Shaiful Bakhtiar bin Rodzman
Universiti Teknologi MARA

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Expert judgment Z-Numbers as a ranking indicator for hierarchical fuzzy logic system Shaiful Bakhtiar bin Rodzman; Normaly Kamal Ismail; Nurazzah Abd Rahman; Syed Ahmad Aljunid; Zulhilmi Mohamed Nor; Ku Muhammad Naim Ku Khalif
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 8, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (493.902 KB) | DOI: 10.11591/ijai.v8.i3.pp244-251

Abstract

In this article, the researchers main contribution is to investigate three factors which may correlate in implementation of Expert Judgment Z-Numbers as new Fuzzy Logic Ranking Indicator such as: expert relevance judgment or score, the expert confidence and the level of expertise. The Expert Judgment Z-Numbers then will be an input to the Hierarchical Fuzzy Logic System of Domain Specific Text Retrieval, along with other indicators such as Ontology BM25 Score, Fabrication Rate, Shia Rate and Positive Rate of hadith document. The results showed, the proposed system, with the additional new indicator of Expert Judgment Z-Numbers, may improve the original BM25 ranking function, by yielding better results on 26 queries, on all evaluation metrics that are measured in this research such as P@10, %no measures and MAP, and has achieved better results in 28 queries on P@10 alone, compared to the BM25 original score, that only yield better results in 2 queries on all evaluation metrics, and also yield better results in 4 queries on the MAP alone. The results proved that the proposed system has a capability to utilize the expert confidence and their relevant judgment that are represented in Z-Number, as an indicator to optimize the existing ranking function system and has a potential for a further research to be conducted on these domains. For the future works, the researchers would like to enhance this research by including a variety of expert’s level confidence and their judgment, also a new calculation to represent the value of Z-Numbers.
I-OnAR: a rule-based machine learning approach for intelligent assessment in an online learning environment Shaiful Bakhtiar bin Rodzman; Nordin Abu Bakar; Yun-Huoy Choo; Syed Ahmad Aljunid; Normaly Kamal Ismail; Nurazzah Abd Rahman; Marshima Mohd Rosli
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 2: February 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i2.pp1021-1028

Abstract

Intelligent systems are created to automate decision making process that is similar to human intelligence. Incorporating intelligent component has achieved promising results in many applications, including in education. Intelligence modules in a tutoring system would bring the application and its capability closer to a human's ability to serve its human users and to solve problems. However, the majority of the online learning provided in the literature review especially in Malaysia, normally only provide the lecture notes, assignments and tests and rarely suggest or give feedbacks on what the students should study or do next in order to fully understand the subjects. Hence, the researchers propose an online learning environment called Intelligent Online Assessment and Revision (I-OnAR). It facilitates the learning process at multiple learning phases such as test creation, materials revision, feedback for improvement and performance analysis. These components are incorporated into the tutoring system to assist self-pace learning at anytime and anywhere. The intelligent agent uses a Rule-based Machine Learning method for the adaptive capabilities such as automated test creation and feedbacks for improvement. The system has been tested on a group of students and found to be useful to support learning process. The results have shown that 60% of the subjects’ performance have improved with the help of the system. The students were given feedbacks on the topic they did poorly as well as how to improve their performance. This proves that the Intelligent Online Assessment and revision (I-OnAR) can be a useful tool to help online students intelligently, systematically and efficiently. For the future works, the researchers would like to apply the usage of other techniques such as Fuzzy Logic to strengthen the analysis and decision of the current system.
Development of mobile application for Malay translated hadith search engine Nurazzah Abd Rahman; Faiz Ikhwan Mohd Rafhan Syamil; Shaiful Bakhtiar bin Rodzman
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 2: November 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i2.pp932-938

Abstract

This paper presents the development of mobile application for Malay Translated Hadith search engine. Limitations of current Hadith web application are the design is to optimize its usage on desktop computer but not on mobile devices, which requires simple and user friendly interface. Besides that, web application also needs internet connection to use. Due to increase usage of mobile application among mobile phone users, many existing web applications have moved to mobile based applications to cater for increasing numbers of mobile users. In this study, a mobile application for Android and iOS mobile application has been developed using Flutter framework, a hybrid mobile application framework. A Malay Translated hadith search engine mobile application can easily assist those who are seeking knowledge to learn more about certain topics in hadith, a second source of Islamic knowledge. This mobile application has search and directory features for users to browse the 2028 Sahih Bukhari hadith collection. Users can enter their query using search features to find selected hadith in Malay language. Queries will be processed for searching relevant hadith and display the results to the user. Evaluation using Recall and Precision shows that on the average Recall is 73% and Precision is 33%. Functionality testing is also conducted to test against the functional requirements or specifications. Results shows all requirements are successfully tested.
Domain specific concept ontologies and text summarization as hierarchical fuzzy logic ranking indicator on malay text corpus Shaiful Bakhtiar bin Rodzman; Normaly Kamal Ismail; Nurazzah Abd Rahman; Syed Ahmad Aljunid; Zulhilmi Mohamed Nor; Ahmad Yunus Mohd Noor
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i3.pp1527-1534

Abstract

Ranking function is a predictive algorithm that is used to establish a simple ordering of documents according to its relevance. This step is critical because the results’ quality of a Domain Specific Information Retrieval (IR) such as Hadith Information Retrieval is fundamentally dependent of the ranking function. A Hierarchical Fuzzy Logic Controller of Mamdani-type Fuzzy Inference System has been built to define the ranking function, based on the Malay Information retrieval’s BM25 Model. The model examines three-inputs (Ontology BM25 Score, Fabrication Rate of Hadith and Shia Rate of Hadith) and four-output values of Final Ranking Score which consist of three triangular membership functions. The proposed system has outperformed the BM25 original score and the Vector Space Model (VM) on 16 queries, while the BM25 original score and Vector Space Model only yield better result in 9 and 2 queries respectively on the P@10, %no measures and MAP. P@10 represent the values of Precision at Rank 10 P@10), %no measures represent the percentage of queries with no relevant documents in the top ten retrieved and MAP represents Mean Average Precision of the queries. The results show the proposed system have capability to demote negative documents and move up the relevant documents in the ranking list and its capability to recall unseen document with the application of ontology in text retrieval. For the future works, the researcher would like to apply the usage of other Malay Semantic elements and another corpus for positive ranking indicator.