Nik Muhammad Farhan Hakim Nik Badrul Alam

@uitm.edu.my

Lecturer, Faculty of Computer and Mathematical Sciences
Universiti Teknologi MARA Pahang



                 

https://researchid.co/farhanhakim

EDUCATION

Bachelor of Science (Mathematics) with Honours
University of Malaya

Master of Science (Mathematics)
Universiti Kebangsaan Malaysia

RESEARCH INTERESTS

Fuzzy Mathematics
Inequalities

25

Scopus Publications

145

Scholar Citations

7

Scholar h-index

5

Scholar i10-index

Scopus Publications

  • Construct validation of students' anxiety and attitudes towards statistical concepts questionnaire: An exploratory factor analysis procedure
    Fadila Amira Razali, Sharifah Norhuda Syed Wahid, Noor Izyan Mohamad Adnan, Nik Muhammad Farhan Hakim Nik B. Alam, and Zulkifli Ab Ghani Hilmi
    AIP Publishing

  • Comparison of intuitionistic fuzzy time series forecasting models using different interval partitioning methods in predicting Malaysian crude palm oil prices
    Nik Muhammad Farhan Hakim Nik B. Alam, Nazirah Ramli, Asyura Abd Nassir, Ainun Hafizah Mohd, and Norhuda Mohammed
    AIP Publishing

  • Intuitionistic fuzzy time series forecasting model based on intuitionistic fuzzification function approach
    Nik Muhammad Farhan Hakim N. Badrul Alam, Nazirah Ramli, Asyura Abd Nassir, Ainun Hafizah Mohd, and Norhuda Mohammed
    AIP Publishing

  • Development of Reliable TOPSIS Method Using Intuitionistic Z-Numbers
    Nik Muhammad Farhan Hakim Nik Badru Alam, Ku Muhammad Naim Ku Khalif, and Nor Izzati Jaini
    Springer Nature Switzerland

  • The Application of Z-Numbers in Fuzzy Decision Making: The State of the Art
    Nik Muhammad Farhan Hakim Nik Badrul Alam, Ku Muhammad Naim Ku Khalif, Nor Izzati Jaini, and Alexander Gegov
    MDPI AG
    A Z-number is very powerful in describing imperfect information, in which fuzzy numbers are paired such that the partially reliable information is properly processed. During a decision-making process, human beings always use natural language to describe their preferences, and the decision information is usually imprecise and partially reliable. The nature of the Z-number, which is composed of the restriction and reliability components, has made it a powerful tool for depicting certain decision information. Its strengths and advantages have attracted many researchers worldwide to further study and extend its theory and applications. The current research trend on Z-numbers has shown an increasing interest among researchers in the fuzzy set theory, especially its application to decision making. This paper reviews the application of Z-numbers in decision making, in which previous decision-making models based on Z-numbers are analyzed to identify their strengths and contributions. The decision making based on Z-numbers improves the reliability of the decision information and makes it more meaningful. Another scope that is closely related to decision making, namely, the ranking of Z-numbers, is also reviewed. Then, the evaluative analysis of the Z-numbers is conducted to evaluate the performance of Z-numbers in decision making. Future directions and recommendations on the applications of Z-numbers in decision making are provided at the end of this review.

  • The effect of students’ attitudes and concerns on statistical concepts performance: A SEM approach
    Fadila Amira Razali, Sharifah Norhuda Syed Wahid, Noor Izyan Mohamad Adnan, Nik Muhammad Farhan Hakim Nik Badrul Alam, and Zulkifli Ab Ghani Hilmi
    Conscientia Beam
    The purpose of this study was to investigate how the attitudes and concerns of higher learning students made an impact on their performance in the fundamental concepts of the statistics course. Despite being classified as one of the important areas of scientific, industrial, or social problems, students generally perceive statistics as a challenging course to understand.  This negative perception leads to a set of complex emotional reactions that may cause great discomfort, resulting in negative consequences, such as anxiety. A sample of 248 UiTM Pahang Branch students, enrolled in a basic statistics course, was randomly selected using a stratified sampling technique. This study employed Structural Equation Modeling (SEM) method to assess the linear relationship model between students' attitudes and concerns, and their performance in statistics examinations. The findings indicated that both students' attitudes and concerns showed a significant negative influence on their performance in statistics examinations, resulting in poor academic performance. Hence, to foster students' academic success in statistics courses, it is essential to cultivate a positive attitude and enhance their confidence levels.

  • ANALYTIC HIERARCHY PROCESS BASED ON THE MAGNITUDE OF Z-NUMBERS
    Nik Muhammad Farhan Hakim Nik Badrul Alam, Ku Muhammad Naim Ku Khalif, and Nor Izzati Jaini
    Creative Decisions Foundation
    The Analytic Hierarchy Process (AHP) is a powerful multi-criteria and multi-alternative decision-making model, which assists decision-makers in giving preferences using pairwise comparison matrices. The development of the AHP using fuzzy numbers has received attention from many researchers due to the ability of fuzzy numbers to handle vagueness and uncertainty. The integration of the AHP with fuzzy Z-numbers has improved the model since the reliability of the decision-makers is considered, in which the judgment is followed by a degree of certainty or sureness. Most of the existing decision-making models based on Z-numbers transform the Z-numbers into regular fuzzy numbers by integrating the reliability parts into the restriction parts, causing a significant loss of information. Hence, this study develops the AHP based on the magnitude of Z-numbers, which is used to represent the criteria weights. A numerical example of criteria ranking for the prioritization of public services for digitalization is implemented to illustrate the proposed AHP model.

  • Synergic ranking of fuzzy Z-numbers based on vectorial distance and spread for application in decision-making
    Nik Muhammad Farhan Hakim Nik Badrul Alam, Ku Muhammad Naim Ku Khalif, and Nor Izzati Jaini
    American Institute of Mathematical Sciences (AIMS)
    <abstract> <p>Decision science has a wide range of applications in daily life. Decision information is usually incomplete and partially reliable. In the fuzzy set theory, Z-numbers are introduced to handle this situation because they contain the restriction and reliability components, which complement the impaired information. The ranking of Z-numbers is a challenging task since they are composed of pairs of fuzzy numbers. In this research, the vectorial distance and spread of Z-numbers were proposed synergically, in which the vectorial distance measures how much the fuzzy numbers are apart from the origin, which was set as a relative point, and their spreads over a horizontal axis. Furthermore, a ranking method based on the convex compound was proposed to combine the restriction and reliability components of Z-numbers. The proposed ranking method was validated using several empirical examples and a comparative analysis was conducted. The application of the proposed ranking method in decision-making was illustrated via the development of the Analytic Hierarchy Process-Weighted Aggregated Sum Product Assessment (AHP-WASPAS) model to solve the prioritization of public services for the implementation of Industry 4.0 tools. Sensitivity analysis was also conducted to evaluate the performance of the proposed model and the results showed that the proposed model has improved its consistency from 66.67% of the existing model to 83.33%. This research leads to a future direction of the application of ranking based on the vectorial distance and spread in multi-criteria decision-making methods, which use Z-numbers as linguistic values.</p> </abstract>

  • Application of Intuitionistic Z-Numbers in Supplier Selection
    Nik Muhammad Farhan Hakim Nik Badrul Alam, Ku Muhammad Naim Ku Khalif, and Nor Izzati Jaini
    Computers, Materials and Continua (Tech Science Press)


  • Integration of 4253HT Smoother with Intuitionistic Fuzzy Time Series Forecasting Model
    NIK Muhammad Farhan Alam, Nazirah Ramli, Adie Safian Ton Mohamed, and Noor Izyan Mohamad Adnan
    Pakistan Journal of Statistics and Operation Research
    Fuzzy time series is widely used in forecasting time series data in linguistic forms. Implementing the intuitionistic fuzzy sets (IFS) in fuzzy time series can better handle uncertainties and vagueness in the time series data. However, the time series data always fluctuate randomly and cause drastic changes. In this study, the 4253HT smoother is integrated with the intuitionistic fuzzy time series forecasting model to improve the forecasting accuracy. The proposed model is implemented in predicting the Malaysian crude palm oil prices. The data are firstly smoothed, and followed with the fuzzification process. Next are the transformation of fuzzy sets into IFS and the de-i-fuzzification via equal distribution of hesitancy. The forecasted data are calculated based on the defuzzified values considering the new membership degrees of the IFS after de-i-fuzzification. The results show that the integrated model produces a better forecasting performance compared to the common intuitionistic fuzzy time series forecasting model. In the future, the integration of the data smoothing should be considered before the forecasting of data using fuzzy time series could be performed.

  • Second Order Intuitionistic Fuzzy Time Series Forecasting Model via Crispification
    Nik Muhammad Farhan Hakim Nik Badru Alam and Nazirah Ramli
    Springer International Publishing

  • One-Pot Sol-Gel Synthesis of a Zinc Oxide-Reduced Graphene Oxide Composite: Photocatalysis and Kinetics Studies using a Fuzzy Inference System


  • Arithmetic Operations of Intuitionistic Z-Numbers Using Horizontal Membership Functions
    Nik Muhammad Farhan Hakim Nik Badrul Alam, Ku Muhammad Naim Ku Khalif, and Nor Izzati Jaini
    Springer International Publishing

  • Images and Metaphors of Mathematics Among University Students



  • Defuzzification of Intuitionistic Z-Numbers for Fuzzy Multi Criteria Decision Making
    Nik Muhammad Farhan Hakim Nik Badrul Alam, Ku Muhammad Naim Ku Khalif, Nor Izzati Jaini, Ahmad Syafadhli Abu Bakar, and Lazim Abdullah
    Springer International Publishing

  • Time Series Forecasting Model Based on Intuitionistic Fuzzy Set via Equal Distribution of Hesitancy De-I-Fuzzification
    Nik Muhammad Farhan Hakim Nik Badrul Alam and Nazirah Ramli
    World Scientific Pub Co Pte Ltd
    The fuzzy time series forecasting model is a powerful tool in forecasting the time series data. The nature of the fuzzy set exhibits its role in handling the uncertainty of the data. The intuitionistic fuzzy set (IFS) is a generalization of a fuzzy set that makes the forecasting process more precise and accurate. This paper proposes a new fuzzy forecasting model based on IFS via the de-i-fuzzification approach, namely equal distribution of hesitancy. The proposed model consists of four main parts; the fuzzification of historical data; the establishment of the IFS; the de-i-fuzzification; and the defuzzification. For the fuzzification, the historical data is partitioned into 14 intervals using the frequency density-based method and trapezoidal fuzzy numbers are used to fuzzify the data. The data are then converted into IFS. The data in IFS form is reduced to fuzzy set using equally distributed with the degree of hesitancy approach. The arithmetic rules based on centroid defuzzification is used to calculate the forecasted output. The proposed model shows a better performance than the existing forecasting models based on IFS, indicating that the equal distribution of hesitancy de-i-fuzzification managed to handle the non-determinism in the forecasting with simplified procedure. In the future, an improved method will be proposed to defuzzify the IFS into crisp values without going through the de-i-fuzzification process, yet preserving the nature of IFS.

  • Intuitionistic fuzzy set-based time series forecasting model via delegeration of hesitancy degree to the major grade de-i-fuzzification and arithmetic rules based on centroid defuzzification
    Nik Muhammad Farhan Hakim N B Alam, Nazirah Ramli, and Ainun Hafizah Mohd
    IOP Publishing
    De-i-fuzzification is a process of converting the intuitionistic fuzzy set into a fuzzy set. It becomes one of the core procedures in fuzzy time series forecasting model based on the intuitionistic fuzzy set. In this paper, we propose a fuzzy time series forecasting model based on intuitionistic fuzzy set via de-i-fuzzification. The de-i-fuzzification approach used is assigning the hesitancy degree to the major grade. The data are partitioned into a few intervals using the frequency density-based method. The data in the fuzzy set form is then transformed into an intuitionistic fuzzy set using the definition of intuitionistic fuzzy set. The arithmetic rules based on centroid defuzzification is used to obtain the forecasted output. The model is implemented on the data of student enrolment at the University of Alabama. The results are then compared to forecasting method using classical fuzzy set and similar de-i-fuzzification approach using max-min operation. The proposed method outperforms the other two methods, thus supports the fact that intuitionistic fuzzy set is a generalization of a classical fuzzy set and gives better performance in forecasting.

  • Challenges of home learning during movement control order among UiTM Pahang students
    Siti Rosiah Mohamed, Syafiza Saila Samsudin, Nazihah Ismail, Nik Muhammad Farhan Hakim N B Alam, and Noor Izyan Mohamad Adnan
    IOP Publishing
    Due to the COVID-19 pandemic, the enforcement of the Movement Control Order (MCO) by theMalaysian government since March 2020 significantly impacted many sectors such as the economy, society, and others. MCO enforcement has made Malaysians spend most of their time staying at home, and even some have lost their income source. Another sector that has been greatly affected is the educational sector. Today’s landscape of education has changed dramatically with the phenomenal rise of virtual classes from home. Learning and teaching processes are undertaken remotely and on digital platforms to curb the spreading of the virus. This situation has affected the lesson and learning process from home to many of the several students in Malaysia. Therefore, this study investigates the challenges of home learning during MCO among students in the Universiti Teknologi MARA (UiTM) Pahang Branch. A simple random sampling technique was used to distribute the online survey questionnaires, involving a sample of 213 students. Besides, a descriptive statistic was used to study the students’ demographic characteristics according to the challenges. In contrast, logistic regression analysis was used to determine the factors associated with home learning challenges during MCO. Based on the findings, most male and female students were not well prepared for home learning during MCO, with a percentage of 71.60% and 69.70%, respectively. As a result, 79.81% agreed that home learning is more stressful than the physical classes on the campus. In comparison, 79.63% of Social Science and 83.02% of Science and Technology students claimed that the workload given is way more significant during online classes. Furthermore, this study concludes that the most associated challenges of home learning faced by the students during MCO are the abundance of workload and loss of interest in the subject.

  • Hermite-Hadamard type inequalities for composite m -convex functions
    N.M.F.H.N.B. Alam and Ajab Bai Akbarally
    AIP Publishing

  • Fuzzy time series forecasting model based on intuitionistic fuzzy sets and arithmetic rules
    N.M.F.H.N.B. Alam, Nazirah Ramli, and Daud Mohamad
    AIP Publishing

  • Fuzzy time series forecasting model based on intuitionistic fuzzy sets via delegation of hesitancy degree to the major grade de-i-fuzzification method
    Nik Muhammad Farhan Hakim Nik Badrul Alam, Nazirah Ramli, and Norhuda Mohammed
    Horizon Research Publishing Co., Ltd.
    Fuzzy time series is a powerful tool to forecast the time series data under uncertainty. Fuzzy time series was first initiated with fuzzy sets and then generalized by intuitionistic fuzzy sets. The intuitionistic fuzzy sets consider the degree of hesitation in which the degree of non-membership is incorporated. In this paper, a fuzzy set time series forecasting model based on intuitionistic fuzzy sets via delegation of hesitancy degree to the major grade de-i-fuzzification approach was developed. The proposed model was implemented on the data of student enrollments at the University of Alabama. The forecasted output was obtained using the fuzzy logical relationships of the output, and the performance of the forecasted output was compared with the fuzzy time series forecasting model based on fuzzy sets using the mean square error, root mean square error, mean absolute error, and mean absolute percentage error. The results showed that the forecasting model based on induced fuzzy sets from intuitionistic fuzzy sets performs better compared to the fuzzy time series forecasting model based on fuzzy sets.

  • Comparison of fuzzy time series forecasting model based on similarity measure concept with different types of interval length
    Nazirah Ramli, N. Muhammad Farhan Hakim Nik Badrul Alam, Siti Musleha Ab Mutalib, and Daud Mohamad
    AIP Publishing

  • Hermite-hadamard type inequalities for composite log-convex functions
    Nik Muhammad Farhan Hakim Nik Badrul Alam, Ajab Bai Akbarally, and Silvestru Sever Dragomir
    Horizon Research Publishing Co., Ltd.
    Hermite-Hadamard type inequalities related to convex functions are widely being studied in functional analysis. Researchers have refined the convex functions as quasi-convex, h-convex, log-convex, m-convex, (a,m)-convex and many more. Subsequently, the Hermite-Hadamard type inequalities have been obtained for these refined convex functions. In this paper, we firstly review the Hermite-Hadamard type inequality for both convex functions and log-convex functions. Then, the definition of composite convex function and the Hermite-Hadamard type inequalities for composite convex functions are also reviewed. Motivated by these works, we then make some refinement to obtain the definition of composite log-convex functions, namely composite- -1 log-convex function. Some examples related to this definition such as GG-convexity and HG-convexity are given. We also define k-composite log-convexity and k-composite- -1 log-convexity. We then prove a lemma and obtain some Hermite-Hadamard type inequalities for composite log-convex functions. Two corollaries are also proved using the theorem obtained; the first one by applying the exponential function and the second one by applying the properties of k-composite log-convexity. Also, an application for GG-convex functions is given. In this application, we compare the inequalities obtained from this paper with the inequalities obtained in the previous studies. The inequalities can be applied in calculating geometric means in statistics and other fields.

RECENT SCHOLAR PUBLICATIONS

  • Efficient photodegradation of paracetamol by TiO2/ZnO photocatalyst and prediction via Fuzzy Inference System
    ZAM Hir, H Mokhtar, HA Rafaie, S Daud, NAM Shohaimi, NMFHN Badrul
    Iranian Journal of Catalysis 14 (2) 2024

  • Comparison of intuitionistic fuzzy time series forecasting models using different interval partitioning methods in predicting Malaysian crude palm oil prices
    NMFHNB Alam, N Ramli, AA Nassir, AH Mohd, N Mohammed
    AIP Conference Proceedings 2895 (1) 2024

  • Construct validation of students’ anxiety and attitudes towards statistical concepts questionnaire: An exploratory factor analysis procedure
    FA Razali, SNS Wahid, NIM Adnan, NMFHNB Alam, ZAG Hilmi
    AIP Conference Proceedings 2895 (1) 2024

  • Development of Reliable TOPSIS Method Using Intuitionistic Z-Numbers
    NMFHNB Alam, KMNK Khalif, NI Jaini
    World Conference Intelligent System for Industrial Automation, 73-80 2024

  • Intuitionistic fuzzy time series forecasting model based on intuitionistic fuzzification function approach
    NMFHNB Alam, N Ramli, AA Nassir, AH Mohd, N Mohammed
    AIP Conference Proceedings 2905 (1) 2024

  • Analytic hierarchy process based on the magnitude of z-numbers
    NMFHN Badrul, KMNK Khalif, NI Jaini
    International Journal of the Analytic Hierarchy Process 15 (1) 2023

  • The application of Z-numbers in fuzzy decision making: the state of the art
    NMFHNB Alam, KMN Ku Khalif, NI Jaini, A Gegov
    Information 14 (7), 400 2023

  • The effect of students’ attitudes and concerns on statistical concepts performance: A SEM approach
    FA Razali, SNS Wahid, NIM Adnan, NMFHN Badrul, ZAG Hilmi
    International Journal of Education and Practice 11 (3), 669-680 2023

  • Synergic ranking of fuzzy Z-numbers based on vectorial distance and spread for application in decision-making
    NMFHN Badrul, KMNK Khalif, NI Jaini
    AIMS Mathematics 8 (5), 11057-11083 2023

  • Application of Intuitionistic Z-Numbers in Supplier Selection
    NMFHNB Alam, KMN Ku Khalif, NI Jaini
    Intelligent Automation & Soft Computing 35 (1), 47-61 2023

  • A Hybrid Fuzzy Time Series Forecasting Model with 4253HT Smoother
    NMFH Alam, N Ramli, ASM Ton, NIM Adnan
     2022

  • Second Order Intuitionistic Fuzzy Time Series Forecasting Model via Crispification
    NMFHNB Alam, N Ramli
    International Conference on Intelligent and Fuzzy Systems, 556-565 2022

  • One-Pot Sol-Gel Synthesis of a Zinc Oxide-Reduced Graphene Oxide Composite: Photocatalysis and Kinetics Studies using a Fuzzy Inference System
    ZAM Hir, NMFHNB Alam, AS Shaari, HA Rafaie
    Malaysian Journal of Chemistry 24 (2), 37-46 2022

  • The Association Between Students' Leisure Activities on Weekends During Movement Control Order (MCO) and Demographic Characteristics
    SS Samsudin, NIM Adnan, NMFHNB Alam, SR Mohamed, N Ismail
    Voice of Academia 18 (2), 225-237 2022

  • Arithmetic operations of intuitionistic Z-numbers using horizontal membership functions
    NMFH Nik Badrul Alam, KMN Ku Khalif, NI Jaini
    International Conference on Soft Computing and Data Mining, 25-34 2022

  • Predicting Malaysian Crude Palm Oil Prices Using Intuitionistic Fuzzy Time Series Forecasting Model
    NMFHNB Alam, N Ramli, AA Nassir
    ESTEEM Academic Journal 18, 61-70 2022

  • Comparison of Interval Lengths for the Intuitionistic Fuzzy Time Series Forecasting Model
    NMFHNB Alam, A Abd Nassir, AH Mohd, N Ramli
    Gading Journal of Science and Technology (e-ISSN: 2637-0018) 5 (1), 36-43 2022

  • Effectiveness of gamification in teaching and learning mathematics
    NAN Ariffin, N Ramli, NMFHNB Alam, Y Yusof, A Suparlan
    Journal on Mathematics Education 13 (1), 173-190 2022

  • Intuitive Multiple Centroid Defuzzification of Intuitionistic Z-Numbers
    NMFH Alam, KMN Ku Khalif, NI Jaini, ASA Bakar, L Abdullah
    Journal of Fuzzy Extension and Applications 2022

  • Images and Metaphors of Mathematics Among University Students
    R Osman, ZAG Hilmi, N Ramli, NHM Abdullah, NMFHNB Alam
    Malaysian Journal of Mathematical Sciences 16 (1), 67-78 2022

MOST CITED SCHOLAR PUBLICATIONS

  • Effectiveness of gamification in teaching and learning mathematics
    NAN Ariffin, N Ramli, NMFHNB Alam, Y Yusof, A Suparlan
    Journal on Mathematics Education 13 (1), 173-190 2022
    Citations: 24

  • The application of Z-numbers in fuzzy decision making: the state of the art
    NMFHNB Alam, KMN Ku Khalif, NI Jaini, A Gegov
    Information 14 (7), 400 2023
    Citations: 20

  • Application of Intuitionistic Z-Numbers in Supplier Selection
    NMFHNB Alam, KMN Ku Khalif, NI Jaini
    Intelligent Automation & Soft Computing 35 (1), 47-61 2023
    Citations: 20

  • Fuzzy time series forecasting model based on intuitionistic fuzzy sets and arithmetic rules
    N Alam, N Ramli, D Mohamad
    AIP conference proceedings 2365 (1) 2021
    Citations: 12

  • Intuitionistic fuzzy set-based time series forecasting model via delegeration of hesitancy degree to the major grade de-i-fuzzification and arithmetic rules based on centroid
    NMFHNB Alam, N Ramli, AH Mohd
    Journal of Physics: Conference Series 1988 (1), 012014 2021
    Citations: 11

  • Intuitive Multiple Centroid Defuzzification of Intuitionistic Z-Numbers
    NMFH Alam, KMN Ku Khalif, NI Jaini, ASA Bakar, L Abdullah
    Journal of Fuzzy Extension and Applications 2022
    Citations: 9

  • Time series forecasting model based on intuitionistic fuzzy set via equal distribution of hesitancy de-i-fuzzification
    NMFH Nik Badrul Alam, N Ramli
    International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 2021
    Citations: 7

  • Predicting Malaysian Crude Palm Oil Prices Using Intuitionistic Fuzzy Time Series Forecasting Model
    NMFHNB Alam, N Ramli, AA Nassir
    ESTEEM Academic Journal 18, 61-70 2022
    Citations: 6

  • Construct validation of students’ anxiety and attitudes towards statistical concepts questionnaire: An exploratory factor analysis procedure
    FA Razali, SNS Wahid, NIM Adnan, NMFHNB Alam, ZAG Hilmi
    AIP Conference Proceedings 2895 (1) 2024
    Citations: 5

  • Fuzzy Time Series Forecasting Model Based on Intuitionistic Fuzzy Sets via Delegation of Hesitancy Degree to the Major Grade De-i-fuzzification Method
    NMFHNB Alam, N Ramli, N Mohammed
    Mathematics and Statistics 9 (1), 46-53 2021
    Citations: 5

  • Defuzzification of intuitionistic Z-numbers for fuzzy multi criteria decision making
    NMFH Nik Badrul Alam, KMN Ku Khalif, NI Jaini, AS Abu Bakar, ...
    International Conference on Intelligent and Fuzzy Systems, 879-887 2021
    Citations: 4

  • Challenges of home learning during movement control order among UiTM Pahang students
    SR Mohamed, SS Samsudin, N Ismail, NMFHNB Alam, NIM Adnan
    Journal of Physics: Conference Series 1988 (1), 012052 2021
    Citations: 4

  • Synergic ranking of fuzzy Z-numbers based on vectorial distance and spread for application in decision-making
    NMFHN Badrul, KMNK Khalif, NI Jaini
    AIMS Mathematics 8 (5), 11057-11083 2023
    Citations: 3

  • One-Pot Sol-Gel Synthesis of a Zinc Oxide-Reduced Graphene Oxide Composite: Photocatalysis and Kinetics Studies using a Fuzzy Inference System
    ZAM Hir, NMFHNB Alam, AS Shaari, HA Rafaie
    Malaysian Journal of Chemistry 24 (2), 37-46 2022
    Citations: 3

  • Comparison of Interval Lengths for the Intuitionistic Fuzzy Time Series Forecasting Model
    NMFHNB Alam, A Abd Nassir, AH Mohd, N Ramli
    Gading Journal of Science and Technology (e-ISSN: 2637-0018) 5 (1), 36-43 2022
    Citations: 2

  • Hermite-Hadamard type inequalities for composite m-convex functions
    N Alam, AB Akbarally
    AIP Conference Proceedings 2365 (1) 2021
    Citations: 2

  • Comparison of fuzzy time series forecasting model based on similarity measure concept with different types of interval length
    N Ramli, NMFHNB Alam, SMA Mutalib, D Mohamad
    AIP Conference Proceedings 2266 (1) 2020
    Citations: 2

  • Efficient photodegradation of paracetamol by TiO2/ZnO photocatalyst and prediction via Fuzzy Inference System
    ZAM Hir, H Mokhtar, HA Rafaie, S Daud, NAM Shohaimi, NMFHN Badrul
    Iranian Journal of Catalysis 14 (2) 2024
    Citations: 1

  • Analytic hierarchy process based on the magnitude of z-numbers
    NMFHN Badrul, KMNK Khalif, NI Jaini
    International Journal of the Analytic Hierarchy Process 15 (1) 2023
    Citations: 1

  • A Hybrid Fuzzy Time Series Forecasting Model with 4253HT Smoother
    NMFH Alam, N Ramli, ASM Ton, NIM Adnan
     2022
    Citations: 1