Mekanisme pengurusan hutang dalam pembahagian harta pusaka orang-orang Islam di Malaysia

Pengurusan hutang merupakan tanggungjawab setiap individu untuk melangsaikannya. Namun masyarakat Islam di Malaysia kini memandang ringan mengenai tanggungjawab pengurusan hutang dalam menguruskan harta pusaka sehingga mengakibatkan timbulnya isu harta beku yang semakin meningkat peratusannya setiap tahun. Pengabaian menguruskan penyelesaian hutang dalam harta pusaka boleh berlaku disebabkan beberapa faktor antaranya, kedudukan dan status hutang si mati yang tidak jelas dan faktor daripada sikap tidak prihatin di kalangan ahli waris atau pentadbir yang dilantik menguruskan harta si mati. Salah satu faktor fenomena ini berlaku disebabkan ketidakfahaman pentadbir atau ahli waris terhadap prosedur di agensi pengurusan harta pusaka termasuk hal mekanisme untuk menyelesaikan hutang peninggalan si mati. Justeru itu, kajian ini bertujuan mengenal pasti prosedur pengurusan hutang si mati dalam pembahagian harta pusaka. Oleh itu, pengumpulan data dengan penggunaan kaedah kualitatif melalui kaedah temu bual dan analisis dokumen daripada fail kes digunakan di dalam kajian ini. Hasil kajian mendapati agensi pengurusan harta mempunyai bidang kuasa tertentu dalam menguruskan hutang peninggalan si mati bergantung kepada jenis dan kedudukan status harta dan hutang. Selain itu, didapati pengurusan hutang peninggalan si mati didapati lebih kompeten dikendalikan oleh Unit Pembahagian Pusaka Kecil (UPPK) manakala Amanah Raya Berhad pula lebih memainkan peranan sebagai Pentadbir harta pusaka si mati manakala Mahkamah Syariah pula lebih kompeten dalam urusan pengesahan ahli waris melalui perintah serta penentuan kadar bahagian ahli waris masing-masing termasuk Baitulmal. Beberapa cadangan turut dikemukakan di dalam kajian ini bagi meningkatkan pengetahuan umat Islam terhadap permasalahan hutang dalam harta pusaka dan meningkatkan perkhidmatan agensi-agensi yang berkenaan di Malaysia

Whom to Ask? Jury Selection for Decision Making Tasks on Micro-blog Services

It is universal to see people obtain knowledge on micro-blog services by asking others decision making questions. In this paper, we study the Jury Selection Problem(JSP) by utilizing crowdsourcing for decision making tasks on micro-blog services. Specifically, the problem is to enroll a subset of crowd under a limited budget, whose aggregated wisdom via Majority Voting scheme has the lowest probability of drawing a wrong answer(Jury Error Rate-JER). Due to various individual error-rates of the crowd, the calculation of JER is non-trivial. Firstly, we explicitly state that JER is the probability when the number of wrong jurors is larger than half of the size of a jury. To avoid the exponentially increasing calculation of JER, we propose two efficient algorithms and an effective bounding technique. Furthermore, we study the Jury Selection Problem on two crowdsourcing models, one is for altruistic users(AltrM) and the other is for incentive-requiring users(PayM) who require extra payment when enrolled into a task. For the AltrM model, we prove the monotonicity of JER on individual error rate and propose an efficient exact algorithm for JSP. For the PayM model, we prove the NP-hardness of JSP on PayM and propose an efficient greedy-based heuristic algorithm. Finally, we conduct a series of experiments to investigate the traits of JSP, and validate the efficiency and effectiveness of our proposed algorithms on both synthetic and real micro-blog data.Comment: VLDB201

Time-aware topic recommendation based on micro-blogs

Topic recommendation can help users deal with the information overload issue in micro-blogging communities. This paper proposes to use the implicit information network formed by the multiple relationships among users, topics and micro-blogs, and the temporal information of micro-blogs to find semantically and temporally relevant topics of each topic, and to profile users' time-drifting topic interests. The Content based, Nearest Neighborhood based and Matrix Factorization models are used to make personalized recommendations. The effectiveness of the proposed approaches is demonstrated in the experiments conducted on a real world dataset that collected from Twitter.com

A Data-driven Study of Influences in Twitter Communities

This paper presents a quantitative study of Twitter, one of the most popular micro-blogging services, from the perspective of user influence. We crawl several datasets from the most active communities on Twitter and obtain 20.5 million user profiles, along with 420.2 million directed relations and 105 million tweets among the users. User influence scores are obtained from influence measurement services, Klout and PeerIndex. Our analysis reveals interesting findings, including non-power-law influence distribution, strong reciprocity among users in a community, the existence of homophily and hierarchical relationships in social influences. Most importantly, we observe that whether a user retweets a message is strongly influenced by the first of his followees who posted that message. To capture such an effect, we propose the first influencer (FI) information diffusion model and show through extensive evaluation that compared to the widely adopted independent cascade model, the FI model is more stable and more accurate in predicting influence spreads in Twitter communities.Comment: 11 page

The Usage of Personal Data as Content in Integrated Marketing Communications

Personal user data has proven extremely valuable for firms in the digital age. The wealth of data available to firms has provided unprecedented access into the world of the consumer. Companies hoping to capitalize on their user's data have turned to several interesting outlets. This research addresses the repurposing of user data as content in marketing. By analyzing four cases of data presented as marketing communications across two companies, this research provides new insights into the public release of private user data for marketing purposes. Four cases of personal data used in marketing communications were chosen specifically for their time proximity, characteristics of the sending firms, and their disparate outcomes. These instances of marketing communications, two by Spotify and two by Netflix, were released during November and December of 2017 and each resulted in a diverse range of public opinion. An analysis of these cases was conducted using the comprehensive framework of integrated marketing communications (Tafesse & Kitchen, 2017). There is a significant difference in the perceptual outcomes of integrated marketing communication campaigns which display user data as content. This analysis provides insights into the characteristics of marketing communications and how their outcomes fit into broader marketing strategies. These case studies provide opportunities for marketers to improve their campaigns in line with their desired audience outcome. Patterns of scope, strategy, mode, and outcome do not suggest success or failure in the context of marketing communications, but rather a set of insights marketers should keep in mind when pursuing communication strategies which harness personal user data.No embargoAcademic Major: Marketin