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Manel Velasco - IEEE Xplore Author Profile
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Manel Velasco

Also published under: M. Velasco

Publications
74
Citations
1,191
Publications by Year
19992025
Co-Authors:
Show All Co-Authors (50)
Image of author Manel Velasco

Manel Velasco

Also published under: M. Velasco

Affiliation

Automatic Control Department
Universitat Politècnica de Catalunya
Barcelona, Spain

Publication Topics

Biography

Manel Velasco received the maritime engineering degree and the Ph.D. degree in automatic control from the Technical University of Catalonia, Barcelona, Spain, in 1999 and 2006, respectively.,Since 2002, he has been an Assistant Professor in the Department of Automatic Control at the Technical University of Catalonia. He has been involved in research on artificial intelligence from 1999 to 2002 and, since 2000, on the impact of real-time systems on control systems. His research interests include artificial intelligence, real-time control systems, and collaborative control systems, especially on redundant controllers and multiple controllers with self-interacting systems.(Based on document published on 20 May 2008).
Publications
74
Citations
1,191
Publications by Year
19992025
Co-Authors:
Show All Co-Authors (50)
Author's Published Works

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Detection of Depression on Social Media X With FastText Feature Expansion Using Hybrid Deep Learning CNN-GRU

Wahyu Nata Mahendra;Erwin Budi Setiawan

2025 International Conference on Advancement in Data Science, E-learning and Information System (ICADEIS)
Year: 2025 | Conference Paper |
Depression is a mental illness that is experienced by many people in the world. Depression can have serious repercussions such as suicide if not treated early. Therefore, it is important to conduct early detection to provide mental support and appropriate treatment. Detection can be done through one way, namely identifying posts on social media. Thus, this study aims to detect depression through I...Show More

Detection of Depression on Social Media X With FastText Feature Expansion Using Hybrid Deep Learning CNN-GRU

Wahyu Nata Mahendra;Erwin Budi Setiawan

Year: 2025 | Conference Paper |

Semantic Segmentation of Land Cover in Multisource Aerial Imagery Using U-Net

Sayid Rayhan Mulachela;Erwin Budi Setiawan;Gamma Kosala

2025 International Conference on Advancement in Data Science, E-learning and Information System (ICADEIS)
Year: 2025 | Conference Paper |
Accurate land cover segmentation in aerial imagery is vital for environmental monitoring and greenhouse gas (GHG) emissions assessment. This study applies the U-Net model for semantic segmentation of land cover types, including buildings, forests, water bodies, and roads, to analyze their impact on GHG emissions. Using the LandCover.ai dataset (1,200 images) and a supplementary dataset from Java, ...Show More

Semantic Segmentation of Land Cover in Multisource Aerial Imagery Using U-Net

Sayid Rayhan Mulachela;Erwin Budi Setiawan;Gamma Kosala

Year: 2025 | Conference Paper |

Optimizing Learning Rates and Feature Expansion with FastText in Hybrid CNN-BiGRU for Indonesian Cyberbullying Detection on X

Rexcel Pabian;Erwin Budi Setiawan

2025 International Conference on Advancement in Data Science, E-learning and Information System (ICADEIS)
Year: 2025 | Conference Paper |
Cyberbullying is often defined as any behavior carried out by an individual or group via social networks that includes negative, intimidating, or demeaning messages, causing discomfort to others. Cyberbullying has a harmful impact on the psychological well-being of its victims. The context-sensitive nature of tweets presents challenges in interpreting message content, particularly in languages suc...Show More

Optimizing Learning Rates and Feature Expansion with FastText in Hybrid CNN-BiGRU for Indonesian Cyberbullying Detection on X

Rexcel Pabian;Erwin Budi Setiawan

Year: 2025 | Conference Paper |

Depression Detection Using Hybrid Model BiLSTM – CNN with Glove as Feature Expansion in X

Bintan Dinar Artamevia;Erwin Budi Setiawan

2025 International Conference on Advancement in Data Science, E-learning and Information System (ICADEIS)
Year: 2025 | Conference Paper |
Depression is a significant global health issue, with increasing prevalence among various age groups, especially severed by the COVID-19 pandemic. Early detection of depression is crucial for effective intervention because of its traditional methods may be time-consuming. This study proposes a hybrid deep learning model, BiLSTM-CNN, combined with GloVe word embeddings and TF-IDF feature extraction...Show More

Depression Detection Using Hybrid Model BiLSTM – CNN with Glove as Feature Expansion in X

Bintan Dinar Artamevia;Erwin Budi Setiawan

Year: 2025 | Conference Paper |

Sentiment Analysis on 2024 Regional Elections using Hybrid CNN-SVM with Semantic Features and Word2Vec

Syahbilla Putri Andinny;Erwin Budi Setiawan

2025 International Conference on Advancement in Data Science, E-learning and Information System (ICADEIS)
Year: 2025 | Conference Paper |
Regional Head Election is a political agenda held every five years. Everyone has their point of view on assessing the candidates. These political conversations often appear on platform X, a social media to exchange information, responses, comments, and even emotions. These public expressions can be classified into positive, negative, and neutral sentiments. This political phenomenon is the object ...Show More

Sentiment Analysis on 2024 Regional Elections using Hybrid CNN-SVM with Semantic Features and Word2Vec

Syahbilla Putri Andinny;Erwin Budi Setiawan

Year: 2025 | Conference Paper |

Machine Learning Method for Carbon Stock Classification with Drone and GEE Data

Mohammad Daffa Setiawan;Erwin Budi Setiawan

2025 International Conference on Advancement in Data Science, E-learning and Information System (ICADEIS)
Year: 2025 | Conference Paper |
Accurately classifying carbon stock is essential for tackling climate change, as it helps improve forest management and carbon storage efforts. However, traditional measurement methods are often costly, time-consuming, and require extensive fieldwork. To address these challenges, remote sensing combined with machine learning offers a more efficient and scalable solution. This study explores the us...Show More

Machine Learning Method for Carbon Stock Classification with Drone and GEE Data

Mohammad Daffa Setiawan;Erwin Budi Setiawan

Year: 2025 | Conference Paper |

Parameter Optimization for Long Short-Term Memory (LSTM) and Bi-LSTM in Netflix Recommendation System

Mohamad Irfan Nafiyanto;Erwin Budi Setiawan

2024 International Conference on Intelligent Cybernetics Technology & Applications (ICICyTA)
Year: 2024 | Conference Paper |
Watching movies is a popular activity enjoyed by many individuals. Netflix is a leading entertainment platform that offers a vast selection of movies. This research aims to enhance the recommendation system by integrating Content-Based Filtering (CB) with Long Short-Term Memory (LSTM) and Bidirectional Long Short-Term Memory (Bi-LSTM) to assist users in discovering movies that align with their pre...Show More

Parameter Optimization for Long Short-Term Memory (LSTM) and Bi-LSTM in Netflix Recommendation System

Mohamad Irfan Nafiyanto;Erwin Budi Setiawan

Year: 2024 | Conference Paper |

Hybrid Deep Learning CNN and BiLSTM with FastText as Feature Expansion for Sentiment Analysis in President Election 2024

Yunolva Anis Ramaziyah;Erwin Budi Setiawan

2024 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT)
Year: 2024 | Conference Paper |
Twitter, now X is a highly influential social media platform in shaping public sentiment, particularly during the 2024 Indonesian Presidential Election. Sentiment analysis research has been implemented in various topics using deep learning and hybrid deep learning methods, which include feature expansion and optimization techniques. This study aims to develop a sentiment analysis system by leverag...Show More

Hybrid Deep Learning CNN and BiLSTM with FastText as Feature Expansion for Sentiment Analysis in President Election 2024

Yunolva Anis Ramaziyah;Erwin Budi Setiawan

Year: 2024 | Conference Paper |

Convolutional Neural Network (CNN) with Bat Algorithm Optimization and Word2Vec Feature Expansion for Information Credibility Detection on Social Media X

Muhammad Faqih Madani;Erwin Budi Setiawan

2024 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT)
Year: 2024 | Conference Paper |
X is one of the most popular social media platforms for rapidly disseminating information. However, not all information circulating on X is credible; there are hoaxes and rumors, especially during election periods when many bot and buzzer accounts spread information. Therefore, there is a need for an information credibility detection model on X. This research proposes an information credibility de...Show More

Convolutional Neural Network (CNN) with Bat Algorithm Optimization and Word2Vec Feature Expansion for Information Credibility Detection on Social Media X

Muhammad Faqih Madani;Erwin Budi Setiawan

Year: 2024 | Conference Paper |

Gated Recurrent Unit (GRU) for Information Credibility Detection on Social Media X with GloVe Feature Expansion and Artificial Bee Colony (ABC) Optimization

Echie Talitha Dielizal;Erwin Budi Setiawan

2024 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT)
Year: 2024 | Conference Paper |
The rapidly growing social media platform X as one of the most popular platforms presents new challenges for its users. The lack of supervision and control over the content shared on this platform raises serious problems, one of which is related to the credibility of information. The credibility of information on social media is a crucial aspect that needs to be considered to assess the level of u...Show More

Gated Recurrent Unit (GRU) for Information Credibility Detection on Social Media X with GloVe Feature Expansion and Artificial Bee Colony (ABC) Optimization

Echie Talitha Dielizal;Erwin Budi Setiawan

Year: 2024 | Conference Paper |

Information Credibility Detection on Social Media X Using Bi-GRU with GloVe and Firefly Algorithm

Firmanesa Salwaerdya Syalaisha Purwanto;Erwin Budi Setiawan

2024 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT)
Year: 2024 | Conference Paper |
In this digital era, a lot of information is scattered, and its quality cannot always be guaranteed to be credible and reliable. During the general election in Indonesia, which was widely discussed on Social Media X, people needed to understand and discern whether the information they encountered was true or a hoax. Therefore, this research developed an information credibility detection system tha...Show More

Information Credibility Detection on Social Media X Using Bi-GRU with GloVe and Firefly Algorithm

Firmanesa Salwaerdya Syalaisha Purwanto;Erwin Budi Setiawan

Year: 2024 | Conference Paper |

Tourism Destination Recommendation System on Social Media X (Twitter) with Content-Based Filtering (CBF) and Gated Recurrent Unit (GRU) Approach

Fadil Faithul Azhan;Erwin Budi Setiawan

2024 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT)
Year: 2024 | Conference Paper |
Along with the growth of the tourism sector in the city of Bandung, challenges have emerged within the community. People often struggle to find tourist destinations that align with their preferences. One way the community seeks information about tourist destinations is by utilizing social media platform X (Twitter). However, information about a tourist destination obtained from Twitter is consider...Show More

Tourism Destination Recommendation System on Social Media X (Twitter) with Content-Based Filtering (CBF) and Gated Recurrent Unit (GRU) Approach

Fadil Faithul Azhan;Erwin Budi Setiawan

Year: 2024 | Conference Paper |

Detection and Classification of Hate Speech on Twitter Using Convolutional Neural Network (CNN)

Muhammad Rafi Yanaputeranto;Erwin Budi Setiawan

2024 International Conference on Data Science and Its Applications (ICoDSA)
Year: 2024 | Conference Paper |
Hate speech is any form of communication that attacks a person or group based on attributes such as race, religion, ethnicity, gender, sexual orientation, nationality, or other attributes. It can be verbal, written, or nonverbal. Hate speech can be dangerous because it can lead to violence, discrimination, and social exclusion for certain demographics of people. Social media platforms have become ...Show More

Detection and Classification of Hate Speech on Twitter Using Convolutional Neural Network (CNN)

Muhammad Rafi Yanaputeranto;Erwin Budi Setiawan

Year: 2024 | Conference Paper |

Detection and Classification of Hate Speech on Twitter Using Convolutional Neural Network (CNN)

Muhammad Rafi Yanaputeranto;Erwin Budi Setiawan

2024 International Conference on Data Science and Its Applications (ICoDSA)
Year: 2024 | Conference Paper |
Hate speech is any form of communication that attacks a person or group based on attributes such as race, religion, ethnicity, gender, sexual orientation, nationality, or other attributes. It can be verbal, written, or nonverbal. Hate speech can be dangerous because it can lead to violence, discrimination, and social exclusion for certain demographics of people. Social media platforms have become ...Show More

Detection and Classification of Hate Speech on Twitter Using Convolutional Neural Network (CNN)

Muhammad Rafi Yanaputeranto;Erwin Budi Setiawan

Year: 2024 | Conference Paper |

Adam and AdamW Optimization Algorithm Application on BERT Model for Hate Speech Detection on Twitter

Putri Nabila;Erwin Budi Setiawan

2024 International Conference on Data Science and Its Applications (ICoDSA)
Year: 2024 | Conference Paper |
Cited by: Papers (5)
Twitter is one of the social media platforms used to channel user's opinions and it is common for users to misuse this feature to express hate speech. Hate speech, intentional or unintentional, can trigger conflicts, especially on social media platforms with a large user base like Twitter, where hate speech can easily spread and reach its targets. Therefore, a system is needed to detect hate speec...Show More

Adam and AdamW Optimization Algorithm Application on BERT Model for Hate Speech Detection on Twitter

Putri Nabila;Erwin Budi Setiawan

Year: 2024 | Conference Paper |

Cyberbullying Detection on Twitter using Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU)

Nur Wakhidah Fitri Amalia;Erwin Budi Setiawan

2023 International Conference on Artificial Intelligence Robotics, Signal and Image Processing (AIRoSIP)
Year: 2023 | Conference Paper |
Social media sites, most notably Twitter, have become active centers of community participation, knowledge sharing, and communication in the modern digital era. However, this initial expansion has been followed by an alarming rise in cyberbullying, a ubiquitous problem. Cyberbullying is a broad term that refers to various harmful actions that take place online, such as aggressive bullying, harassm...Show More

Cyberbullying Detection on Twitter using Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU)

Nur Wakhidah Fitri Amalia;Erwin Budi Setiawan

Year: 2023 | Conference Paper |

Feature Expansion with GloVe for Hate Speech Detection Using Convolutional Neural Network (CNN) and Long Short-term Memory (LSTM) Methods on Twitter

Muh. Fachrul Hidayat;Erwin Budi Setiawan

2023 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT)
Year: 2023 | Conference Paper |
Hate speech is unwanted behavior that aims to attack individuals or groups. The spread of hate speech can be found on social media, one of which is on the Twitter platform. This problem can be solved by classifying hate speech. This research proposes to build a hybrid model of hate speech detection using three deep learning models CNN (Convolutional Neural Network), LSTM (Long-Short Term Memory), ...Show More

Feature Expansion with GloVe for Hate Speech Detection Using Convolutional Neural Network (CNN) and Long Short-term Memory (LSTM) Methods on Twitter

Muh. Fachrul Hidayat;Erwin Budi Setiawan

Year: 2023 | Conference Paper |

Sentiment Analysis of Twitter Data on Bank Central Asia Stocks (BBCA) Using RNN and CNN Model with GloVe Feature Expansion

Muhammad Kamil Hasan;Erwin Budi Setiawan

2023 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT)
Year: 2023 | Conference Paper |
Cited by: Papers (3)
Since the Covid-19 pandemic in recent years, investing in stocks has become one of the things that people have grown more interested in. Factors that can affect stock price movements, including corporate policies and public opinion regarding the company, including general services. These issues frequently discussed on social media. In order to determine how much of an impact sentiment had on the f...Show More

Sentiment Analysis of Twitter Data on Bank Central Asia Stocks (BBCA) Using RNN and CNN Model with GloVe Feature Expansion

Muhammad Kamil Hasan;Erwin Budi Setiawan

Year: 2023 | Conference Paper |

Hate Speech Detection using CNN and BiGRU with Attention Mechanism on Twitter

Qomarudin Sifak;Erwin Budi Setiawan

2023 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT)
Year: 2023 | Conference Paper |
Indonesia is the country that leads the most use of social media in Asia. Twitter is one of the most popular social media platforms in Indonesia. Twitter is a social media that is typically used for opinion exchange, criticism, and storytelling. This is frequently abused by Internet users, including the dissemination of hate speech directed at an individual or groups. Therefore, the aim of this re...Show More

Hate Speech Detection using CNN and BiGRU with Attention Mechanism on Twitter

Qomarudin Sifak;Erwin Budi Setiawan

Year: 2023 | Conference Paper |

Topic Classification Using the Long Short-Term Memory (LSTM) Method with FastText Feature Expansion on Twitter

Bella Adriani Putri;Erwin Budi Setiawan

2023 International Conference on Data Science and Its Applications (ICoDSA)
Year: 2023 | Conference Paper |
Twitter serves as a social network where people can connect by sending short messages, known as tweets. The limited character count often leads to variations in wording, making it challenging to understand tweets without proper classification. In this research, feature expansion is employed to solve these issues. The main goal of this research is to evaluate the impact of FastText feature expansio...Show More

Topic Classification Using the Long Short-Term Memory (LSTM) Method with FastText Feature Expansion on Twitter

Bella Adriani Putri;Erwin Budi Setiawan

Year: 2023 | Conference Paper |

The Influence of Sentiment on the Movement of Bank BCA (BBCA) Shares with the CNN-GRU Classification Model and Feature Expansion with GloVe

Muhammad Fauzan Avidiansyah;Erwin Budi Setiawan

2023 International Conference on Data Science and Its Applications (ICoDSA)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
This study examines the influence of sentiment on the movement of Bank BCA (BBCA) shares using a Convolutional Neural Network-Gated Recurrent Unit (CNNGRU) classification model and feature expansion with GloVe. The research reveals a strong positive correlation coefficient of 0.76 for positive sentiment and 0.7 for negative sentiment, as determined through the Spearman Rank correlation test. Addit...Show More

The Influence of Sentiment on the Movement of Bank BCA (BBCA) Shares with the CNN-GRU Classification Model and Feature Expansion with GloVe

Muhammad Fauzan Avidiansyah;Erwin Budi Setiawan

Year: 2023 | Conference Paper |

Feature Expansion Using GloVe for Hate Speech Detection using Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) Method in Twitter

Vincent Williams Jonathan;Erwin Budi Setiawan

2023 International Conference on Data Science and Its Applications (ICoDSA)
Year: 2023 | Conference Paper |
In this day and age, people have easy access to social media, allowing them the freedom to express their opinions. Consequently, hate speech against individuals or groups can be easily found on social media platforms. This paper proposes a system to classify hate speech in Indonesian language tweets. Three distinct deep learning techniques were employed: Convolutional Neural Network (CNN), Recurre...Show More

Feature Expansion Using GloVe for Hate Speech Detection using Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) Method in Twitter

Vincent Williams Jonathan;Erwin Budi Setiawan

Year: 2023 | Conference Paper |

Aspect Based Sentiment Analysis Using Recurrent Neural Networks (RNN) on Social Media Twitter

Muhammad Afryan Saputra;Erwin Budi Setiawan

2023 International Conference on Data Science and Its Applications (ICoDSA)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
One of the social media platforms that has seen the most success in Indonesia is Twitter. Because of the enormous number of users and the intensity with which it is utilized, Twitter may also be used to perform sentiment analysis to search for information relating to a product or topic. On Twitter, movie reviews are consistently one of the most popular topics of conversation. Because everyone’s th...Show More

Aspect Based Sentiment Analysis Using Recurrent Neural Networks (RNN) on Social Media Twitter

Muhammad Afryan Saputra;Erwin Budi Setiawan

Year: 2023 | Conference Paper |

Hoax Detection in Social Media using Bidirectional Long Short-Term Memory (Bi-LSTM) and 1 Dimensional-Convolutional Neural Network (1D-CNN) Methods

Arvinda Dwi Safira;Erwin Budi Setiawan

2023 11th International Conference on Information and Communication Technology (ICoICT)
Year: 2023 | Conference Paper |
Cited by: Papers (3)
Technology development facilitates the dissemination of information and news from various media, especially on social media. The news spread on social media is not necessarily the truth, and it could cause many fake news or hoaxes to spread and mislead the public. The number of hoaxes circulating on social media confuses readers in understanding the truth of information. Several models for detecti...Show More

Hoax Detection in Social Media using Bidirectional Long Short-Term Memory (Bi-LSTM) and 1 Dimensional-Convolutional Neural Network (1D-CNN) Methods

Arvinda Dwi Safira;Erwin Budi Setiawan

Year: 2023 | Conference Paper |

Hoax Detection on Social Media with Convolutional Neural Network (CNN) and Support Vector Machine (SVM)

Manuel Benedict;Erwin Budi Setiawan

2023 11th International Conference on Information and Communication Technology (ICoICT)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Hoax news has long been a problem for society that is quite worrying because receiving hoax news can change a person's point of view to something that is not good, the impact of which is detrimental to many individuals and groups of people. Machine learning and deep learning can be implemented to detect hoax news. Examples of methods used in previous studies are SVM (Support Vector Machine) and CN...Show More

Hoax Detection on Social Media with Convolutional Neural Network (CNN) and Support Vector Machine (SVM)

Manuel Benedict;Erwin Budi Setiawan

Year: 2023 | Conference Paper |

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