Algoritma Pengolahan Sinyal Photoplethysmography (PPG) Berbasis Ekstraksi Fitur dan Machine Learning untuk Sistem Pengukuran Tekanan Darah Noninvasif = Photoplethysmography (PPG) Signal Processing Algorithm Based on Feature Extraction and Machine Learning for Noninvasive Blood Pressure Measurement System

Rancang Bangun Sistem Embedded Pengukuran Konsentrasi Hemoglobin Noninvasif deng = Design and Development of an Embedded System for Non Invasive Hemoglobin Concentration Measurement Using Machine Learning Method Based on Nvidia Jetson Nano

Model Antarmuka Adaptif Terintegrasi untuk Sistem Pembelajaran Daring yang Dipersonalisasi = An Integrated Model of Adaptive User Interface for Personalized E-Learning Systems

Pengembangan Alat Ukur Konsentrasi Hemoglobin Non-Invasif Menggunakan Photoplethysmography dan Berbasis Machine Learning = Development of a Non-Invasive Hemoglobin Concentration Measurement Device Based on Photoplethysmography and Machine Learning

Teknik Ekstraksi Fitur Sinyal Photoplethysmography untuk Klasifikasi Non-Invasif Kadar Glukosa Darah Menggunakan Analisis Frekuensi-Waktu dengan Bidirectional Long Short Term Memory = Feature Extraction Technique of Photoplethysmography Signals for Non-Invasive Classification Blood Glucose Level Using Time-Frequency Analysis with Bidirectional Long-Short-Term Memory