Oc-C-Gen (read: oxy-gen) stands for Occupation Chronology Generation. This project purposes to automatically generate a query-based occupation chronology of a person using Indonesian news data set. After user inputs query and news data set, our system extracts candidate occupation and uses four-factor ranking model to score the most salient occupations of the query person. Our system will process ccupation candidates with the highest score and list them in chronological order.
Shirley Anugrah Hayati. 2016. Penyusunan Riwayat Pekerjaan Menggunakan Metode Linguistik dan Statistik (in Indonesian). Universitas Indonesia, Depok, Indonesia.
Pemuisi is a poetry generation system that generates topical poems in Indonesian using a constraint satisfaction approach. It scans popular news websites for articles and extracts relevant keywords that are combined with various language resources such as templates and other slot fillers into lines of poetry. It then composes poems from these lines by satisfying a set of given constraints
Fam Rashel & Ruli Manurung. Pemuisi: a constraint satisfaction-based generator of topical Indonesian poetry. In Proceedings of International Conference on Computational Creativity (ICCC 2014), Ljubljana, Slovenia.
Part-of-speech tag is a grammatical category for words, such as noun, verb, adjective, etc. Part-of-speech tagging is a process of assigning those part-of-speech tags to words in a text. Doing part-of-speech tagging manually would be a time-consuming duty. That is why automating the process is such a fundamental process in natural language processing.
Fam Rashel, Andry Luthfi, Arawinda Dinakaramani, and Ruli Manurung. Building an Indonesian Rule-Based Part-of-Speech Tagger. International Conference on Asian Language Processing (IALP 2014). Kuching, 20-22 October 2014.
We performed political sentiment analysis on Indonesian microblogs with respect to Indonesian Presidential Election in 2014. We show the popularity, sentiment orientation, as well as topical words of each candidate. Finally, we present the information using several fancy graphical tools.
Mochamad Ibrahim, Omar Abdillah, Alfan Farizki Wicaksono, Mirna Adriani. Buzzer Detection and Sentiment Analysis for Predicting Presidential Election Results in A Twitter Nation SOMERA 2015 (in conjunction with the IEEE International Conference on Data Mining 2015)
Emotion Map is an application that shows people's emotion (happy, sad, love, angry, and fear) around Jakarta. Currently, we still use static data consisting of 600 tweets crawled on Saturday, 7th Feb. 2015. This application was developed based on our research published in the following paper:
Johanes Effendi The, Alfan Farizki Wicaksono, Mirna Adriani A Two-Stage Emotion Detection on Indonesian Tweets In Proceedings of the International Conference on Advanced Computer Science and Information Systems (ICACSIS 2015)