Developed by Group 2:
Hammam Jitapsara (2304140050)
Yudhistira Lucky Oktavian (2304140080)
Aisyah Wilavy Zahra (2304140068)
Arif Satria Tama (2304140063)

Supervised by:
M. Faris Al Hakim, S.Pd., M.Cs.

📂 Project GitHub Repository: Pemilih Mahasiswa Terbaik

#Overview

In our final group project, we developed a web-based Decision Support System (DSS) called "Pemilih Mahasiswa Terbaik". The goal of this system is to help organizations and academic staff objectively determine the best students based on multiple criteria. We combined two well-known MCDM (Multi-Criteria Decision Making) methods: Weighted Product (WP) and Simple Additive Weighting (SAW).

This blog post shares how the system works, the decision-making logic behind it, and the technology stack we used.

#How the System Works

The system follows a logical sequence:

1. Data Input: The user inputs student information across six evaluation criteria:

   • Academic Achievement (IQ)

   • Social Contribution (EQ)

   • Self-Development (Attitude)

   • Organizational Involvement (Association)

   • Peer Interaction (Friendship)

   • Time Discipline (Effort Regulation)

2. Normalization: Since the scale of these criteria vary, we normalize the data to make them comparable. For benefit criteria, we divide each value by the maximum. For the single cost criterion (Effort Regulation), we divide the minimum value by the actual value.

3. Dynamic Weighting using WP: The WP method is applied to determine weights for each criterion based on real data. This allows the system to automatically adjust the importance of each criterion, depending on data distribution.

4. Scoring using SAW: The normalized data is combined with the computed weights using SAW to generate a final score for each student.

5. Ranking Output: Students are ranked from highest to lowest score, and the results are shown in a simple table interface. Users can also view the dynamically calculated weights.

#Technologies Used

• Backend: PHP 7.4+

• Frontend: HTML + Tailwind CSS + JavaScript

• Database: MySQL 5.7+

• Server: Apache or Nginx

• Other Tools: Composer (dependency manager)

The system is built with a clean structure where input forms are in form.php, calculations are handled in ranking.php, and data is dynamically fetched from a MySQL database.

#Key Code Snippet

Here’s a simplified overview of how we process ranking:

$mahasiswaData = getMahasiswaData($conn);
$normalizedData = normalizeMatrix($mahasiswaData);
$weights = calculateWPWeights($mahasiswaData);
$rankings = calculateSAWRankings($normalizedData, $weights);

This modular approach improves code readability and reusability, consistent with good software engineering practice.

#Why We Chose WP + SAW

• WP allows dynamic adjustment of weights based on real distributions in the data, which adds objectivity.

• SAW is computationally simple and makes score interpretation straightforward.

Together, they balance flexibility and transparency, making the system robust and understandable.

#Try It or Fork It

We encourage students or educators to fork our repository and adapt it to their own evaluation needs. Whether you’re evaluating scholarship applicants, leadership awards, or internal selections, this system can serve as a solid foundation.

🔗 GitHub: https://github.com/hammamjeunnes/PemilihMahasiswaTerbaik

Thanks for reading! We hope this project inspires others to build meaningful decision support tools in education and beyond.