Norma Latif Fitriyani

Assistant Professor

Sejong University

South Korea

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About

Norma Latif Fitriyani is an Assistant Professor at Sejong University in South Korea. Her research interests include facial emotion recognition, diabetes prediction, fake news detection, and cardiovascular disease prediction. She has contributed to advancements in composting technologies and has worked on improving credit card fraud detection and cryptocurrency price forecasting through innovative machine learning models. Additionally, she explores natural language processing applications in discussions surrounding the circular economy and health diagnostics.

Articles (20)

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2025

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2022

Collaborators (4)

Muhammad Syafrudin

Assistant Professor

Sejong University

SOUTH KOREA

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Jongtae Rhee

Dongguk University

SOUTH KOREA

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Dursun Aydin

University of Wisconsin-Madison

UNITED STATES

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Filip Benes

VSB - Technical University of Ostrava

CZECH REPUBLIC

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Norma Latif Fitriyani

Research Interests

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About

Articles (20)

A multi-scale simplicial transformer with graph attention for facial emotion recognition

Tab transformer with meta-ensemble learning approaches for enhanced diabetes prediction

Harnessing interpretable novel combination of GloVe embedding with deep CNN-BiLSTM neural network for fake news detection

A Novel Approach Utilizing Bagging, Histogram Gradient Boosting, and Advanced Feature Selection for Predicting the Onset of Cardiovascular Diseases

Advancements in Composting Technologies for Efficient Soil Remediation of Polycyclic Aromatic Hydrocarbons (PAHs): A Mini Review

Enhanced Credit Card Fraud Detection Using Deep Hybrid CLST Model

Enhanced Interpretable Forecasting of Cryptocurrency Prices Using Autoencoder Features and a Hybrid CNN-LSTM Model

Tweeting Circular Economy: Unveiling Current Discourse Through Natural Language Processing

Improving thyroid disorder diagnosis via innovative stacking ensemble learning model

Human pose estimation in physiotherapy fitness exercise correction using novel transfer learning approach

Brain Pathology Classification of MR Images Using Machine Learning Techniques

Identifying Factors to Develop and Validate Social Vulnerability to Floods in Malaysia: A Systematic Review Study

Performance Analysis and Assessment of Type 2 Diabetes Screening Scores in Patients with Non-Alcoholic Fatty Liver Disease

Energy Usage Forecasting Model Based on Long Short-Term Memory (LSTM) and eXplainable Artificial Intelligence (XAI)

Utilizing Random Forest with iForest-Based Outlier Detection and SMOTE to Detect Movement and Direction of RFID Tags

Optimisation of Knowledge Management (KM) with Machine Learning (ML) Enabled

Performance Analysis of Classification and Detection for PV Panel Motion Blur Images Based on Deblurring and Deep Learning Techniques

CRAS-YOLO: A Novel Multi-Category Vessel Detection and Classification Model Based on YOLOv5s Algorithm

Drought Analysis Based on Standardized Precipitation Evapotranspiration Index and Standardized Precipitation Index in Sarawak, Malaysia

Retinal Nerve Fiber Layer Analysis Using Deep Learning to Improve Glaucoma Detection in Eye Disease Assessment

Collaborators (4)

Muhammad Syafrudin

Jongtae Rhee

Dursun Aydin

Filip Benes

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