| E-ISSN | : | 3089-9710 |
| Editor-in-Chief | : | Yahya Auliya' Abdillah |
| Accreditation No. | : | - |
| DOI | : | Prefix 10.64595/ijlc by |
| Frequency | : | 2 issues per year, June and December |
| Publisher | : | CV Narasi Khatulistiwa Indonesia |
| Citation & Indexing | : | - |
About the Journal
Khatulistiwa : Journal of Artificial Intelligence is a Journal of Published by The CV Narasi Khatulistiwa Indonesia, Probolinggo, East Java, Indonesia. It publishes biannually on June and December (twice a year). Khatulistiwa : Journal of Artificial Intelligence covers a wide range of topics in the field of Artificial Intelligence (AI). Its focus includes the development of algorithms, machine learning techniques, and AI applications for problem-solving across various sectors. The journal also highlights innovations in big data processing, natural language processing, and knowledge-based intelligent systems. Additionally, it emphasizes ethical considerations and the social impact of AI to promote responsible technological advancements.
Current Issue
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
