Mdm Salmah Binti Fattah

Salmah Fattah is a lecturer in the department of Network Engineering, Faculty of Computing and Informatics, Universiti Malaysia Sabah (UMS). She involves as an academician, researcher, teaching experience and undergraduate project supervision for more than ten years. She has completed Master degree in Information Technology (MIT) from National University of Malaysia (UKM) with a specialization of Information Retrieval. Her current research interests are underwater wireless sensor networks (UWSN), wireless sensor networks (WSN) multi-objective optimization, Intelligent robotics and Internet of Things (IoT).

10

Year of Experience

25,000

Granted (RM)Funds

10

Total Publications

6

Total Projects

3

Project Finished

RECENT PUBLICATIONS

  1. Manzoor, A., Judge, M. A., Almogren, A., Akhunzada, A., Fattah, S., Gani, A., &Zareei, M. (2020). A Priori Multiobjective Self-Adaptive Multi-Population Based Jaya Algorithm to Optimize DERs Operations and Electrical Tasks. Ieee Access, 8, 181163-181175.
  2. Fattah, S., Gani, A., Ahmedy, I., Idris, M. Y. I., & Targio Hashem, I. A. (2020). A Survey on Underwater Wireless Sensor Networks: Requirements, Taxonomy, Recent Advances, and Open Research Challenges. Sensors, 20(18), 5393.
  3. Jason Teo , Mohd Hanafi Ahmad Hijazi, Hui Keng Lau, Salmah Fattah, Aslina Baharum. 2015. Crossover-first Differential Evolution For Improved Global Optimization In Non-uniform Search Landscapes. Progress In Artificial Intelligence. Jil. 3. 3. 129-134.
  4. Salmah Fattah Siti Hasnah Tanalol Asni Tahir. 2014. Assessing Perceptions Of Academic Staff In Using SmartUMS For Teaching And Learning. International Journal On E-Learning Practices (IJELP) Vo.1(1) 2014. Jil. 1. 1. 59-67.
  5. A Tahir, S Fattah, R Alfred, H Appolonius. 2013. Proceedings Of 6th International Conference Of Education, Research And Innovation. Ontology-Based User Model And IRT For Personalized Learning Environment. 978-84-616-3847-5.
  6. A Tahir, S Fattah, V Petrus Atin. 2013. ICERI2013 Proceedings. PERSONALISED VIRTUAL LEARNING ENVIRONMENT FOR INDIGENOUS LANGUAGE LEARNING. 978-84-616-3847-5.
  7. S Fattah, A Tahir. 2013. EDULEARN13 Proceedings. STUDENTS’ EXPERIENCE TOWARDS LMS: A CASE STUDY FOR UNIVERSITI MALAYSIA SABAH. 978- 84-616-3822-2.
  8. H Appolonius, S Fattah, A Tahir, SH Tanalol, R Alfred. 2013. EDULEARN13 Proceedings. MODELLING A SUCCESS LEARNING STYLE IN ADAPTIVE HYPERMEDIA. 978-84-616-3822-2.
  9. Helena Appolonius, Salmah Fattah, Asni Tahir, Siti Hasnah Tanalol And Rayner Alfred. 2013. EDULEARN13 Proceedings. Modelling A Success Learning Style In Adaptive Hypermedia. 978- 84-616-3822-2.
  10. Salmah Fattah, Siti Hasnah Tanalol, Asni Tahir, Chung Seng Kheau, 2012. Assessing the Acceptability of The FYP Website: An Initial Investigation. International Conference on Education and New Learning Technologies, EDULEARN2012, Barcelona (Spain), July 2-4, 2012.

RECENT PROJECTS

Ongoing Projects:

  1. Deep Learning Approach to Detection and Prediction of Harmful Algae Blooms in Sabah
  2. Sistem Fertigasi Pintar
  3. The Development of Early Tuberculosis Screening Module using Entropy Canny- Edge Detector and Deep Learning

Completed Projects:

  1. 1. Pembinaan e-Instrumen Sosioemosi OKU-Pembelajaran (e-ISEOKU-Pb) sebagai Alat Ukur Pengujian Kesejahteraan Psikologi di kalangan OKU-Pb
  2. Construction of Intelligent Personalised Learning Tools
  3. Augmentation of Ontology-Based User Model with Item Response Theory

Collaborate With Us

We are persuaded that having a research group that has close coordinated efforts with the encompassing society is something that is useful for everybody. Thusly, we are extremely glad to work together with various organizations and industries on research projects and to develop joint funding applications.

  • Email Us

    Dr Leau Yu Beng : lybeng@ums.edu.my

    Dr Tan Soo Fun : soofun@ums.edu.my

    Ms Nordaliela Mohd Rusli : daliela@ums.edu.my

    Mdm Salmah Binti Fattah: salmahf@ums.edu.my

  • Visit Us

    Faculty of Computing and Informatics
    Universiti Malaysia Sabah
    88400, Jln UMS, Kota Kinabalu, Sabah