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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Indonesian Journal of Electrical Engineering and Computer Science
Nurazzah Abd Rahman
Universiti Teknologi MARA
Computer Science & IT Engineering

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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.
Classification of customer feedbacks using sentiment analysis towards mobile banking applications Nurazzah Abd Rahman; Seri Dahlia Idrus; Noor Latiffah Adam
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 4: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i4.pp%p

Abstract

Innovation and technology have subsequently transformed banking industry’s way of delivering products and services to their customer. Mobile banking is an effective way of performing transaction as it can be performed anywhere and anytime. The evolution of banking experience is important to fulfil customers’ need and demand especially in highly competitive banking industry. Through mobile banking application, customer can express their satisfaction and dissatisfaction directly on the application store platform. The fulfilment of customer’s satisfaction is important to avoid customer attrition. This research focused on customer feedbacks towards six mobile banking application in Malaysia which is Maybank, Commerce International Merchant Bankers (CIMB), Public Bank, Hong Leong Bank, Rashid Hussein Bank (RHB) and AmBank. This research aims to identify keywords related to customer feedback towards mobile banking, classify the sentiment and evaluate the accuracy performance by using supervised machine learning algorithm of support vector machine (SVM) and Naïve Bayes (NB). The result shows that linear SVM is the best model with the highest value in all accuracy, precision, recall, including F1-score with value 97.17%, 97.21%, 97.17% and 97.18% respectively. With this high accuracy value, this model would have better performance in analyzing the classification of customer feedback in mobile banking application.
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.
Ant colony algorithm for text classification in multicore-multithread environment Ahmad Nazmi Fadzal; Mazidah Puteh; Nurazzah Abd Rahman
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1359-1366

Abstract

This paper presents about Ant Colony Algorithm (ACO) for Text Classification in Multicore-Multithread Environment in Artificial Intelligent domain. We had develop a software which assimilate concurrency concept to multiple artificial ants. Pheromone in ACO is the main concept used to solve the text classification problem. In regards to its role, pheromone value is changed depending on the solution finding that has been discovered at the pseudo random heuristic attempt in selecting path from text words. However, ACO can take up longer time to process larger training document. Based on the cooperative concept of ants living in colony, the ACO part is examined to work in multicore-multithread environment as to cater additional execution time benefit. In running multicore-multithread environment, the modification aims to make artificial ants actively communicate between multiple physical cores of processor. The execution time reduction is expected to show an improvement without compromising the original classification accuracy by the investment of trading on more processing power. The single and multicore-multithreaded version of ACO was compared statistically by conduction relevant test. It was found that the result shows a positive time reduction improvement.
Jahai language repository: a mobile application Nurazzah Abd Rahman; Masurah Mohamad; Itaza Afiani Mohtar; Saidi Adnan Md Nor
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp1214-1223

Abstract

The Jahai language is facing extinction primarily because it is among the least spoken language among minority groups in Malaysia. This is due to lesser speakers and the shift to using a more dominant language. The Jahai tribe is one of the community groups living in the Royal Belum Perak State Park. People who need assistance from Jahai people often face difficulties in communicating with them due to the language barrier. Therefore, a mobile translation system was developed to preserve the language. The system translates the Jahai terms into Malay language. This way, by using the system, other ethnics in Malaysia can understand the language especially when communicating with Jahai people. Three main steps are required in the translation process; first, key in the text input via special character keypad. Then, the system will search the matching word in the database. Finally, the meaning of the word will be displayed. The testing results have indicated this system is functional and accepted with the SUS score of 94/100. Several future recommendations could be made such as including voice search function and adding more Jahai terms in other categories so as to improve the functionality and usability of this proposed system.
Co-Authors Ahmad Nazmi Fadzal Ahmad Yunus Mohd Noor Faiz Ikhwan Mohd Rafhan Syamil Itaza Afiani Mohtar Ku Muhammad Naim Ku Khalif Marshima Mohd Rosli Masurah Mohamad Mazidah Puteh Noor Latiffah Adam Nordin Abu Bakar Normaly Kamal Ismail Saidi Adnan Md Nor Seri Dahlia Idrus Shaiful Bakhtiar bin Rodzman Syed Ahmad Aljunid Yun-Huoy Choo Zulhilmi Mohamed Nor