Andreas Handojo

Work place: Department of Informatics, Petra Christian University, Indonesia

E-mail: handojo@petra.ac.id

Website: https://scholar.google.co.id/citations?user=KUbgSxQAAAAJ&hl=en

Research Interests: Decision Support System, Mobile Computing, Management, Production Supply Chain,

Biography

Andreas Handojo – Obtained his Bachelor of Electrical Engineering degree in Electrical Engineering Department from Petra Christian University, Indonesia in 1999. He received his master, in Master of Technology Management from Institute of Technology Sepuluh Nopember, Indonesia, in 2007. Now, he served as Associate Professor in Informatics Engineering Department at Petra Christian University, Indonesia. His primary research interest are in management information system, supply chain management, business intelligent, and mobile device application.

Author Articles
A Comparative Analysis of Deep Learning Architecture for Early Detection of DoS/DDoS Patterns in Network Traffic Using Intrusion Detection Systems

By Andreas Handojo Marvel Wilbert Odelio Nico Alexandre Kurniawan Dillan Engelbert Hendrarto Matthew Timothy Handoyo

DOI: https://doi.org/10.5815/ijcnis.2026.01.09, Pub. Date: 8 Feb. 2026

Advanced intrusion detection systems are required due to the quick uptake of cloud computing and the growing complexity of cyber threats, especially Denial of Service and Distributed Denial of Service attacks. Deep learning architectures are becoming more popular because traditional IDS techniques frequently falter in dynamic, large-scale settings. Using datasets including CICIDS2017, NSL-KDD, and UNSW-NB15, this paper assesses the effectiveness of well-known DL architectures for intrusion detection, including Convolutional Neural Network, Recurrent Neural Networks, Long Short-Term Memory, and others. Key performance indicators such as accuracy, precision, and false positive rates are examined to compare the efficacy of these models. The findings show that some designs, like ResNet and Self-Organizing Map, perform well in structured environments but poorly on complicated datasets like KDDTest-21. Another important data gap highlighting the need for more research in this area is that most models do not automatically adjust to unexpected threats. This work aids in the creation of intelligent, scalable systems for changing network environments by evaluating the efficacy of DL-based IDS solutions.

[...] Read more.
The Development of Officer Selection System using the Method of Analytic Network Process (ANP) at Pharmacy Company

By Alexander Setiawan Andreas Handojo Olivia Gozali

DOI: https://doi.org/10.5815/ijem.2016.02.01, Pub. Date: 8 Mar. 2016

In this life, every person is always faced with various options and each choice will certainly bring different consequences. Pharmacy Company as an organization which managed by the human resources are also faced with various options in order to determine a quality officer. The hardest thing in making a choice is an effort to eliminate the subjectivity factor of the procurement team so that every choice made is objective.
Based on the analysis of the above requirements, the company need a computer application that can support decision making using the Analytic Network Process. The application is not a key decision makers who will replace the role of men but only as decision support.
Applications are made to assist the Personnel Manager of the company in selecting prospective employees and new employee selection. In addition, the application also help in a structured data collection so that support a balanced and objective assessment.

[...] Read more.
Other Articles