Remaja bercinta: kajian terhadap tiga jenis sekolah menengah kebangsaan, agama dan agama swasta

Remaja bercinta adalah fenomena percintaan antara dua pasangan berlainan jantina di alam persekolahan. Fenomena remaja bercinta yang tidak terkawal boleh membawa kepada permasalahan gejala sosial remaja seperti lari rumah, buang anak, keruntuhan akhlak, dan lemah dalam pelajaran. Kebanyakan kehidupan zaman remaja dihabiskan di alam persekolahan. Di samping peranan ibu bapa, sekolah adalah tempat yang penting untuk memberi pendidikan berkesan terhadap remaja. Selain daripada memberi penekanan terhadap akademik, sekolah juga bertanggungjawab memberi pendidikan tentang isu percintaan dalam kalangan remaja, agar mereka memahami hakikat bercinta. Oleh itu kajian dilakukan terhadap tiga jenis sekolah menengah; sekolah menengah kebangsaan, sekolah menengah agama dan sekolah menengah agama persendirian bertujuan untuk mengenalpasti sejauhmana remaja bercinta, faktor remaja bercinta dan hubungannya terhadap pencapaian akademik. Sebanyak 431 soal selidik telah diterima dari 6 buah sekolah, 2 sekolah mewakili setiap jenis sekolah. Tiga jenis sekolah ini mempunyai persamaan dari aspek kandungan pembelajaran akademik, persekitaran fizikal seperti kemudahan, sekolah jenis campuran jantina dan guru yang bertauliah. Manakala ia mempunyai perbezaan dari perlaksanaan pendidikan, aktiviti kerohanian dan suasana sekolah yang diwujudkan oleh pihak pengurusan. Hasil dapatan mendapati sekolah menengah agama swasta mempunyai paling kurang peratusan remaja bercinta (<10%) berbanding sekolah menengah agama (50%) dan sekolah menengah kebangsaan (80%). Hasil kajian juga mendapati bahawa remaja bercinta tidak memberi pengaruh terhadap akademik mereka. Kelima-lima faktor seperti diri, rakan, keluarga, media dan internet dikenalpasti mempengaruhi remaja bercinta, bagaimanapun kajian mendapati terdapat perbezaan yang ketara pada jenis sekolah. Hasil kajian dapat disimpulkan bahawa perlaksanaan pendidikan, jenis aktiviti kerohanian dan suasana sekolah sangat mempengaruhi sikap remaja dan secara tidak langsung memberi kesedaran kepada remaja akan hakikat bercinta yang sebenar dan seterusnya menghindarkan mereka terjebak cinta dalam zaman remaja

Using software abstraction to develop an agent based system.

The main contribution of the thesis is to present a systematic process to develop an agent-based system that assists a system developer to construct the required system, through a series of modelling activities, employing several levels of abstraction to show the milestones and produce intermediate deliverables. Current practice emphasises "downstream activities" such as implementation at the expense of "upstream activities" such as "modelling". The research has found that the development process for an agent system consists of three phases: agent system development, agent environment development and agent system deployment. The first and second phases represent an intertwined spiral model. All three phases themselves consist of three stages. Each phase employs different development techniques and each stage uses appropriate models and tools such as problem domain model, agent use cases, scenarios, agent system architecture, plan model and individual agent model.The proposed agent development method is applied to two case studies: a Filtering Agent System and Diabetic Consultation System. Both systems have been implemented and tested. Three distinct ways were used to evaluate the proposed method. First, comparing with the criteria of a methodology. Second, comparing it with the current agent-oriented methodologies. Third, informal observations from a potential user community.In conclusion, the research has demonstrated an effective synthesising process to build a set of agent concepts, development life-cycle and modelling to show a systematic process for developing agent systems. Moreover, by employing a whole host of software abstraction tools and techniques in the process, two benefits accrue: the introduction of more 'up stream' activities as well as placing modelling at the heart of the process. Illustratively, we could say that the modelling presented here does for agent systems what data flow diagram and data entity diagram have done for structured methodologies, i.e. raise the level of abstraction employed

Cheapest Insertion Constructive Heuristic based on Two Combination Seed Customer Criterion for the Capacitated Vehicle Routing Problem

The heuristic method is a well-known constructive method for initialize trail quality solutions in capacitated vehicle routing problem. Cheapest insertion heuristic is a popular construction heuristic known for being fast, producing decent solutions, simple to implement and easy to extend handling complicated constraints. However, in previous work, there was less focus on diverse initial quality solutions. Therefore, this study proposed an extension to the cheapest insertion heuristic which consider various combinations of seed customer criteria (the first customer inserted on a route) to preserve solutions diversification. Three seed customer criteria proposed which based on the combination of two criteria based on (farthest, nearest and random criteria). The best performing criteria selected and tested on benchmark dataset, later compared with Clarke and Wright saving heuristic. The results shown that the combination of (farthest and random) criteria obtained the best initial solution which preserve balance between the quality and diversity, with less time when compared to Clarke and wright saving heuristic. This approach is for generating diverse and quality starting solutions for the capacitated vehicle routing problem

Modified Dynamic Time Warping for Hierarchical Clustering

Time series clustering is the process of grouping sequential correspondences in similar clusters. The key feature behind clustering time series data lies on the similarity/distance function used to identify the sequential matches. Dynamic Time Warping (DTW) is one of the common distance measures that have demonstrated competitive results compared to other functions. DTW aims to find the shortest path in the process of identifying sequential matches. DTW relies on dynamic programming to obtain the shortest path where the smaller distance is being computed. However, in the case of equivalent distances, DTW is selecting the path randomly. Hence, the selection could be misguided in such randomization process, which significantly affects the matching quality. This is due to randomization may lead to the longer path which drifts from obtaining the optimum path. This paper proposes a modified DTW that aims to enhance the dynamic selection of the shortest path when handling equivalent distances. Experiments were conducted using twenty UCR benchmark datasets. Also, the proposed modified DTW result has been compared with the state of the art competitive distance measures which is based on precision, recall and f-measure including the original DTW, Minkowski distance measure and Euclidean distance measure. The results showed that the proposed modified DTW reveal superior results in compared to the standard DTW, either using Minkowski or Euclidean. This can demonstrate the effectiveness of the proposed modification in which optimizing the shortest path has enhanced the performance of clustering. The proposed modified DTW can be used for having good clustering method for any time series data

Water Flow-Like Algorithm with Simulated Annealing for Travelling Salesman Problems

Water Flow-like Algorithm (WFA) has been proved its ability obtaining a fast and quality solution for solving Travelling Salesman Problem (TSP). The WFA uses the insertion move with 2-neighbourhood search to get better flow splitting and moving decision. However, the algorithms can be improved by making a good balance between its solution search exploitation and exploration. Such improvement can be achieved by hybridizing good search algorithm with WFA.  This paper presents a hybrid of WFA with various three neighbourhood search in Simulated Annealing (SA) for TSP problem. The performance of the proposed method is evaluated using 18 large TSP benchmark datasets. The experimental result shows that the hybrid method has improved the solution quality compare with the basic WFA and state of art algorithm for TSP

Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization

Existing face recognition methods utilize particle swarm optimizer (PSO) and opposition based particle swarm optimizer (OPSO) to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO) technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM). In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented