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Implementasi Framework Laravel dalam Pembuatan Website Segitiga Motor dengan Metode Waterfall Dini Nurul Azizah; Luthfi Dika Chandra; Muhammad Galuh Gumelar; Wien Kuntari
Mars : Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer Vol. 2 No. 6 (2024): Desember : Mars : Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/mars.v2i6.539

Abstract

The Segitiga Motor website was developed using the Laravel framework with the SDLC Waterfall model approach to digitize the management of customer data and workshop services. The development process includes stages such as requirements analysis, system design, implementation, testing, and maintenance. Laravel was chosen for its ability to speed up development through reusable components and its organized and flexible structure. The website successfully integrates key features such as online service booking, customer data management, product catalog, and promotions, all effectively. Testing results show that the system works as planned, enhancing operational efficiency and making it easier for customers to access services. For future development, adding features like analytics and integration with digital payment systems could further improve customer experience and satisfaction.    
Design GiggleGate as Desktop Virtual Assistant with Face and Speech Recognition Authentication System Jasmine Aulia Mumtaz; Kinaya Khairunnisa Komariansyah; Wildan Holik; Reza Pratama; Muhammad Galuh Gumelar; Endang Purnama Giri; Gema Parasti Mindara
International Journal of Computer Technology and Science Vol. 1 No. 4 (2024): October: International Journal of Computer Technology and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijcts.v1i4.113

Abstract

In recent years, virtual assistants have become an integral part of everyday life, simplifying routine tasks and allowing users to focus on more important matters. This research aiming to design GiggleGate, a virtual desktop assistant integrated with both face and speech recognition technology to enhance authentication security. The objective is to develop an authentication system that not only verifies user identity but also provides a more intuitive experience and seamless interaction. The research employs a development methodology to create and implement the system, which integrates face recognition via OpenCV and speech recognition via a Python library. The findings indicate that the integration of these technologies enhances security and user experience by offering dual-factor authentication. The system is expected to contribute to more secure and accessible virtual assistant applications, offering both a practical and efficient solution for users. The implications of this study suggest that the combination of face and speech recognition can provide an effective means to protect user privacy and improve the overall functionality of desktop assistants.
Black Box Testing on the Wingpos Website Using the Equivalence Partitioning Technique Nadhifah, Jauza; Muhammad Al Amin; Capriandika Putra Susanto; Muhammad Galuh Gumelar; Anka Luffi Ramdani; Mindara, Gema Parasti; Wicaksono, Aditya
International Journal of Information Engineering and Science Vol. 2 No. 1 (2025): February : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v1i4.128

Abstract

In the digital business environment, web-based Point of Sale (POS) systems play a vital role in supporting transaction processing, inventory management, and operational decision-making. Ensuring the functional reliability of such systems is essential, particularly in critical authentication features that regulate user access. However, undetected functional errors within login and registration modules may disrupt operations, compromise data integrity, and reduce user experience quality. Therefore, this study aims to evaluate the functionality of the Wingpos website, focusing specifically on the login and registration features. The research applies the Black Box Testing approach using the Equivalence Partitioning technique, which enables systematic functional validation by classifying input data into representative valid and invalid partitions without requiring access to source code. The testing process involved designing structured test cases, executing input scenarios, and comparing actual system outputs with expected results. The findings reveal that most authentication processes function in accordance with system specifications, as seven out of ten test scenarios produced expected outcomes. Nevertheless, three discrepancies were identified, including inconsistent error message validation in the login feature and the system’s inability to properly verify invalid email domains during registration. These results indicate that while the system demonstrates general functional reliability, certain validation mechanisms require refinement. In conclusion, the application of Black Box Testing with the Equivalence Partitioning technique proves effective in identifying functional gaps and supporting quality assurance processes in web-based POS systems, particularly in strengthening authentication feature reliability and improving overall system performance
Analisis Sentimen Ulasan Aplikasi HeyJapan di Google Play Store Menggunakan Algoritma NLP Jasmine Aulia Mumtaz; Kinaya Khairunnisa Komariansyah; Wildan Holik; Muhammad Galuh Gumelar; Reza Pratama; Humannisa Rubina Lestari
Pragmatik : Jurnal Rumpun Ilmu Bahasa dan Pendidikan  Vol. 3 No. 3 (2025): Juli: Pragmatik : Jurnal Rumpun Ilmu Bahasa dan Pendidikan
Publisher : Asosiasi Periset Bahasa Sastra Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/pragmatik.v3i3.1801

Abstract

Digital learning applications like HeyJapan are increasingly popular. User reviews on platforms such as Google Play Store contain valuable information on user perceptions and experiences. To process this information systematically, this study employs a Natural Language Processing (NLP) approach to analyze sentiment toward the HeyJapan application. Data was collected using web scraping techniques with Python and the google play scraper library, resulting in 1,000 latest user reviews. The analysis included data collection, preprocessing, sentiment labeling using TextBlob, visualization, modeling with Logistic Regression, and evaluation. After preprocessing, 923 valid reviews were classified into three sentiment categories based on polarity which are positive, neutral, and negative. Results showed 71.4% of reviews positive, 26.1% neutral, and 2.5% negative. Visualizations in pie charts and word clouds provided an overview of user perceptions. Modeling with TF-IDF and Logistic Regression achieved 88% accuracy with the highest f1-score in the positive sentiment category. Evaluation indicates the model is fairly reliable in classifying sentiments, especially for positive and neutral categories, though negative sentiment classification needs improvement. This study shows the NLP approach can evaluate user perceptions of educational applications based on reviews and serve as a basis for improving foreign language learning app quality.