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All Journal International Journal of Electrical and Computer Engineering Jurnal Teknologi Terpadu Engineering, Mathematics and Computer Science Journal (EMACS)
Nabiilah, Ghinaa Zain
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics

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Journal : Engineering, Mathematics and Computer Science Journal (EMACS)

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Parking System Application Using a Greedy Algorithm Approach Saputri, Hanis Amalia; Syaputra, William; Charles, Charles; Irawan, Andreas Dwi; Nabiilah, Ghinaa Zain
Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 7 No. 1 (2025): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v7i1.12575

Abstract

Indonesia has recently witnessed a significant increase in the number of automobiles, reaching an estimated 17.2 million units by the end of 2022, according to the Central Statistics Agency (BPS). Extensive ownership and usage of vehicles in public parking areas, including campuses, have created a high demand for parking spaces. However, challenges still exist within the parking system, such as longer search times for available parking spaces and the lack of technological regulation, leading to uncertainty. Our research focuses on addressing these issues by employing a priority-based greedy algorithm for the nearest lift, prioritizing convenience and speed. We utilize an SQL database to store parking data, leveraging its comprehensive features for efficient processing. The result of this research is a website where customers can input their license plate numbers, processed by our algorithm to generate parking tickets, granting access to designated parking areas. The algorithm works by providing parking slot locations from even-numbered floors first; when all even-numbered floors are filled, it will then allocate parking slots on odd numbered floors. The implementation of the greedy algorithm and SQL database has proven to be efficient in the context of the nearest lift in the Binus parking lot, handling a manageable amount of data and prioritizing data processing speed over achieving the optimal solution in all scenarios
Effectiveness Analysis of RoBERTa and DistilBERT in Emotion Classification Task on Social Media Text Data Nabiilah, Ghinaa Zain
Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 7 No. 1 (2025): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v7i1.12618

Abstract

The development of social media provides various benefits in various ways, especially in the dissemination of information and communication. Through social media, users can express their opinions, or even their feelings. In this regard, sometimes users also convey information or opinions according to the user's feelings or emotions. This triggers the impact of aggressive online behavior, including cyberbullying, which triggers unhealthy debates on social media. The development of deep learning models has also been developed in several ways, especially emotion classification. In addition to using deep learning models, the development of classification tasks has also been carried out using transformer architectures, such as BERT. The development of the BERT model continues to be carried out, so this study will analyze and explore the application of BERT model development, such as RoBERTa and DistilBERT. The optimal result of this study is with an accuracy value of 92.69% using the RoBERTa model.
Co-Authors Alam, Islam Nur Charles Charles Hidayat, Muhammad Fadlan Irawan, Andreas Dwi Prasetyo, Simeon Yuda Purwanto, Eko Setyo Saputri, Hanis Amalia Syaputra, William