Customer purchasing decision: an empirical study among Malaysian hypermarket shoppers / Mohd Najmie Osman...[et al.]

A report by Malaysian Retail Association stated that the estimation on Malaysia Retail Industry Quarterly Growth Rate 2017 was 1.5 % to 5.5% and at the average whole year by 3.9%. In Malaysia, the first hypermarket was Makro Cash & Carry outlet, a company owned by HSV Holding from the Netherland in 1993. This was followed by other hypermarkets such as Carrefour, Giant, Tesco, AEON Big and Mydin. The objective of the research was to identify the variables that would aid in developing better understanding of the dynamics hypermarket customer purchasing decision. Location, price, promotion, and variety of products represent the independent variables. 100 questionnaires were distributed to respondents that shopped at a particular hypermarket by using purposive sampling method. The data were statistically analyzed for reliability, correlation and multiple regressions. Based on the findings, it was discovered that price, promotion and variety of products have direct influence on customer purchasing decision. The results would help the industry in improving their action by emphasizing on the three independent variables in managing the complex issues of hypermarket customer purchasing decision. In conclusion, this study was carried out to gain a better understanding of the factors that influence customers in the process of making their purchasing decision at hypermarket

KETIDAKSANTUNAN BERBAHASA MELALUI APLIKASI TWITTER DALAM KALANGAN MAHASISWA

Ketidaksantunan merupakan satu strategi ancaman muka pendengar. Ketidaksantunan memberikan implikasi negatif dalam sesuatu komunikasi. Kajian ini dijalankan untuk mengenal pasti kekerapan penggunaan aplikasi Twitter dalam kalangan mahasiswa di Kulliyyah Bahasa dan Pengurusan, UIAM, Pagoh dan menganalisis ketidaksantunan bahasa menggunakan teori Culpeper 1996. Kajian ini menggunakan kaedah gabungan antara kaedah kuantitatif dan kualitatif. Kajian ini mengunakan borang soal selidik dan penganalisisan teori Culpeper (1996). Hasil kajian mendapati bahawa kekerapan penggunaan aplikasi Twitter adalah bertujuan untuk mengetahui isu semasa dan bukan sahaja sebagai medium meluahkan perasaan. Pengadaptasian Teori Culpeper (1996) dalam kajian ini memaparkan bahawa mahasiswa UIAM, Pagoh banyak menggunakan strategi ketidaksantunan positif dalam ujaran. Oleh itu, kajian berkaitan ketidaksantunan berbahasa ini akan memberi ilmu pengetahuan baharu kepada masyarakat berkaitan situasi bahasa Melayu yang sering digunakan semasa berkomunikasi. Kajian ini diharapkan dapat membantu pengkaji lain untuk menjalankan kajian berkaitan ketidaksantunan berbahasa pada masa akan datang

An analysis of finding the best strategies of water security for water source areas using an integrated IT2FVIKOR with machine learning

Worldwide, water security is adversely affected by factors such as population growth, rural–urban migration, climate, hydrological conditions, over-abstraction of groundwater, and increased per-capita water use. Water security modeling is one of the key strategies to better manage water safety and develop appropriate policies to improve security. In view of the growing global demand for safe water, intelligent methods and algorithms must be developed. Therefore, this paper proposes an integrated interval type-2 Fuzzy VIseKriterijumska Optimizcija I Kompromisno Resenje (IT2FVIKOR) with unsupervised machine learning (ML). This includes IT2FVIKOR for ranking and selecting a set of alternatives. Unsupervised machine learning includes hierarchical clustering, self-organizing map, and autoencoder for clustering, silhouette analysis and elbow method to find the most optimal cluster count, and finally Adjusted Rank Index (ARI) to find the best comparison within two clusters. This proposed integrated method can be divided into a two-phase fuzzy-machine learning-based framework to select the best water security strategies and categorize the polluted area using the water datasets from the Terengganu River, one of Malaysia’s rivers. Phase 1 focuses on the IT2FVIKOR method to select five different strategies with five different criteria using five decision makers for finding the best water security strategies. Phase 2 continues the unsupervised machine learning where three different clustering algorithms, namely, hierarchical clustering, self-organizing map, and autoencoder, are used to cluster the polluted area in the Terengganu River. Silhouette analysis is applied along with the clustering algorithms to estimate the number of optimal clusters in a dataset. Then, the ARI is applied to find the best comparison within the original data with hierarchical clustering, self-organizing map, and autoencoder. Next, the elbow method is applied to double-confirm the best clusters for each clustering algorithm. Last, lists of polluted areas in each cluster are retrieved. Finally, this 2-phase fuzzy-Machine learning–based framework offers an alternative intelligent model to solve the water security problems and find the most polluted area

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

An extended Interval Type-2 Fuzzy VIKOR technique with equitable linguistic scales and Z-Numbers for solving water security problems in Malaysia

Interval Type-2 Fuzzy VIseKriterijumska Optimizacija I Kompromisno Resenje (IT2FVIKOR) technique is one of the techniques of Interval Type-2 Fuzzy Multi-Criteria Decision Making (IT2FMCDM), which was developed to solve problems involving conflicting and multiple objectives. Most of the IT2FVIKOR methods are created from linguistic variables based on Interval Type-2 Fuzzy Set (IT2FS) and its generalization, such as Interval Type-2 Fuzzy Numbers (IT2FNs). Recent literature suggests that equitable linguistic scales can offer a better alternative, particularly when IT2FSs have some limitations in handling uncertainty and imbalance. This paper proposes the extended IT2FVIKOR with an equitable linguistic scale and Z-Numbers, where its linguistic scale introduces an equitable balance of positive and negative scales added to the restriction and reliability approach. Different from the typical IT2FVIKOR, which directly utilizes IT2FNs with a positive membership, the proposed method introduces positive and negative membership where each side considers a restriction and reliability approach. Besides, this paper also offers objective weights using fuzzy entropy-based IT2FS to calculate the weights of the extended IT2FVIKOR. The obtained solutions would help decision makers (DMs) identify the best solution to enhance water security projects in terms of finding the best strategies for water supply security in Malaysia

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

The presence of vibrionaceae, betanodavirus and iridovirus in marine cage-cultured fish: role of fish size, water physicochemical parameters and relationships among the pathogens

The study determines the presence of Vibrionaceae, Betanodavirus and Iridovirus in marine cage-cultured fish, while identifying the roles of fish size, water physicochemical parameters and relationships among the pathogens itself. Cultured grouper and snapper were randomly sampled from a commercial fish farm between February and December 2014. The total body weight and length of individual fish were measured. The kidney, liver and spleen were sampled for bacteria isolation, while for viral identification, the sample of brain, eye, kidney and spleen were used. Water physicochemical parameters during the sampling activities were also determined. Laboratory results revealed isolations of multiple pathogens including Vibrio alginolyticus, V. vulnificus, Photobacterium damselae subsp. damselae (PD), Nervous Necrosis Virus (NNV) and Iridovirus (IV) at low to high prevalence throughout the study period. The weight of affected groupers ranged between 98 g and 719 g, while snappers between 67 g and 982 g. There was a weak and moderate negative correlation between the grouper’s weight and the presence of NNV (R = −0.3684; P 0.05) difference was noted in the rate of isolated pathogens between groupers and snappers, and between the pathogens affecting snappers. However, detection of IV in groupers was significantly (P < 0.05) higher than V. alginolyticus, V. vulnificus and PD. Isolations of V. vulnificus in groupers showed strong and moderate positive correlations with isolations of PD (R = 0.7069; P < 0.05) and IV (R = 0.6665; P < 0.05), respectively. In snappers, there was strong positive correlation between isolation of V. alginolyticus and NNV (R = 0.7526; P < 0.05). Multivariate analyses showed that water temperature, dissolved oxygen, ammonia, iron and nitrite were the most significant water physicochemical parameters associated with presence of these pathogens

Analyze distribution pattern and relationship of growth behavior of dipterocarp tree species in FRIM / Nur Fatin Amira Zamri

The Geographical Information System (GIS) has been used to analyze the pattern of distribution and behavioral growth of Dipterocarp species in Field 11 at the Forest Research Institute Malaysia (FRIM). Meranti Tembaga, Merawan Jangkang and Chengal are among one of Dipterocarp species found in FRIM and the study focuses on these three trees only. Issues that need to be resolved such as FRIM did not make detailed study of the plant and analyze the pattern of tree distribution have made this study done. The objective of this study is to investigate the distribution of existing Dipterocarp tree species based on the Diameter Breast Height (DBH), to classify the distribution pattern of trees based on Dipterocarp tree species and to study the relationship of Dipterocarp species growth behavior. The study has been through several processes such as design, data collection, geoprocessing, Hotspot analysis (Getis-Ord gi *) in mapping clusters, Spatial Autocorrelation (Moran I) in Spatial and Regression analyzing patterns to study Dipterocarp species growth behavior. GIS provides the advantage of collecting tree data from the database for mapping and extracting reports from analysis carried out in the study. Therefore, the latest data require a better improvement by FRIM to always be up-to-date. As a result, the study indicates the pattern of tree distribution, output of the map pattern and distribution from the report summary generated by analyzing the pattern and knowing the relationship of the main behavior to grow. So, GIS has assisted FRIM in maintaining and making conservation in managing Dipterocarp trees using the approach systemati

The presence of Vibrionaceae, Betanodavirus and Iridovirus in marine cage-cultured fish: Role of fish size, water physicochemical parameters and relationships among the pathogens

The study determines the presence of Vibrionaceae, Betanodavirus and Iridovirus in marine cage-cultured fish, while identifying the roles of fish size, water physicochemical parameters and relationships among the pathogens itself. Cultured grouper and snapper were randomly sampled from a commercial fish farm between February and December 2014. The total body weight and length of individual fish were measured. The kidney, liver and spleen were sampled for bacteria isolation, while for viral identification, the sample of brain, eye, kidney and spleen were used. Water physicochemical parameters during the sampling activities were also determined. Laboratory results revealed isolations of multiple pathogens including Vibrio alginolyticus, V. vulnificus, Photobacterium damselae subsp. damselae (PD), Nervous Necrosis Virus (NNV) and Iridovirus (IV) at low to high prevalence throughout the study period. The weight of affected groupers ranged between 98 g and 719 g, while snappers between 67 g and 982 g. There was a weak and moderate negative correlation between the grouper’s weight and the presence of NNV (R = −0.3684; P < 0.05) and V. vulnificus (R = −0.6451; P < 0.05), respectively. No significant (P > 0.05) difference was noted in the rate of isolated pathogens between groupers and snappers, and between the pathogens affecting snappers. However, detection of IV in groupers was significantly (P < 0.05) higher than V. alginolyticus, V. vulnificus and PD. Isolations of V. vulnificus in groupers showed strong and moderate positive correlations with isolations of PD (R = 0.7069; P < 0.05) and IV (R = 0.6665; P < 0.05), respectively. In snappers, there was strong positive correlation between isolation of V. alginolyticus and NNV (R = 0.7526; P < 0.05). Multivariate analyses showed that water temperature, dissolved oxygen, ammonia, iron and nitrite were the most significant water physicochemical parameters associated with presence of these pathogens

The presence of Vibrionaceae, Betanodavirus and Iridovirus in marine cage-cultured fish: Role of fish size, water physicochemical parameters and relationships among the pathogens

The study determines the presence of Vibrionaceae, Betanodavirus and Iridovirus in marine cage-cultured fish, while identifying the roles of fish size, water physicochemical parameters and relationships among the pathogens itself. Cultured grouper and snapper were randomly sampled from a commercial fish farm between February and December 2014. The total body weight and length of individual fish were measured. The kidney, liver and spleen were sampled for bacteria isolation, while for viral identification, the sample of brain, eye, kidney and spleen were used. Water physicochemical parameters during the sampling activities were also determined. Laboratory results revealed isolations of multiple pathogens including Vibrio alginolyticus, V. vulnificus, Photobacterium damselae subsp. damselae (PD), Nervous Necrosis Virus (NNV) and Iridovirus (IV) at low to high prevalence throughout the study period. The weight of affected groupers ranged between 98 g and 719 g, while snappers between 67 g and 982 g. There was a weak and moderate negative correlation between the grouper’s weight and the presence of NNV (R = −0.3684; P < 0.05) and V. vulnificus (R = −0.6451; P < 0.05), respectively. No significant (P > 0.05) difference was noted in the rate of isolated pathogens between groupers and snappers, and between the pathogens affecting snappers. However, detection of IV in groupers was significantly (P < 0.05) higher than V. alginolyticus, V. vulnificus and PD. Isolations of V. vulnificus in groupers showed strong and moderate positive correlations with isolations of PD (R = 0.7069; P < 0.05) and IV (R = 0.6665; P < 0.05), respectively. In snappers, there was strong positive correlation between isolation of V. alginolyticus and NNV (R = 0.7526; P < 0.05). Multivariate analyses showed that water temperature, dissolved oxygen, ammonia, iron and nitrite were the most significant water physicochemical parameters associated with presence of these pathogens