Vol. 3 No. 1 (2026): June 2026
The fourth edition of Khatulistiwa: Journal of Artificial Intelligence (Vol. 3, No. 1, June 2025) presents five research articles that explore the application of Artificial Intelligence (AI) and machine learning across various fields, including finance, e-commerce, healthcare, agriculture, and meteorology. The topics covered include predicting potential deposit customers using CatBoost, comparing the performance of XGBoost, LightGBM, and CatBoost for customer churn prediction, classifying eye diseases using VGG-19 and TensorFlow, detecting shallot leaf diseases using CNN and SVM, and forecasting rainfall using an Attention-Based LSTM model. These articles represent the contributions and collaborations of researchers from Indonesia, the United States, Algeria, and Morocco in developing innovative AI-based solutions to address real-world challenges across multiple sectors.
Articles
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Predicting Potential Deposit Customers Using CatBoost with Feature Selection and Hyperparameter Optimization
Abstract View: 5,
Pdf Download: 7
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Comparison of XGBoost LightGBM and CatBoost for Online Store Customer Churn Prediction
Abstract View: 8,
Pdf Download: 5
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Eye Disease Classification Using VGG-19 and TensorFlow on Fundus Images
Abstract View: 8,
Pdf Download: 8
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Shallot Leaf Disease Detection Using Convolutional Neural Network and Support Vector Machine
Abstract View: 7,
Pdf Download: 7
