18 papers
A Comparative Analysis of Classical Machine Learning and Deep Learning Approaches for Sentiment Classification on IMDb Movie Reviews
Erma Daniar Safitri, Lia Hana Ichisasmita, Citra Agustin +3
This paper presents a comparative study of classical machine learning and deep learning methods for sentiment classification on the IMDb movie reviews dataset. The machine learning…
Hybrid TF--IDF Logistic Regression and MLP Neural Baseline for Indonesian Three-Class Sentiment Analysis on Social Media Text
Allya Nurul Islami Pasha, Eka Fidiya Putri, Luluk Muthoharoh +2
This paper presents a compact three-class sentiment analysis study for Indonesian social media text. The task is formulated with positive, negative, and neutral outputs derived fro…
A Comparative Analysis of Machine Learning and Deep Learning Models for Tweet Sentiment Classification: A Case Study on the Sentiment140 Dataset
Vita Anggraini, Cintya Bella, Bastian +3
The exponential growth of social media has created an urgent need for automated systems to analyze unstructured public sentiment in real time. This study compares a traditional Log…
Sentiment Analysis and Customer Satisfaction Prediction on E-Commerce Platforms Based on YouTube Comments Using the XGBoost Algorithm
Ridho Benedictus Togi Manik, Muhammad Aqil Ramadhan, Ihsan Maulana Yusuf +3
The exponential expansion of digital commerce in Indonesia has significantly shifted consumer interactions toward video-centric social networks, particularly YouTube. Consequently,…
Sentiment Analysis of Indonesian Spotify Reviews Using Machine Learning and BiLSTM
Uliano Wilyam Purba, Andre Hadiman Rotua Parhusip, Sahid Maulana +3
This paper benchmarks classical machine learning and deep learning approaches for three-class sentiment classification of Indonesian Spotify reviews. Using 100,000 scraped reviews…
A Comparison of Traditional Machine Learning Algorithms and LSTM-Based Deep Learning Models for Email Sentiment Analysis
Virdio Samuel Saragih, Baruna Abirawa, Kartini Lovian Simbolon +3
The rapid growth of electronic communication has necessitated more robust systems for email classification and sentiment detection. This study presents a comparative performance an…
Benchmarking Logistic Regression, SVM, Naive Bayes, and IndoBERT Fine-Tuning for Sentiment Analysis on Indonesian Product Reviews
Nabila Zakiyah Zahra, Salwa Farhanatussaidah, Nasywa Nur Afifah +3
The exponential growth of e-commerce platforms in Indonesia has generated a massive volume of user-generated product reviews. Analyzing the sentiment of these reviews is critical f…
Benchmarking LightGBM and BiLSTM for Sentiment Analysis on Indonesian E-Commerce Reviews
Lidia Natasyah Marpaung, Vania Claresta, Iqfina Haula Halika +3
This study presents a comparative analysis between two primary approaches in Natural Language Processing (NLP): Machine Learning (ML) utilizing the PyCaret AutoML framework, and De…
Sentiment Analysis of Mobile Legends App Reviews Using Machine Learning and LSTM-Based Deep Learning Models
Vira Putri Maharani, Kharisa Harvanny, Daris Samudra +3
This paper compares Machine Learning and LSTM-based Deep Learning methods for sentiment analysis of Mobile Legends app reviews. Using a dataset of 10,000 reviews labeled as positiv…
Enhancing Game Review Sentiment Classification on Steam Platform with Attention-Based BiLSTM
Abit Ahmad Oktarian, Fadhil Fitra Wijaya, Dhafin Razaqa Luthfi +3
This paper investigates sentiment classification of Steam game reviews using an attention-based Bidirectional Long Short-Term Memory (BiLSTM) model. Using a dataset of 50,000 revie…
Sentiment Analysis of AI Adoption in Indonesian Higher Education Using Machine Learning and Transformer-Based Models
Happy Syahrul Ramadhan, Ahmad Sahidin Akbar, Karin Yehezkiel Sinaga +3
This study analyzes Indonesian student opinions on the adoption of artificial intelligence in higher education using two approaches: TF-IDF-based machine learning and Transformer-b…
Classification of Public Opinion on the Free Nutritional Meal Program on YouTube Media Using the LSTM Method
Berliana Enda Putri, Lisa Diani Amelia, Muhammad Zaky Zaiddan +3
Public opinion towards the Free Nutritious Meal Program (MBG) on YouTube social media reflects diverse community responses. This study applies the Long Short-Term Memory (LSTM) met…
Benchmarking PyCaret AutoML Against BiLSTM for Fine-Grained Emotion Classification: A Comparative Study on 20-Class Emotion Detection
Arya Muda Siregar, Arielva Simon Siahaan, Haikal Fransisko Simbolon +3
Fine-grained emotion classification, which identifies specific emotional states such as happiness, anger, sadness, and fear, remains a challenging task in natural language processi…
Comparative Analysis of AutoML and BiLSTM Models for Cyberbullying Detection on Indonesian Instagram Comments
Raihana Adelia Putri, Aisyah Musfirah, Anggi Puspita Ningrum +3
This study compares machine learning and deep learning approaches for cyberbullying detection in Indonesian-language Instagram comments. Using a balanced dataset of 650 comments la…
Benchmarking Logistic Regression, SVM, and LightGBM Against BiLSTM with Attention for Sentiment Analysis on Indonesian Product Reviews
Razin Hafid Hamdi, Ivana Margareth Hutabarat, Hanna Gresia Sinaga +3
Sentiment analysis of product reviews on e-commerce platforms plays a critical role in automatically understanding customer satisfaction and providing actionable insights for selle…
Benchmarking PyCaret AutoML Against IndoBERT Fine-Tuning for Sentiment Analysis on Indonesian IKN Twitter Data
Mutia Alfi Mayzaroh, Dwi Fitria Ningsih, Nindi Destriani +1
This paper benchmarks a classical machine learning approach based on PyCaret AutoML against a deep learning approach based on IndoBERT fine-tuning for binary sentiment analysis of…
Sentiment and Emotion Classification of Indonesian E-Commerce Reviews via Multi-Task BiLSTM and AutoML Benchmarking
Hermawan Manurung, Ibrahim Al-Kahfi, Ahmad Rizqi +1
Indonesian marketplace reviews mix standard vocabulary with slang, regional loanwords, numeric shorthands, and emoji, making lexicon-based sentiment tools unreliable in practice. T…
Pixel Intensity Tracking for Remote Respiratory Monitoring: A Study on Indonesian Subject
Muhammad Yahya Ayyashy Mujahidan, Martin Clinton Tosima Manullang
Respiratory rate is a vital sign indicating various health conditions. Traditional contact-based measurement methods are often uncomfortable, and alternatives like respiratory belt…