Ayatilah, Maslahatul Kaunaini (2025) EMOTIONAL CHAT CLASSIFICATION WITH LOGISTIC REGRESSION MODELLING (ECC-LRM). Project Report (Praktek Kerja Lapang dan Magang). Fakultas Ilmu Komputer, Surabaya. (Unpublished)
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Abstract
Emotional Chat Classification with Logistic Regression Modelling (ECC-LRM) is a project aimed at developing an emotion classification model for text conversations using Logistic Regression algorithms. This project was undertaken during the Practical Work Experience (PKL) at PT Hacktivate Teknologi Indonesia, a company focused on technological innovation in education. ECC-LRM is designed to help users accurately and efficiently identify and understand emotions in conversations. The project development process includes several stages, from Exploratory Data Analysis, Data Pre-Processing, Feature Extraction, to Modelling and Deployment of the model on the Watsonx.ai platform. The author explores various text preprocessing techniques and feature extraction methods to improve the model's accuracy and performance. The final results indicate that the developed Logistic Regression model can classify emotions in text with satisfactory accuracy. Furthermore, the project compares the effectiveness of the Logistic Regression model with other classification methods to ensure optimal performance. The implementation of the ECC-LRM model is expected to enhance user efficiency and satisfaction in understanding and managing their emotions. This project not only provides practical insights into the development of artificial intelligence-based technology but also enhances the author's technical skills and soft skills through hands-on experience in project development and implementation. Keywords : ECC-LRM, emotion classification, Logistic Regression, Watsonx.ai, Machine Learning, digital platform development, data analysis, artificial intelligence.
| Item Type: | Monograph (Project Report (Praktek Kerja Lapang dan Magang)) | ||||||||
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| Subjects: | Q Science > QA Mathematics > QA76.6 Computer Programming | ||||||||
| Divisions: | Faculty of Computer Science > Departemen of Informatics | ||||||||
| Depositing User: | Maslahatul Kaunaini Ayatilah | ||||||||
| Date Deposited: | 23 Jan 2026 08:37 | ||||||||
| Last Modified: | 23 Jan 2026 08:37 | ||||||||
| URI: | https://repository.upnjatim.ac.id/id/eprint/34722 |
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