Informatika Kelas X Kurikulum Merdeka Bab 2: Algoritma Pencarian | Ngode with Kang Aldi

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Published on Aug 15, 2025 This response is partially generated with the help of AI. It may contain inaccuracies.

Table of Contents

Introduction

This tutorial will guide you through the key concepts of search algorithms, as presented in the video "Informatika Kelas X Kurikulum Merdeka Bab 2: Algoritma Pencarian" by Kang Aldi. Understanding search algorithms is crucial for programming and data management. This tutorial will break down the essential steps to grasp these algorithms effectively.

Step 1: Understanding Search Algorithms

  • Definition: A search algorithm is a method used to locate specific data within a data structure or database.
  • Importance: They are fundamental in computer science for retrieving information efficiently.
  • Types of Search Algorithms:
    • Linear Search: Checks each element in a list sequentially until the desired element is found.
    • Binary Search: Requires a sorted list and divides the search interval in half repeatedly.

Step 2: Implementing Linear Search

  • Concept: Start at the beginning of a list and check each element one by one.

  • Steps:

    1. Start from the first element of the list.
    2. Compare the current element with the target value.
    3. If a match is found, return the index of the element.
    4. If no match is found, move to the next element.
    5. Repeat until the end of the list is reached or the element is found.
  • Example Code:

def linear_search(arr, target):
    for i in range(len(arr)):
        if arr[i] == target:
            return i
    return -1  # Target not found

Step 3: Implementing Binary Search

  • Concept: This algorithm is more efficient than linear search but requires the list to be sorted first.

  • Steps:

    1. Set two pointers: one at the start (low) and one at the end (high) of the list.
    2. Calculate the midpoint of the current list segment.
    3. Compare the midpoint element with the target value.
    4. If it matches, return the midpoint index.
    5. If the target is less than the midpoint, move the high pointer to the midpoint - 1.
    6. If the target is greater, move the low pointer to the midpoint + 1.
    7. Repeat until the pointers meet.
  • Example Code:

def binary_search(arr, target):
    low = 0
    high = len(arr) - 1
    
    while low <= high:
        mid = (low + high) // 2
        if arr[mid] == target:
            return mid
        elif arr[mid] < target:
            low = mid + 1
        else:
            high = mid - 1
    return -1  # Target not found

Step 4: Practical Applications of Search Algorithms

  • Real-World Use Cases:
    • Searching for a contact in a phone book (linear search).
    • Finding a word in a dictionary (binary search).
  • Common Pitfalls:
    • Remember that binary search only works on sorted lists.
    • Ensure to handle cases where the element is not found.

Conclusion

In this tutorial, you learned about search algorithms, including linear and binary search, along with their implementations in Python. Understanding how these algorithms work will enhance your programming skills and efficiency in managing data. As a next step, practice implementing these algorithms with different datasets and explore their performance in various scenarios.