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All Journal Griya Journal of Mathematics Education and Application Teknik: Jurnal Ilmu Teknik dan Informatika
Muhammad Iqbal Fahrezzi
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Computer Science & IT Education Mathematics

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Portal rekrutmen berbasis web dengan seleksi transparan metode first come first served Zulfahmi Indra; Nafil Rizq Trianto; Augis Dinanti; Khairany Zuhriyyah Jinan Hsb; Muhammad Iqbal Fahrezzi
Griya Journal of Mathematics Education and Application Vol. 5 No. 4 (2025): Desember 2025
Publisher : Pendidikan Matematika FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/griya.v5i4.945

Abstract

The advancement of information technology has accelerated digital transformation in various sectors, including job vacancy management and distribution systems. Manual registration processes often cause issues such as data duplication, delayed information delivery, and inefficiency. This study aims to design and implement a web-based job vacancy information system that applies the First Come First Served (FCFS) method as the registration and applicant selection mechanism. The system was developed using the Waterfall model, with PHP as the programming language and MySQL as the database management system. System testing focused on functional suitability, usability, and performance efficiency. The results indicate that the system successfully manages registration processes fairly and transparently based on submission order while improving overall efficiency and user experience. This research contributes to the development of an integrated and accessible employment information system that supports digital transformation in workforce management.
Perbandingan Algoritma Greedy dan Dynamic Programming pada Penyelesaian Knapsack Problem untuk Optimasi Pemilihan Barang Hsb, Khairany Zuhriyyah Jinan; Augis Dinanti; Muhammad Iqbal fahrezzi; Arion Pardede; Adidtya Perdana
Teknik: Jurnal Ilmu Teknik dan Informatika Vol. 6 No. 1 (2026): Mei : Teknik: Jurnal Ilmu Teknik dan Informatika
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/teknik.v6i1.1127

Abstract

Optimization problems in computer science often arise when a system must select the best combination from several alternatives under limited resources such as capacity, time, or cost. One commonly used optimization model is the Knapsack Problem, which involves selecting a number of items with specific weights and values to obtain the maximum profit without exceeding the available capacity. This study aims to analyze and compare the performance of the Greedy algorithm and Dynamic Programming in solving the 0–1 Knapsack Problem. The research employs a quantitative experimental approach by implementing both algorithms in a computer program and testing them on several datasets with different sizes. The evaluation parameters include the maximum value obtained and the algorithm execution time. The results show that the Greedy algorithm has faster execution time and more efficient memory usage, but it does not always produce an optimal solution. In contrast, the Dynamic Programming algorithm consistently produces an optimal solution, although it requires greater computational time. Therefore, the choice of algorithm should be adjusted to system requirements, whether prioritizing computational efficiency or optimal solution quality.
Co-Authors Adidtya Perdana, Adidtya Arion Pardede Augis Dinanti Hsb, Khairany Zuhriyyah Jinan Khairany Zuhriyyah Jinan Hsb Nafil Rizq Trianto Zulfahmi Indra, Zulfahmi