NUS BBA 01 May 2018

Students winning with data analytics

The Department of Analytics & Operations (DAO) recently held an end-of-semester showcase of the Poster Competition for NUS BBA year 3 and year 4 taking related modules. 16 teams participated in the competition to present recommendations or solutions to real business challenges.

The department’s Associate Professor Jussi Keppo, Assistant Professor Hu Zhenyu, Senior Lecturer Qi Mei and Visiting Professor Sheryl Kimes were the judges. They assessed the posters in terms of their practicality and clarity. The four faculty also judged the students on how well they could articulate their projects.

Due to the high quality of posters, the judges decided to award two teams the first prize and another two teams the second prize. Professor Melvyn Sim, Head of Department, gave away the prizes to the winning teams.

The team with project instructor Asst Prof He Long (left)

Students Lim Wei Yang Jerome, Chew Anzhen Benjamin, Lam Sze Ting, Teoh Ean Xiang and Qiu Yitong won the first prize with their project on enhancing facial recognition using data mining algorithms.

The team with project instructor Asst Prof He Long (left)

The other co-winning team (Caitlin Holly Cranmer, Chan Medric, Liew Jian Bin and Wang Yushan) for the first price also used data mining algorithms to gain insights on the factors that lead to employees leaving their organisations.

Each team won a SG$500 voucher, while the second-place teams won SG$250 each.

The team with project instructor Asst Prof He Long (right)

Second place winners Ang Peng Seng, Ang Wei Xuan, Leon Tham, Simon Hung, Vanessa Yap built a methodology that can determine what makes movies profitable and popular. The students say this would help studios make better investment choices, actors choose “better” films and even build a recommendation system for websites (Netflix) to recommend movies.

Co-second place winners Goh Jie Da, Ching Wee Keat Patrick, George Ng, and Nguyen Phuong Nhu built a model that can predict whether a new Airbnb user will be active or inactive, and in the long run help boost Airbnb’s general competitiveness.

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