Artificial Neural Network Model for Affective Environmental Control System in Food SMEs

This paper presents an affective environmental control system for Small and Medium-sized Enterprises (SMEs). The system is proposed as a technology innovation in appropriate information technology. It is defined that workplace environment set points could be controlled using worker workload. The research objectives are: 1) To design an affective environmental control model for SME; 2) To develop an Artificial Neural Network (ANN) model for predicting affective environment set points. The system consisted of 4 sub-systems as measurement, assessment, control and decision. An ANN model is developed for sub-systems of control. Training and validation data are acquired from 4 (four) samples of SME in Yogyakarta Special Region, Indonesia. The model has been developed successfully to predict temperature and light intensity set points using back-propagation supervised learning method. The research results indicated the satisfied performance of ANN with minimum error. ANN model indicated the closeness of R2 value between training and validation data. The research results could be applied to support the worker productivity in food SMEs by providing a comfort workplace environment and optimum worker workload

An Optimization Model for Environmental Ergonomics Assessment in Bioproduction of Food SMEs

Environmental ergonomics in bioproduction of food Small Medium-sized Enterprises (SMEs) become a concern and need to be optimized. An optimization model was developed using a Genetic Algorithm (GA). The weight of an Artificial Neural Network Model was used as a fitness function for GA. The research objectives were: 1) To design an environmental ergonomic assessment system for bioproduction of Food SMEs, 2) To develop an optimization model for environmental ergonomic assessment using a Genetic Algorithm. GA is utilized to search optimal set points of environmental ergonomics based on the predicted fitness values. Each chromosome of GA represents the environmental ergonomics value. The parameters were heart rate, bioproduction temperature, distribution of bioproduction relative humidity and light intensity. The target of the optimization model was the bioproduction temperature set points. The research result indicated the model generated optimum values of environmental ergonomics parameter in bioproduction of food SMEs. The parameters could be used to provide standard workplace environment for the sustainability of food SMEs

An Intelligent Incentive Model Based on Environmental Ergonomics for Food SMEs

In this study, an intelligent incentive model based on environmental ergonomics in food small and medium-sized enterprises (SMEs) was developed. Environmental ergonomics was defined as the impact of temperature and relative humidity within a certain range on a worker's heart rate during work. Optimum environmental ergonomics are highly required as a basic standard for food SMEs to provide fair incentives. Recommendable parameters from a genetic algorithm and fuzzy inference modeling were used to model customized incentives based on optimum heart rate, workplace temperature and relative humidity before and after working. The research hypothesis stated that industries should optimize their workload and workstation environment prior to customizing incentives. The research objectives were: 1) to recommend optimum environmental ergonomics parameters for customized incentives; 2) to determine the incentives at workstations of SMEs based on optimum environmental ergonomics parameters and fuzzy inference modeling. The optimum values for heart rate, workstation temperature and relative humidity used were based on recommendable values from the genetic algorithm. An inference model was developed to generate decisions whether a worker should receive an incentive based on a calculated index. The results indicated that 84.4% of workers should receive an incentive. The results of this research could be used to promote the concept of ergonomics-based customized incentives

Development of Green-Affective Work System for Food SMEs

Work system of food Small and Medium-sized Enterprises (SMEs) is influenced by various factors as worker performance, characteristics of raw material, value-added process and workplace environmental ergonomics. Green-affective design analyzes properties of work systems and how these technical attributes could be sensible to the environment (Green) and worker (Affective). The research objectives were: 1) To explore the relationship between green and affective parameters in work systems of Food SMEs; 2) To design a green-affective work system for Food SMEs. Six (6) SMEs of different food products were used for the case studies as Crackers, Nuggets, Fish Chips, Bakpia, Tempe and Herbal Instant Beverages. Air conditioner was suggested to set the temperature set points for controlling environmental ergonomics. Green parameters were analyzed using calculation of air conditioner electricity cost at different workplace temperature set point. Affective parameters were analyzed using heart rate, worker energy consumption and rowan incentive plan. Research findings indicated air conditioner could be used to control environmental ergonomics based on the satisfied temperature set points and efficient electricity cost in work system of food SMEs. Keywords: Air Conditioner; Environmental Ergonomics; Heart Rate; Rowan Incentive Pla

A rapid classification of wheat flour protein content using artificial neural network model based on bioelectrical properties

A conventional technique of protein analysis is laborious and costly. One rapid method used to estimate protein content is near infrared spectroscopy (NIRS), but the cost is relatively expensive. Therefore, it is necessary to find a cheaper alternative measurement such as measuring the bioelectrical properties. This preliminary study is a new rapid method for classified modeling of wheat flour protein content based on the bioelectrical properties. A backpropagation artificial neural network (ANN) was developed to classify the protein content of wheat flour. ANN input were bioelectrical properties, namely capacitance, and resistance and output was a type of the flour, namely hard, medium and soft flour. The result showed that the ANN model could classify the various type of flour. The best ANN model produces a mean square error (MSE) and regression correlation (R) of 0.0399 and 0.9774 respectively. This ANN model could classify the protein content of wheat flour based on the bioelectrical properties and have the potential to be used as a basic instrument to estimate the protein content

The doctoral research abstracts Vol:1 2012 / Institute of Graduate Studies, UiTM

Foreword: Congratulations to Institute of Graduate Studies on the 1st issue of The Doctoral Research Abstracts. This inaugural issue consists of 40 abstracts from our PhD graduands receiving their scrolls in the UiTM’s 76th Convocation. This convocation is very significant especially for UiTM since we are celebrating the success of 40 PhD graduands from 12 of the university’s 25 faculties – the largest number ever conferred at any one time. To the 40 doctorates, I would like it to be known that you have most certainly done UiTM proud by journeying through the scholastic path with its endless challenges and impediments, and by persevering right till the very end. Let it remain in your thoughts and hearts that knowledge is Godgiven, and for those of us who have some to spare, never fear to share with those around us, and never be sparing in serving the community and the country, in the name of the Almighty. Dato’ Prof Ir Dr Sahol Hamid Bin Abu Bakar , FASc Vice Chancellor Universiti Teknologi MAR

Proceedings of the 2nd Conference on Production Systems and Logistics (CPSL 2021)

Proceedings of the CPSL 202

The doctoral research abstracts. Vol:7 2015 / Institute of Graduate Studies, UiTM

Foreword: The Seventh Issue of The Doctoral Research Abstracts captures the novelty of 65 doctorates receiving their scrolls in UiTM’s 82nd Convocation in the field of Science and Technology, Business and Administration, and Social Science and Humanities. To the recipients I would like to say that you have most certainly done UiTM proud by journeying through the scholastic path with its endless challenges and impediments, and persevering right till the very end. This convocation should not be regarded as the end of your highest scholarly achievement and contribution to the body of knowledge but rather as the beginning of embarking into high impact innovative research for the community and country from knowledge gained during this academic journey. As alumni of UiTM, we will always hold you dear to our hearts. A new ‘handshake’ is about to take place between you and UiTM as joint collaborators in future research undertakings. I envisioned a strong research pact between you as our alumni and UiTM in breaking the frontier of knowledge through research. I wish you all the best in your endeavour and may I offer my congratulations to all the graduands. ‘UiTM sentiasa dihati ku’ / Tan Sri Dato’ Sri Prof Ir Dr Sahol Hamid Abu Bakar , FASc, PEng Vice Chancellor Universiti Teknologi MAR

Validation of Perceived Ability in Statistical concepts Questionnaire (PASQ) Based on Rasch Measurement Model

This paper describes the process of assessing the unidimensionality and validity of the Perceived Ability in Statistical Concepts Questionnaire (PASQ) based on the Rasch Measurement Model. Students’ perceived ability was measured by a self-developed 30 PASQ items of Likert-scale format comprises of concepts on types of data (6 items), graphical representations of distributions (8 items), measures of central tendency (8 items), and measures of variability (8 items). The process of assessing the validity of PASQ involved a collection of data from 416 students at four institutions of higher learning in Malaysia where the measurement of construct validity for the overall PASQ and its subscales were established using Winsteps 3.68.2. Various Rasch measurement tools were utilized to demonstrate the true unidimensionality and validity measure of the PASQ and in meeting the needs of the Rasch measurement model. The findings show that the validity and unidimensionality of PASQ can be truly established and can satisfy the characteristics of the Rasch measurement model