Pengembangan dan Analisis Metode Hybrid Deep Learning (CNN-MLP dan CNN-LSTM) untuk Peningkatan Akurasi Deteksi Serangan Man In The Middle (MitM) = Development and Analysis of Hybrid Deep Learning (CNN-MLP and CNN-LSTM) Methods to Improve Man in the Middle Detection Accuracy

Pengembangan Model Prediksi Massa Ikan Berdasarkan Gambar dan Video Menggunakan Yolov8 dan Regression Model = Model Development for Predicting Fish Mass Based on Images and Videos Using YOLOv8 and Regression Model

Perbandingan Model Deep Learning dan Model Machine Learning dalam Kasus Analisis Sentimen pada Ulasan Pengguna Traveloka = Comparison of Deep Learning and Machine Learning Models in the Case of Sentiment Analysis of Traveloka User Reviews

Rancang Bangun Sistem Pendeteksi Komponen Struk Belanja Menggunakan Algoritma Deep Learning YOLOv5, Faster R-CNN, dan RetinaNet = Development of a Shopping Receipt Component Detection System using the Deep Learning YOLOv5 Algorithm, Faster R-CNN, and RetinaNet

Hibrida Model BERT dan Deep Learning untuk Analisis Sentimen Bahasa Indonesia - Studi Kasus Sentimen Pengguna Media Sosial terkait Pilpres 2024 = The Hybrid of BERT and Deep Learning Models for Indonesian Sentiment Analysis - A Case Study of Social Media User Sentiments Regarding the 2024 Indonesia Presidential Election