Robyn Irawan, M.Sc

Email	:	robynirawan.tjia@unpar.ac.id
Jabatan Struktural	:	Asisten Ahli
Pendidikan	:	M.Sc in Statistics with specialization in Biostatistics (2020) di Hasselt University, Belgium B.Sc in Mathematics (2016) di Universitas Katolik Parahyangan, Indonesia

Minat Penelitian

1. Regression Models
2. Bayesian Inference Statistics
3. Biostatistics

Penelitian Terkini

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

Publikasi Terpilih

1. Bayesian Additive Regression Tree Application for Predicting Maternity Recovery Rate of Group Long-Term Disability Insurance
   S Budiana, F Kusnadi, R Irawan
   BAREKENG: Jurnal Ilmu Matematika dan Terapan 17 (1), 0135-0146
2. Bayesian Poisson-gamma and Log-normal models for estimating the relative risks of health insurance claims due to dengue disease in Bandung
   B Yong, F Kristiani, R Irawan, Marcellus
   Journal of Statistics and Management Systems 23 (8), 1497-1512
3. Non-Spatial Analysis of Relative Risk of Dengue Disease in Bandung Using Poisson-gamma and Log-normal Models: A Case Study of Dengue Data from Santo Borromeus Hospital in 2013
   R Irawan, B Yong, F Kristiani
   Journal of Physics: Conference Series 812 (1), 012034

Topik Skripsi yang Ditawarkan

1. Analisis prediktif
2. Model survival
3. Analisis data longitudinal
4. Model inferensi Bayesian
5. Statistika multivariat

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

Publikasi