Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Valentina, Putri Eka
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Analisis Penerapan Metode WASPAS untuk Penentuan Pola Belajar Mahasiswa Berdasarkan Gaya Belajar Ester, Ria; Yuniarti, Dian Tri; Valentina, Putri Eka; Kusumah Putra, Faris Maulana
JURNAL FASILKOM Vol. 15 No. 3 (2025): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v15i3.10768

Abstract

Higher education in the digital era requires learning approaches that are able to adapt to individual student characteristics, including differences in learning styles. This study aims to develop a model for assessing students’ learning patterns and to provide more personalized learning recommendations using the Weighted Aggregated Sum Product Assessment (WASPAS) method. The data used are secondary data obtained from 1,000 students with seven learning criteria, namely academic score, course participation, attendance rate, physical activity, emotional engagement, device usage, and feedback score. The WASPAS method is applied through two main stages, namely the calculation of the Weighted Sum Model (WSM) and the Weighted Product Model (WPM), which are then aggregated to produce a composite WASPAS score for each student. Manual calculations are demonstrated using five student samples, while computations for the entire dataset are performed using Python in the Jupyter Notebook environment. The results show that students’ WASPAS scores range from 0.2815 to 0.9914 with a distribution that tends to be normal. Most students fall into the “fair” to “very good” learning pattern categories, while a small proportion are classified as “very high” and “requiring special attention.” Analysis based on visual, auditory, and kinesthetic learning styles indicates differences in average WASPAS scores across groups, supporting the effectiveness of the WASPAS method in integrating multiple learning criteria simultaneously. These findings demonstrate that WASPAS can be used as a decision support tool to map student learning profiles and assist in designing more adaptive, targeted, and personalized learning strategies in higher education
Komparasi Performa REST API Laravel 11 dan CodeIgniter 4 Menggunakan Metode Eksperimental valentina, Putri Eka; Dede Handayani; Surya Rizky Maulana Ibrahim; Nanang, Nanang; Kusumah Putra, Faris Maulana
JURNAL FASILKOM Vol. 16 No. 1 (2026): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v16i1.11274

Abstract

This study evaluates the performance of Laravel 11 and CodeIgniter 4 REST API frameworks using an experimental method with controlled variables. Both frameworks were built with identical CRUD endpoints and stress-tested using Apache JMeter 5.6 at concurrency levels of 100, 500, and 1,000 users, with 10 replications each. Key metrics were response time, throughput (RPS), and server memory usage. Results show CodeIgniter 4 consistently outperforms Laravel 11 in raw speed: 70 ms vs. 100 ms at 100 users; 310 ms vs. 480 ms at 1,000 users — a 35–55% advantage. Throughput ratio reached 2.09:1 in favor of CodeIgniter 4 (1,420 vs. 680 RPS at low load), while memory consumption was 66% lower (10 MB vs. 30 MB per request). Analysis of ORM impact shows Eloquent adds a 24% penalty over Query Builder (385 ms vs. 310 ms for 1,000-record fetches). However, applying route caching, config caching, and OPcache boosted Laravel 11 throughput by 75% (reaching 1,180 RPS) and narrowed response time to 85 ms. These findings provide empirical guidance: CodeIgniter 4 suits lightweight microservices with limited resources, while Laravel 11 is preferable for complex enterprise systems demanding security, maintainability, and team productivity.
Co-Authors Dede Handayani Ester, Ria Kusumah Putra, Faris Maulana nanang nanang Surya Rizky Maulana Ibrahim Yuniarti, Dian Tri