational-thinking exercises; the video mentions Bebras questions and the Indonesian organization.
• Puzzle sources named in the examples: Canada (“Simon Says”) and Turkey (“Building a Dam”).
• Coding challenge websites named: Codewars, LeetCode, HackerRank, and CodeSignal.