Prof. Siana Halim adalah pakar di bidang Matematika dan Statistika yang memiliki rekam jejak riset internasional yang sangat luas. Siana Halim menyelesaikan studi matematika di ITS (1993) sebelum melanjutkan pendidikan doktoral di bidang statistik di RPTU Kaiserslautern-Landau, Jerman (2001–2005).

Dedikasi beliau di dunia akademik diakui secara nasional dengan diraihnya jabatan fungsional tertinggi sebagai Profesor (Guru Besar) sejak September 2019. Prof. Siana memiliki pengalaman riset skala global, di antaranya sebagai peneliti di Fraunhofer ITWM Kaiserslautern, Fraunhofer IPK Berlin, Jerman; menjadi peneliti tamu di Fraunhofer IPK Berlin dan Sophia University Tokyo, Jepang; serta melakukan riset untuk Office of Traffic Safety Edmonton, Canada.

Selain aktif mengajar di Teknik Industri UK Petra sejak 1994, Siana Halim juga dipercaya mengelola publikasi ilmiah sebagai Kepala Jurnal Teknik Industri, sebuah jurnal nasional bereputasi tinggi yang telah terakreditasi Sinta 2.

Email: [email protected]

Bidang Peminatan Penelitian: Statistik, Machine Learning, Forecasting, Data Mining

Publikasi:

• Navigating Uncertainty: A Multivariate Forecasting Approach to Shanghai Containerized Freight Index Trends During the COVID-19 and Red Sea Shipping Crises (2026)
• Integrating Real-Time IoT Based Monitoring and Dashboard Design for Closed-House Hen Farming (2025)
• Technical comparison of Indonesia’s consumer goods companies stock data: Symbolic aggregate approximation approach (2025)
• Implementing a Smart Farm Layer Management System Using Microcontrollers and Android (2024)
• Hierarchy of Reuse Options in Smartphone Selection and Strategies to Support Circular Economy (2024)
• Post-Harvest Soybean Meal Loss in Transportation: A Data Mining Case Study (2023)
• Designing Performance Dashboard for Monitoring Post-harvest Loss in Transportation (2023)
• Identifying Factors that Influence Customers’ Interest in Buying Refurbished Smartphones: An Indonesian Context (2022)
• Predicting the Readiness of Indonesia Manufacturing Companies toward Industry 4.0: A Machine Learning Approach (2021)
• Statistical Learning for Predicting Dengue Fever Rate in Surabaya (2020)