The current state of computer-based research demands an increase of research quality. Researchers are required to actively adapt to the current trend and technology in order to produce a relevant and useful research. In order to meet this requirement, Faculty of Computer Science and Information Technology, Universitas Sumatera Utara would like to present The 1st Workshop of Fasilkom-TI as a joint event of ICCAI 2017. We would like to invite you to this event in order to enhance the knowledge and ability of participants in creating a full-length, high quality, and original research.


How to Write in High Impact Journal by Prof. Dr. Salwani Abdullah

Publication in a reputable, peer reviewed journal provides the most effective and permanent means of disseminating knowledge to the outside world. Many aspiring researchers endeavour to publish their work in high-impact journals. Therefore, it is essential to follow the guiding principles of scientific research in order to make this a reality. This talk aims to provide a four part guideline to assist with the preparation of scientific papers in high-impact journals : (i) best practices of good technical writers, (ii) how to write and publish a scientific paper, (iii) most common writing errors, and (iv) suggestions for writing good scientific papers. In addition, I share my personal experience on how to publish papers in high-impact journals with samples of actual papers that went through the publication process.

Prof. Dr. Salwani Abdullah's CV


Graph Neuron by Dr. Benyamin B. Nasution, Dipl. -Ing., M.Eng

Hierarchical GN (HGN) is an improvement on original Graph Neuron (GN) algorithm for matching in-complete/noisy patterns. It also reduces the crosstalk problem within closely matched patterns. GN is intrinsically a lightweight in-network processing algorithm and it adopts naturally to wireless sensor networks. The GN produces a pattern matching capability by connecting lightweight processes over a data network. GN does not require expensive floating-point computations and hence it is very suited for tiny devices. GN does not entail exponentially increasing processing overhead as traditional graph matching algorithm do. Moreover, GN does not require definition of rules or setting of thresholds by the operator to achieve the desired results as is the case with expert systems, fuzzy logic, and neural nets. GN does not require heuristics entailing iterative operations for memorization and recall of patterns either. The GN implements a single cycle memorization and recall operations through a novel algorithmic design. HGN links multiple GN networks into two, three, or multi-layer arrays for filtering noise and cross talk out of pattern data inputs.

Dr. Benyamin B. Nasution, Dipl.-Ing., M.Eng's CV



GrandDhika Hotel

Date: November 28, 2017

Registration Fee

2 courses = Rp.700,000 (USD 70)

1 course = Rp.500,000 (USD 50)

Registration fees are transferred to the account:

Bank Negara Indonesia
Swift Code: BNINIDJA
Account Number: 0578725032
Account Name: ICCAI 2017

For all participant who have pay the registration fee, please send the proof of payment with your name as the Subject to



Registration Form



12.00 – 13.00 Lunch and Praying Time

13.00 – 15.00 Workshop “How to Write in High Impact Journal”

15.00 – 15.30 Coffee Break

15.30 – 17.30 Workshop “ Graph Neuron”

ICCAI Organizing Committe
Email :
© 2017 Faculty of Computer Science and Information Technology
Jl. Universitas No. 9A, Medan, 20155
University of Sumatera Utara