Dr. Maria Susan Anggreainy, S.Kom., M.Kom., is an interdisciplinary academic and computer scientist whose primary expertise lies in machine learning, natural language processing (NLP), psychoinformatics, and healthcare AI. Her work focuses on developing data-driven decision support systems and early detection models for psychological conditions within healthcare and industrial settings. In addition to her academic career, she has professional experience as a software engineer in the industry, strengthening her ability to bridge theoretical research with practical implementation in AI-based healthcare solutions.
Educational Background
- Doctor of Computer Science (S3), Universitas Indonesia: Her doctoral research focused on computational intelligence models that combined soft computing and machine learning techniques for intricate biological and predictive data analysis.
- Master of Computer Science (S2), Universitas Indonesia : Her master’s thesis investigated computational methods and intelligent optimization algorithms for digital image analysis and pattern recognition.
- Bachelor of Computer Science (S1), Institut Pertanian Bogor, she gained a solid foundation in structured software development methodologies and healthcare information systems during her undergraduate studies
Research Areas
Psychoinformatics
Dr. Anggreainy’s psychoinformatics research applies machine learning, NLP, and deep learning to model psychological states and behavioral data. Her work includes
- AI models for stress detection and behavioral classification
- Transformer-based architecture (ALBERT, BERT) for psychological text analysis
- Explainable AI frameworks in mental health prediction
Health Informatics
In health informatics, she develops predictive analytics and intelligent systems for biomedical and clinical datasets, including:
- Disease prediction and risk assessment modeling
- Clinical decision support systems
- Machine learning and soft computing for health applications
She bridges computational intelligence with real-world healthcare challenges.
Bioinformatics & Big Data Analytics
Her bioinformatics and big data research apply AI, machine learning, and large-scale data engineering to biological and environmental problems. Key themes include:
- Computational analysis of biological and marine data
- Big-data-driven predictive frameworks
- Machine learning for sustainable and ecological modeling
Research and Publication
- Google Scholar: https://scholar.google.com/citations?user=TJz95CwAAAAJ&hl=id
- Scopus Author ID: https://www.scopus.com/authid/detail.uri?authorId=57200074279
- ResearchGate: https://www.researchgate.net/profile/Maria-Anggreainy-2
- Sinta: https://sinta.kemdiktisaintek.go.id/authors/profile/6804008
- ORCID: https://orcid.org/0000-0001-7676-8559
- BINUS Research Profile: https://research.binus.ac.id/lecturer/D6420/dr-maria-susan-anggreainy-skom-mkom/
Research
Publication
Professional Memberships
- Member of APTIKOM – Bioinformatics Division
- Member of Institute of Electrical and Electronics Engineers (IEEE)
Dr. Anggreainy has successfully secured multiple competitive research grants:
2025 – Ministry of Research and Higher Education (Kemenristekdikti) Grant
- Role: Research Member
- Project Title: Model Prediksi Pemetaan Tangkapan Ikan Tuna berbasis Big Data dan Machine Learning
- Focus: Big-data-based predictive modeling for tuna catch mapping to support sustainable fisheries.
2025 – BINUS International Research Grant (PIB)
- Role: Principal Investigator
- Title: Developing AI Models for Stress Level Prediction and Recommendations for Higher Education
- Focus: AI-based stress prediction and recommendation systems for academic environments.
2024 – BINUS International Research Grant (PIB)
- Role: Principal Investigator
- Title: Mental Health Detection Using Machine Learning and Deep Learning Approaches
- Focus: ML and DL frameworks for detecting mental health conditions from behavioral data.