Conference Program
Conference Program Agenda (29 – 30 November 2024)
The location of event on the 29 November will be on Pamandengan 4 (8th Floor) and the location of event on 30 November 2024 will be on Trajumas (2nd Floor). The Dinner will be held on Samazana Resto.
| Day, Date, Room | Parallel | Time | Paper Id | Paper Title |
| Friday, 11/29/2024,
Room: Pamandengan 4 (8th Floor) |
Session 1 | 11.00-11.15 | 26 | Insights and Recommendations for Earthquake Logistics in Indonesia: Analyzing Twitter (X) Data |
| 11.15-11.30 | 20 | Explainable Edge AI for Transparent and Accessible Telemedicine Diagnostics | ||
| 11.30-11.45 | 87 | The Effect of Feature Selection Based on CatBoost, LIME, SHAP, and Random Forest in Identifying the Risk of Violence Against Women | ||
| 11.45-12.00 | 14 | Exploring The Data Balance Effect: Artificial Neural Network Predictions for Rodent Tuber’s Liquid Chromatography Mass Spectrometry Dataset | ||
| Session 2 | 13.00-13.15 | 27 | Machine Learning Models for Early Prediction of Student Success and Dropout in Higher Education | |
| 13.15-13.30 | 33 | PREDICTING STOCK PRICE MOVEMENTS USING THE RNN-MGU MODEL | ||
| 13.30-13.45 | 36 | Comparison of Decision Tree with K-Nearest Neighbor in Binary Particle Swarm Optimization Algorithms for Diagnosis of Parkinson’s Disease | ||
| 13.45-14.00 | 38 | Extractive Indonesian Automated Text Summarization with IndoBERT and One-dimensional Convolutional Neural Network | ||
| 14.00-14.15 | 40 | UPGRADING CREDIT SCORING ASSESSMENT IN BANKING USING ARTIFICIAL INTELLIGENCE | ||
| 14.15-14.30 | 51 | Efficiency Analysis of AI Model Compression for Edge Teledermatology | ||
| 14.30-14.45 | 52 | Enhancing Service Coupling in Microservice Architecture: Strategies and Design Characteristics | ||
| 14.45-15.00 | 53 | Prediction and Correlation Modeling Between Global Commodity Prices and Stock Prices in the Agribusiness Sector Using the Ensemble Learning Approach | ||
| Session
3 |
15.15-15.30 | 57 | A Recommender System for University Libraries: Leveraging Book Loan Records with Alternating Least Squares (ALS) | |
| 15.30-15.45 | 58 | Reduction of NPL (Non-Performing Loan) rate performance using machine learning: Bank XYZ case study | ||
| 15.45-16.00 | 69 | A Model of Selecting Communities in a Citation Network for Paper Recommendation | ||
| 16.00-16.15 | 71 | Forecasting Household Electrical Energy Consumption Using Hybrid XGBoost and Multi-Layer Perceptron | ||
| 16.15-16.30 | 72 | Innovative Transfer Learning Technique for Brain Tumor Diagnosis in Medical Resonance Imaging | ||
| 16.30-16.45 | 74 | Use of CNN in Diagnosing Banana Leaf Diseases An Agricultural Technology-Based Solution | ||
| 16.45-17.00 | 75 | News Media Body of Knowledge (NEWSBOK) Analysis and Future Direction | ||
| 17.00-17.15 | 77 | Artificial Intelligence Implementation in Fraud Detection for financial Due Diligence Project Financing in Indonesia Company | ||
| 17.15-17.30 | 79 | Optimization Of Tourism Recommendation System Using Item-Based Collaborative Filtering Algorithm (Case Study Wonosobo Regency) | ||
| 17.30-17.45 | 82 | Tetris Image Detection: A Study on Convolutional Neural Networks for Game Piece Recognition | ||
| 17.45-18.00 | 83 | Gender-Based Analysis of Heart Disease Prediction Using Binary Logistic Regression | ||
|
Saturday, 11/30/2024, Room: Trajumas (2nd Floor) |
Session
4 |
10.30-10.45 | 89 | Modeling Students’ Course Performance Based on Online Learning Engagement Using Graph Analysis Model |
| 10.45-11.00 | 92 | Evaluating the Performance of Long Short-Term Memory (LSTM) Model Variants: LSTM, Bidirectional-LSTM, Gated Recurrent Unit, Attention-LSTM, Hierarchical-LSTM, and Residual-LSTM using Traditional Music Audio Dataset | ||
| 11.00-11.15 | 96 | Electroencephalography (EEG) Signal Identification using Wavelet Transform and Convolutional Neural Network (CNN) Algorithm for Schizophrenia | ||
| 11.15-11.30 | 104 | Deep Learning and Explainable AI for Accurate and Interpretable Software Defect Prediction | ||
| 11.30-11.45 | 106 | Machine Learning Techniques Applied to Reduce the Risk of Default: A Case Study | ||
| 11.45-12.00 | 108 | Use of Convolutional Neural Network (CNN) with EfficientNet Model for Disease Detection in Apple Leaves | ||
| Session
5 |
13.00-13.15 | 110 | Deep Learning for Classification of Roasted Coffee Beans in Mount Puntang Coffee Production | |
| 13.15-13.30 | 111 | Development Model Software Defect Prediction using Ensemble Learning and Stacking Classifier |