Program Studi Matematika Universitas Katolik Parahyangan
Profil Dosen
Assistant Professor
Email: robynirawan.tjia@unpar.ac.id
Education:
- M.Sc in Statistics with specialization in Biostatistics (2020) at Hasselt University, Belgium
- B.Sc in Mathematics (2016) at Parahyangan Catholic University, Indonesia
Research Interests: Biostatistics; Regression Models; Longitudinal Data Analysis; Predictive Analytics; Disease Mapping
Recent Research:
| 1 | Estimating Relative Risk of Dengue in Bandung using Bayesian Inference through Integrated Nested Laplace Approximation |
| 2 | Detection of Fake News Using Convolutional Neural Network (CNN), Long Short-term Memory (LSTM), and Hybrid Model of CNN-LSTM |
| 3 | Longitudinal Data Analysis on the Sustainability of Countries’ Economic Gross Domestic Product |
| 4 | Predicting the Social Health Insurance Premium Price for COVID-19 Cases by Epidemiology Model |
| 5 | Application of Survival Dynamical System on Disease Transmission |
For research and publications, click here
Undergraduate Thesis Topic Coverage (Topik Skripsi yang ditawarkan):
| 1 | Biostatistika / bioinformatika |
| 2 | Analisis prediktif |
| 3 | Analisis data longitudinal |
| 4 | Model inferensi Bayesian |
| 5 | Model regresi |
Judul skripsi yang pernah dibimbing:
| 1 | Penerapan dan Perbandingan Performa Pembelajaran Mesin Multi-Output Untuk Luaran Numerik-Numerik dan Numerik-Kategorik |
| 2 | Pendeteksian Berita Palsu dengan Menggunakan Model Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), dan CNN-LSTM |
| 3 | Penerapan Model Support Vector Machine, Light Gradient Boosting Machine, Adaptive Boosting, dan Model Hybrid AdaBoost-SVM pada Data Churn Pelanggan |
| 4 | Penerapan Metode Regresi Kuantil dengan Koefisien Tak Konstan Pada Volume Otak untuk Indikasi Penyakit Demensia |
| 5 | Penerapan Linear Mixed Model pada Data Longitudinal: Indeks Pembangunan Manusia |
| 6 | Prediksi Indikator Saham Menggunakan ARIMA-X dan Long Short-Term Memory (LSTM) |
| 7 | Analisis Prediksi Peluang Mortalitas Penduduk Indonesia dan Filipina dengan Menggunakan Model Inferensi Bayesian |
| 8 | Analisis Performa Model ResNet-50 yang Disesuaikan untuk Pengenalan Sidik Jari dan Modifikasinya |