Development of lecturers' publication score algorithm / Zamali Tarmudi and Haijon Gunggut

The aim of this paper is to develop a lecturers' publication score algorithm to assist UiTM Sabah in selecting winners among lecturers in terms of publication contribution. It focuses on how the evaluation committee identifies and determines the score for categories of different publication materials such as journal articles, proceedings, books, and chapter in a book, technical report, etcetera and the justification for the weightage given for each category. Apart from that, the technical aspects such as the type of indexes, role of authors and the level of publications are also discussed thoroughly by the committee until reaching a certain degree of consensus. Based on predetermined characteristics, a comprehensive algorithm was designed with multiple factor bases using the fuzzy evaluation approach. Then, an intial simulation testing was performed by using Microsoft Excel 2010 to simulate the datasets which were obtained from UiTM Sabah. This process is vital to determine the feasibility and suitablility of the proposed algorithm. The results showed that, the proposed algorithm is highly beneficial to the evaluation committee and can significantly reduce the time consumed in the evaluation process . Thus, it can facilitate the task of the committee to make decisions in an easier, transparent and systematic manner

Equilibrium linguistic computation method for fuzzy group decision making

This paper proposes an equilibrium computation method using linguistic variables based on the conflicting bifuzzy sets. The linguistic terms were defined and associated with the triangular fuzzy number as well as the labeling system in the early stages. Then, the negation operator was introduced and the bifuzzy approaches were employed to derive the aggregation equilibrium linguistic judgement for evaluation process

Perbandingan keputusan multi-atribut berasaskan beberapa teori set (Comparison of multi attributes decisions based on several set theories)

Dalam makalah ini dibincangkan analisis perbandingan keputusan multi-atribut yang diperoleh hasil daripada pendekatan penilaian menggunakan teori set ketara, set kabur, set kabur berintuisi dan set dwikabur konflik. Perbincangan tertumpu kepada analisis yang melibatkan penilaian secara dedua dalam teori set biasa, penilaian secara [0,1] dalam set kabur, penilaian secara ‘darjah keahlian’ dan ‘darjah bukan keahlian’ serta syarat 0 ≤ μA(x) + γA(x) ≤ 1 dalam set kabur berintuisi, dan penilaian secara ‘timbal balas’ (i.i., positif dan negatif) dalam set dwikabur konflik. Bagi tujuan ini, keempat-empat teori set dibincangkan secara ringkas dari aspek takrif, kesamaan dan perbezaan serta cara pendekatan yang digunakan untuk mendapat indeks hampiran relatif. Aplikasi pengiraan berangka secara bandingan menggunakan TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) turut diberikan untuk semua pendekatan teori di atas. Keputusan pengiraan menunjukkan, perbezaan yang ketara pada nilai indeks hampiran relatif selain susunan keutamaan alternatif yang berbeza antara set ketara dengan teori set yang lain. Dapatan juga menunjukkan susunan keutamaan alternatif untuk tiga teori set kecuali set ketara adalah sama dan konsisten. Keputusan sebegini sekaligus memberi peluang dan ruang yang luas kepada penyelidik untuk mengkaji secara lebih mendalam pada masa hadapan. This paper discusses the comparison analyses for multi-attributes decision derived from crisp set, fuzzy set, intuitionistic fuzzy set and conflicting bifuzzy set. It focuses on the different evaluation approach using the binary system in crisp sets, the membership degree in [0,1] for fuzzy sets, the membership and non-membership degrees with condition 0 ≤ μA(x) + γA(x) ≤ 1 in intuitionistic fuzzy sets, and ‘equilibrium evaluation approach’ (i.e., positive and negative aspects) in conflicting bifuzzy sets. To meet these objectives, all the set theories are briefly discussed specifically the definitions, equalities, the differences as well as the different evaluation approaches to obtain the relative approximation index. A numerical example using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is also presented to clarify each of the above set theories. From the calculation results, it shows the significant differences of relative approximation index for each theory and different rating between the crisp set and other set theories. It is also found that all the set theories have recorded the same rating and consistent, except crisp sets. Thus, this situation offers wider opportunities to investigate more deeply and holistically for future research

An overview of municipal solid wastes generation in Malaysia

Increasing population and tremendous urbanisation growth and other factors influence directly the municipal solid waste (MSW) generation in Malaysia. The huge quantity of MSW generation, particularly in Peninsular Malaysia, has increased from 16,200 tonnes per day in 2001 to 19,100 tonnes per day in 2005 or an average of 0.8 kg/capita/day. The amount increases yearly and seems to grow in parallel with the urban areas in many Asian countries which are estimated to produce approximately 8 million tonnes per day. Thus, this paper briefly discusses the scenario of MSW generation in Malaysia. It focuses on the trends of MSW generation, the composition of MSW, the contributing factors as well as the management problems occurring in Malaysia presently. In addition, some updated statistical figures related to the MSW and management aspects are provided to clarify the present situation and the government’s future planning. Recent development indicates that the Malaysian government has taken forward to deal with such problems in MSW management across the municipalities through closed dumping sites, upgrading existing conventional landfills to sanitary status, constructing new transfer stations and giving serious priority for an alternative disposal system in the near future. Moreover, the establishing a new national solid waste and public cleansing management corporation and enacted a new specific regulations for solid waste and public cleansing management which approved on September 2007 is also seen as a proactive step towards achieving the sustainability of MSW management as a long term solution

ASSESSING WATER QUALITY INDEX IN RIVER BASIN : FUZZY INFERENCE SYSTEM APPROACH

Water Quality Index is an important water assessment that sustain and conserve the aquatic ecosystem. In Malaysia, the current classi ication practice on Department of Environmental Water Quality Index (DOE WQI) shows rigid value in term of assessing the input of parameters that close to a class boundary. Hence, this study proposed a technique to assess the parameters in a holistic manner by using the Fuzzy Inference System (FIS). The approach as an assessment tool represents the classes of various ranges and aggregating the parameters using membership function and Centroid Function respectively. A numerical example based on actual data from one of the sampling station from Inanam Likas River Basin was adapted in this study. It was adapted to demonstrate the proposed approach. Findings shown using the proposed methods indicate that the river has Poor water status. Overall, FIS is able to assess the parameters and execute into a single index that represent the condition from poor to excellent scales of the water qualit

Pemilihan sistem pelupusan sisa pepejal perbandaran menggunakan model dwikabur konflik (Selecting municipal solid waste disposal system using a conflicting bifuzzy model)

Kajian ini memfokuskan penggunaan model kabur baru untuk pemilihan sistem pelupusan sisa pepejal perbandaran (SPP) yang dewasa ini dilihat semakin menghambat terutamanya negeri-negeri di bahagian tengah Semenanjung Malaysia. Rekod menunjukkan negeri Selangor dan Wilayah Persekutuan Kuala Lumpur (WPKL) mencatatkan penghasilan SPP tertinggi melebihi 2.32 juta tan setahun pada tahun 2005. Lazimnya, proses untuk menentukan sistem pelupusan yang sesuai melibatkan pengenalpastian matlamat dan kriteria berdasarkan pilihan yang ada. Ia juga bersifat pertimbangan multi-kriteria yang melibatkan banyak pihak berkepentingan dalam membuat keputusan. Berdasarkan permasalahan tersebut, model multi-kriteria dwikabur konflik diusulkan menggunakan konsep penegasan linguistik (i.i., dilasi dan konsentrasi) dalam proses hierarki analitik (AHP). Model ini diubahsuai menggunakan teori set baru yang diberi nama ‘set dwikabur konflik’. Kajian kes di negeri Selangor dan WPKL dimanfaatkan sepenuhnya untuk menunjukkan kesesuaian model yang diusulkan. Berdasarkan pengiraan yang ditunjukkan, model yang diusulkan dapat menilai kesemua kriteria secara lebih menyeluruh disebabkan sifat ‘timbal balas’ yang dimilikinya. Di samping itu, ia mampu menangani masalah yang bersifat berketaktentuan secara berkesan disebabkan pembuat keputusan boleh menilai secara linguistik sepenuhnya sekaligus memudahkan mereka membuat keputusan dengan lebih cekap dan berkesan. This research focuses on the application of a new fuzzy model for selecting municipal solid waste (MSW) disposal systems which recently has been big burden, particularly in central Peninsular Malaysia. The state of Selangor and Kuala Lumpur Federal Territoring (KLFT) for instance, recorded the highest MSW generation which estimated more than 2.32 million tonnes per year in 2005. Generally, the process to identify the most suitable disposal system involves various criteria and the options. It also involves the multi-criteria consideration from multiple stakeholders in decision process. In view of this problem, the conflicting bifuzzy multi-criteria model was proposed in an analytic hierarchy process (AHP) method using linguistic hedges concepts (i.e., dilation and concentration). This approach was adopted by using the new set theory, namely ‘conflicting bifuzzy set’. A case study in the state of Selangor and KLFT was utilised to demonstrate the applicable of the proposed model. Based on the calculations, the model offers a comprehensive evaluation in order to have on equilibrium characteristics in every single evaluation processes. Besides that, it also deals efficiently with the uncertainty in initial information through fully linguistic approach thus can assist the decision makers to make a better decision in an effective manner

FLOOD MITIGATION MEASRES USING INTUITIONISTIC FUZZY DEMATEL METHOD

Flood is a natural disaster induced by climate change that resulted in the losses of lives, damages to property, and disrupts the daily activities of local community. Thus, the flood mitigation measures are developed to reduce the impact of flood in our country. The aim of this paper is; to propose IF-DEMATEL method and deal with the uncertainty of input data set of flood mitigation measures, and to validate it using sensitivity analysis. Here, this method is used for flood mitigation measures comprise drainage improvements, barriers, wet flood proofing, dry flood proofing, elevation, relocation, and acquisition. A numerical example from the flood control project selection proposed by a researcher which was adopted to show the applicability of the proposed method. The result shows that the flood mitigation measures are placed based on their priority. Although the rank of flood mitigation measures is sensitive to changes based on the weight of criteria but the best measures is remaining unchanged

Fuzzy simple hierarchy analysis for supplier selection decision / Zamali Tarmudi...[et al.]

Supplier selection problem usually involves so many ambiguity components and multi-criteria factors consideration towards achieving more precision decision. Different researchers have various approaches to overcome such problem concern. In this paper, the Fuzzy Simple Hierarchy Analysis (FSHA) was proposed to deal with the ambiguity or vague multi-criteria evaluation process which commonly exists in supplier selection decision. The technique is equipped with the linguistic variables, the so-called linguistic hedges (i.e., dilation and concentration) for decision-makers (DMs) to evaluate the criterion with ease and direct to the attributes based on their expertise and/or experiences. To show the applicability and practicality of the proposed method, the related hypothetical example was adopted. The calculation results show that the proposed method is highly beneficial and offers a unique advantage to deal with the diversified and too ill-defined in terms of input criterion. Therefore, a simple and systematic manner in evaluation process can be derived from the proposed method without loss any information

River quality classification using different distances in k-nearest neighbors algorithm

The practice of river quality classification usually uses Water Quality Index (WQI) to evaluate the WQI values of the river. However, due to huge data collection on river pollution with uncertain water quality parameter values, need to a different approach to classify the river quality. One of the supervised classification algorithms known as K-Nearest Neighbors (KNN) seems to give new approach for river quality classification where each data points are classified according to the k number or the closest data points neighbors. Therefore, the purpose of this paper is to apply different distances and distance-weighted in KNN for finding the most accurate river quality classification. The accuracy results are compared with Support Vector Machine (SVM) and Decision Tree (DT) algorithms. This KNN algorithm will give a different approach in classify the river quality

A comparison of unsupervised and supervised machine learning algorithms to predict water pollutions

Clean and safe water is vital for our lives and public health. In recent decades, population growth, agriculture, industries, and climate change have worsened freshwater resource depletion and clean water pollution. Several studies have focused on water pollutions risk simulation and prediction in the presence of pollution hotspots. However, the increase and complexity of big data caused by uncertain water quality parameters led to a new efficient algorithm to trace the most accurate pollution hotspots. Therefore, this study proposes to offer different algorithms and comparative studies using Machine Learning (ML) algorithms. Ten different most widely used algorithms, including unsupervised and supervised ML, will be employed to categorize the pollution hotspots for the Terengganu River. Besides, we also validate algorithms' accuracies by improving and changing each parameter in ML algorithms. Our results list all the accurate and efficient ML algorithms for the classification of river pollutions. These results help to facilitate river prediction using efficient and accurate algorithms in various water quality scenario