Saidatul Rahah Hamidi

The Characteristic and Success Factors of an Organizational Memory Information System

Data, information and knowledge have increased within organization across time. They become wasted memories due to retired staff, died or replace to another department. This could give great impact when intellectual capital do not being used wisely especially as competitive advantage element. Therefore, there is a need to manage memories accordingly. Otherwise, time, money and energy are wasted when the same task, research and findings need to be done repeatedly. This paper discusses the implementation of organizational memory system (OMS) which also known as organizational memory information system (OMIS). Before that, the basic theory of organizational memory (OM) will be described for better understanding. This paper indicates that there are 5 blocks of success factor to evaluate OMIS implementation; system quality, information quality, success measure in terms of usage, individual impact and organizational impact. OMS is proposed as a prototype to be implemented for the whole module of Faculty of Computer Science and Information System in order to protect their intellectual capital and optimizing the efficiency by managing organizational memory. The paper provides details of solution to academic management on the approach to making organizational memory information system work in practice. The approaches to manage memories in the model have yielded a number of benefits as demonstrated by a case study. This work will be beneficial to researchers and practitioner who are interested in applying OMIS in organization.

AUTOMATIC MUSIC EMOTION CLASSIFICATION USING ARTIFICIAL NEURAL NETWORK BASED ON VOCAL AND INSTRUMENTAL SOUND TIMBRES

Detecting emotion features in a song remains as a challenge in various area of research especially in Music Emotion Classification (MEC). In order to classify selected song with certain mood or emotion, the algorithms of the machine learning must be intelligent enough to learn the data features as to match the features accordingly to the accurate emotion. Until now, there were only few studies on MEC that exploit audio timbre features from vocal part of the song incorporated with the instrumental part of a song. Timbre features is the quality of a musical features or sound that distinguishes different types of sound production in human voices and musical instruments such as string instruments, wind instruments and percussion instruments. Most of existing works in MEC are done by looking at audio, lyrics, social tags or combination of two or more classes. The question is does exploitation of both timbre features from both vocal and instrumental sound features helped in producing positive result in MEC? Thus, this research present works on detecting emotion features in Malay popular music using artificial neural network by extracting audio timbre features from both vocal and instrumental sound clips. The findings of this research will collectively improve MEC based on the manipulation of vocal and instrumental sound timbre features, as well as contributing towards the literature of music information retrieval, affective computing and psychology.

Sentiment Analysis for Financial News Headlines using Machine Learning Algorithm

The study covers the implementation of machine learning algorithm approaches in sentiment analysis of Malaysia financial news headlines. This study can be used for stakeholders who want to know about the financial news and seek knowledge or data in the financial world. The data are gained from Malaysia online financial news, which are from Business section of New Straits Times. Our study applies Opinion Lexicon-based algorithm and Naive Bayes algorithm as the method to perform sentiment analysis. This study consists of several phases in pre-processing such as extract data, stop word removal, and stemming to clean the dataset and make it as data preparation before performing the sentiment analysis with the selected machine learning algorithms. In the stop word removal, tm package in R is used to clean the dataset while for stemming process, Snowball stemmer is used to set the data to its root word. Sample outcomes of analysis are explained for both algorithms. The conclusion describes the summation of the study and future works.

SMEs Maturity Model Assessment of IR4.0 Digital Transformation

This paper reports on the revolution of industry that leads to the current industry 4.0 through digital transformation. Industry 4.0 promotes innovation in organising and controlling for the entire value chain life cycle. The advancement of technology become future insights of digital transformation is aimed to have a high-flexibility, high-productivity, and become resource friendly that may provide a new level of human-machine relationship. The research is aimed in understanding the readiness of the Small Medium Enterprise (SME) in Malaysia towards digital transformation of Industry 4.0. Hence, a comparative study of the maturity assessment model towards industry 4.0 had been conducted. The IMPULS maturity assessment model is applied and six dimensions were chosen as our research model. Each dimension is explained, calculated and discussed in this paper. Each dimension is then weighted to refer to the level of readiness. The research uses questionnaires in attaining the data pertaining to the readiness of Malaysian SMEs towards industry 4.0. Next, findings of this research will be able to explain and provide a better understanding of where Malaysian SMEs stand in comparison to the maturity level that is set to test out the readiness of SMEs towards industry 4.0. This is to create and increase SMEs’ market sustainability hence creating or increasing profitability.

Industry 4.0 urban mobility: goNpark smart parking tracking module

Emerging technologies in today worlds have made tremendously evolution in digital smart world. Nowadays, implementation of Internet of Thing (IoT), sensor, seamless data transmission and other advance technology become future insights to Industry 4.0. Moreover, the urban population is currently growing and there is an increasing demand for mobility especially on street parking due to the private motor vehicles usage. In order to create a compassionate city, gearing urban mobility with industry 4.0 shall make efficient transport infrastructure and services as well as meeting the peoples preferences for urban. The aim of this research is to study the different types of smart parking system and vehicle detection technologies that can be used in existing smart parking system. Relevant parking information means allowing drivers to make educated decisions about optimal vehicle used in terms of energy, optimize parking space usage, improve the efficiency of the parking operations and help smoother traffic flow. Hence, in this goNpark smart parking systems application were designed and implemented to guide users to find the available parking space easily and accurately in an open space. goNpark embed real-time visualization using video image processing with interest point detection Scale Invariant Feature Transform (SIFT) as occupancy detection module and Geographic Information System (GIS).

Perceived Risk towards Mobile Banking: A case study of Malaysia Young Adulthood

The advancement of technology and the raise of smart devices ownership in Malaysia has eventually increase the exploration of mobile banking services. Mobile banking has been first commercialized in Malaysia on 2005 and expected to growth. Despite the exponential growth, the mobile banking penetration rate is slow compared to online banking. This study aims to highlight the issues and challenges of mobile banking and to have insight on young adulthood perceived risk towards mobile banking, specifically in Malaysia. In order to support the exploratory study, these risks are surveyed in quantitative study conducted among young adulthood in Malaysia. The self-administered questionnaire distributed through email with 384 respondents indicated that the most impacted facets perceiveed risks are performance risk, following by security risk. The results of this study can be used by the practitioner to address the customer challenges, customer interest and concern for mobile banking service improvement.

Factors Contributing to Internet Abuse in the Workplace: Behaviour in SMEs

The Internet is indispensable in the current working environment; in fact, it has become a standard office facility. Using the Internet for personal use during working hour beyond the acceptable usage levels either using office computer or personal smartphones is still an account of Internet abuse. Internet abuse may lead to productivity loss, security incidents, liability and network congestion which therefore are a serious concern by the employers. Since there is lack of emphasis for research on this area, therefore the aims of this study are statistically to prove existence of Internet abuse and gain better understanding of the phenomenon. There are three objectives of the study: (1) to investigate the employees’ Internet abuse activities, (2) to investigate the relationship between demographic, personality and external factors with the intention to abuse the Internet and (3) to recommend countermeasure to overcome Internet abuse during working hours. This study adopted modified theory of planned behaviour (TPB) as the research model. The study was conducted by distributing questionnaires to employees in three small-medium (SME)-sized organizations in ICT sector located in Kuala Lumpur and Selangor. Further to that, interviews were conducted with higher management, HR, IT and an employee to get more information on the subject. This study would give insight into factors contributing to Internet abuse in the workplace and the Internet abuse activities that the employees engaged in which can then be used to plan adequately and manage the issue. It also can help employees to increase the awareness and possibility of change in behaviour with regard to Internet abuse through sharing the result of this study by the employers in monthly bulletin or incorporating the countermeasure in office policy.

Knowledge Preservation Framework for University's Intellectual Output

Intellectual Output (IO) of a university is often neglected by society whereas it actually possesses a great capacity of universitys knowledge produced by researchers. Knowledge preservation is important for community to be able to access, utilize and improve the knowledge at the same time. Thus, Institutional Repository (IR) of an institution is essential to ensure the knowledge is stored and accessible at anytime. There is no specific technique to preserve knowledge, but with the existence of ontological and taxonomy model can help in modeling the knowledge. The scope of IO in this paper is Universitys IO gained by UiTM Research Innovation Business Unit (RIBU). Taxonomy presented in this paper is derived from RIBUs intellectual output which is expected to help the search and retrieval mechanism for an IR.

Change and Bug Tracking System: Anjung Penchala Sdn. Bhd.

Defects or bugs have been existed as a problem in the system and they are normally inevitable in software development. Most software bugs arise from mistakes and errors made by people in either a programs source code or its technical design. Huge amount of bugs could be found in system development. It was relatively difficult to manage bugs in simple word documents or remember everything in one’s head. Thus Change and Bug Tracking (CBT) System has been introduced in order to keep track of the reported bug in the system. By using this tracking system, every user can report and follow up the issue in the system. This system provided a platform for users from different departments to report issues and understand the latest progress in a product. It consolidated and organized information in single system and centralized data repository for the changes and bugs in system. Besides, this system could be accessed by team members concurrently to improve efficiency and they can search particular information in the system easily. It made communication between teams more effective and all the bugs and changes are recorded in web based system and hence the system is scalable. General Terms Security, system development.