Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes

Value stream mapping to reduce the lead-time of a product development process

Product development (PD) is a broad field of endeavor dealing with the planning, design, creation, and marketing of a new product. This revolutionary research domain has become of paramount importance to beat the competition for multidisciplinary products which are larger in size and have a longer development time. The main focus of this paper is to exploit lean thinking concepts in order to manage, improve and develop the product faster while improving or at least maintaining the level of performance and quality. Lean thinking concepts encompass a board range of tools and methods intended to produce bottom line results however, value stream mapping (VSM) method is used to explore the wastes, inefficiencies, non-valued added steps in a single, definable process out of complete product development process (PDP). This single step is highly complex and occurs once while the PDP lasts for 3-5 years. A case study of gas turbine product has been discussed to illustrate and justify the use of proposed framework. In order to achieve this, the following have been performed: First of all a current state map is developed using the Gemba walk. Furthermore, Subject Matter Experts (SMEs) brainstormed to explore the wastes and their root causes found during the Gemba walk and current state mapping. A future state map is also developed with removing all the wastes/inefficiencies. Besides numerous intangible benefits, it is expected that the VSM framework will help the development teams to reduce the PD lead-time by 50%

The use of Bayesian networks to determine software inspection process efficiency

Adherence to a defined process or standards is necessary to achieve satisfactory software quality. However, in order to judge whether practices are effective at achieving the required integrity of a software product, a measurement-based approach to the correctness of the software development is required. A defined and measurable process is a requirement for producing safe software productively. In this study the contribution of quality assurance to the software development process, and in particular the contribution that software inspections make to produce satisfactory software products, is addressed. I have defined a new model of software inspection effectiveness, which uses a Bayesian Belief Network to combine both subjective and objective data to evaluate the probability of an effective software inspection. Its performance shows an improvement over the existing published models of inspection effectiveness. These previous models made questionable assumptions over the distribution of errors and were essentially static. They could not make use of experience both in terms of process improvement and the increased experience of the inspectors. A sensitivity analysis of my model showed that it is consistent with the attributes which were thought important by Michael Fagan in his research into the software inspection method. The performance of my model show that it is an improvement over published models and over a multiple logistic regression model, which was formed using the same calibration data. By applying my model of software inspection effectiveness before the inspection takes place, project managers will be able to make better use of inspection resource available. Applying the model using data collected during the inspection will help in estimation of residual errors in a product. Decisions can then be made if further investigations are required to identify errors. The modelling process has been used successfully in an industrial application

Penerapan Six Sigma Untuk Perbaikan Masalah Kepadatan Dan Kemacetan Workstation Gudang Ekspor Di Perusahaan Cargo Handling Bandara Soekarno Hatta

Pengangkutan kargo melalui pesawat udara merupakan salah satu rantai distribusi barang yang memerlukan biaya dan juga standar keselamatan yang tinggi. PT Jasa Angkasa Semesta (JAS) merupakan salah satu perusahaan ground handling di Bandara Internasional Soekarno Hatta yang salah satu unit usahanya adalah penanganan kargo di gudang ekspor. Salah satu proses di gudang ekspor adalah proses menaikkan kargo ke dalam Unit Load Device (ULD) atau biasa disebut proses build up yang dilakukan di workstation. Kepadatan dan kemacetan sering terjadi di workstation dan akibatnya proses build up, proses penimbangan, pelaporan dan penarikan kargo ke pesawat menjadi terhambat. Penelitian terhadap kepadatan dan kemacetan di workstation bertujuan untuk memecahkan masalah di workstation. Penelitian ini menggunakan metode six sigma DMAIC (Define, Measure, Analyze, Improve dan Control) untuk memecahkan masalah. Dalam tahap define dimulai dengan membuat project charter dan menentukan tim yang akan terlibat. Pada tahap measure menunjukkan bahwa level sigma pada workstation berada pada σ = 3.18. Analisis dilakukan dengan menggunakan metode fishbone dan menunjukkan bahwa penyebab utama dari masalah kepadatan dan kemacetan adalah kapasitas workstation dan penjadwalan build up. Untuk tahap improvement dilakukan dengan melakukan brain storming untuk melakukan perbaikan dan control dilakukan untuk memastikan bahwa improvement yang dibuat akan selalu sesuai harapan. Hasil penerapan penjadwalan, dengan perbandingan hari ke hari, kepadatan dapat berkurang sebesar 28% dan hasil perbaikan penurunan defect sebesar 8.7%. ======================================================================================================== Air cargo transportation is one of goods distribution with high cost and high safety standard. PT Jasa Angkasa Semesta (JAS) is one of ground handling company in Soekarno Hatta International Airport where one of its businesses is cargo handling in export warehouse. One of the processes in the export warehouse is loading cargo into Unit Load Device (ULD) or build up in the workstation. Bottleneck often occurs in the workstation and it affects the build up process, weighing process, reporting, and cargo towing to the aircraft is late. The research was aiming to solve the problem in the workstation. The research used six Sigma DMAIC (Define, Measure, Analyze, Improve, and Control) methodologies to solve the problem. The define phase roll out the project charter and the team involved. On the measure phase reveals that the sigma level of the workstation was on σ = 3.18. The analysis was conducted using fishbone method and the main causes of the bottleneck were capacity and build up scheduling. On improve phase, brain storming was carried out to solve the issue and capability analysis was made to make sure no recurrence on suggested improvement. The result of Build up scheduling implementation reduced congestion by 28% and yield improvement 8.7%

Application of Artificial Neural Networks to Assess Student Happiness

The purpose of this study is to develop an analytical assessment approach to identify the main factors that affect graduate students\u27 happiness level. The two methods, multiple linear regression (MLR) and artificial neural networks (ANN), were employed for analytical modelling. A sample of 118 students at a small non-profit private university constituted the survey pool. Various factors including education, school facilities, health, social activities, and family were taken into consideration as a result of literature review in happiness assessment. A total of 32 inputs and one output variables were identified during survey design phase. The following survey conduction, data collection, cleaning, and preparation; MLR and ANNs were built. ANN models provided better classification performance with over 0.7 R-square and a smaller standard error of estimate compared to MLR. Major policy areas to improve student happiness levels were identified as career services, financial aid, parking and dining services

The doctoral research abstracts. Vol:8 2015 / Institute of Graduate Studies, UiTM

Foreword: THIRTY FIRST October 2015 marks the celebration of 47 PhD doctorates receiving their scroll during UiTM 83rd Convocation Ceremony. This date is significant to UiTM since it is an official indication of 47 more scholarly contributions to the world of knowledge and innovation through the novelty of their research. To date UiTM has contributed 471 producers of knowledge through their doctoral research ranging from the field of Science and Technology, Business and Administration, and Social Science and Humanities. This Doctoral Abstracts epitomizes knowledge par excellence and a form of tribute to the 47 doctorates whose achievement we proudly celebrate. To the graduands, your success in achieving the highest academic qualification has demonstrated that you have indeed engineered your destiny well. The action of registering for a PhD program was not by chance but by choice. It was a choice made to realise your self-actualization level that is the highest level in Maslow’s Hierarchy of Needs, while at the same time unleashing your potential in the scholarly research. Do not forget that life is a treasure and that its contents continue to be a mystery, thus, your journey of discovery through research has not come to an end but rather, is just the beginning. Enjoy life through your continuous discovery of knowledge, and spearhead innovation while you are at it. Make your alma mater proud through this continuous discovery as alumni of UiTM. As you soar upwards in your career, my advice will be to continuously be humble and ‘plant’ your feet firmly on the ground. Congratulations once again and may you carry UiTM as ‘Sentiasa di Hatiku’. Tan Sri Dato’ Sri Prof Ir Dr Sahol Hamid Abu Bakar, FASc, PEng Vice Chancellor Universiti Teknologi MAR

Tight bounds on the size of neural networks for classification problems

This paper relies on the entropy of a data-set (i.e., number-of-bits) to prove tight bounds on the size of neural networks solving a classification problem. First, based on a sequence of geometrical steps, the authors constructively compute an upper bound of O(mn) on the number-of-bits for a given data-set - here m is the number of examples and n is the number of dimensions (i.e., R{sup n}). This result is used further in a nonconstructive way to bound the size of neural networks which correctly classify that data-set

Improving the cost model development process using fuzzy logic

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