Lecturer Name:
Prof. Dr. Ir. Purwanto, DEA

Study Program:
Chemical Engineering

Lecturer Expertise:
Prof. Purwanto’s primary expertise is in chemical engineering, with a focus on process engineering and sustainable technology. His areas of expertise include green chemistry and green engineering, namely the development of environmentally friendly and resource-efficient industrial processes.
Furthermore, his research focuses on waste and hazardous materials management, waste-to-product (converting waste into valuable products), eco-industrial park development, and electrochemical technology.
In practice, this expertise is used to support sustainable industry, processing industrial waste into value-added products, and developing more efficient and environmentally friendly environmental and energy technology systems.

Publication:

Latent Dirichlet allocation (LDA) for aspect extraction of online learning in the post-pandemic COVID-19: A study of topic modeling in Indonesia
https://doi.org/10.1063/5.0201234
Sustainable waste management assessment for Kota Lama Semarang heritage area
https://doi.org/10.1051/e3sconf/202560503027
Academic Performance Prediction Using Supervised Learning Algorithms in University Admission
https://doi.org/10.30865/ijiv.v9i1.6242
Comparative analysis of green building software for energy efficiency in campus settings
https://doi.org/10.1016/j.grets.2025.100191
Domestic wastewater treatment system using waste plastic bottle caps as biofilter media
https://doi.org/10.11591/ijaas.v14.i1.pp235-246
Identification and validation of factors influencing the success of smart village services
https://doi.org/10.11591/eei.v14i1.676
Gastritis Diagnosis Expert System Using Android-Based Certainty Factor Method
https://doi.org/10.1109/ISRITI60371.2023.10291118
Smart Micro Grid Architecture for Realtime Monitoring of Solar Photovoltaic Based on Internet of Things
https://doi.org/10.1088/1755-1315/1203/1/012042
The Blade’s Angle Affects Banki-Turbine Performance as an Alternative Design for Clean Energy Generation
https://doi.org/10.18280/mmep.100132