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All Journal G-Tech : Jurnal Teknologi Terapan
Ana Kurniawati
Universitas Gunadarma, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Energy Engineering

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Sistem Penggajian Berbasis Web untuk Butik Busana Fashion: Implementasi Metode RAD Siti Rokhaila; Ana Kurniawati; Dina Agusten
G-Tech: Jurnal Teknologi Terapan Vol 8 No 2 (2024): G-Tech, Vol. 8 No. 2 April 2024
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/gtech.v8i2.4108

Abstract

Employee salary management is becoming an important aspect in the fashion industry. The current payroll system in Fashion Boutique still uses slow and inefficient manual calculations. Therefore, a website was created to manage employee payroll. This study aims to optimize salary management through a web-based Rapid Application Development (RAD) approach. The RAD method was chosen because it is responsive to rapid business changes. By conducting needs analysis, design, implementation, and testing, an efficient payroll management system integrated with web access was successfully developed. Trials are conducted with black box testing, device testing, desktop browser, and end user. Payroll websites have proven to match user expectations, working well across multiple devices and browsers. The results of this study contribute to improving operational efficiency and accuracy of employee salary management in the context of a dynamic fashion industry, especially in Fashion Fashion Boutiques.
Optimization of Dental Clinic Selection Using Item-Based Collaborative Filtering with Pearson Correlation Daffa Rahman; Ana Kurniawati; Dina Agusten
G-Tech: Jurnal Teknologi Terapan Vol 9 No 3 (2025): G-Tech, Vol. 9 No. 3 July 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i3.7439

Abstract

The advancement of technology in the healthcare sector (e-health) has encouraged dental clinics in Bekasi City to adopt digital systems. However, many clinics have yet to take advantage of this technology. The wide variety of dental clinic options often makes it difficult for users to determine which clinic best suits their needs. This study developed a web-based recommendation system using the Item-Based Collaborative Filtering method and Pearson Correlation calculation. The system recommends clinics based on the similarity of ratings between items, calculated from users’ historical data, and generates predictions using the Weighted Sum algorithm. Recommendations are displayed in table format on the website. The system was developed using PHP and MySQL, with 20 dental clinics in Bekasi City as the research objects. It was tested using Blackbox Testing and User Acceptance Testing (UAT). The MAE evaluation result of 0.28 demonstrates the system's good prediction accuracy, and the SUS score of 80 places it in the "Excellent" category.
Co-Authors Daffa Rahman Dina Agusten Siti Rokhaila