Dewi Wisnu Wardani
Sebelas Maret University (UNS) Surakarta, Indonesia

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Jurnal Sistem Informasi Vol 5 No 2 (2009): Jurnal Sistem Informasi (Journal of Information System)
Publisher : Faculty of Computer Science Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1125.142 KB) | DOI: 10.21609/jsi.v5i2.264


The current researches on question answer usually achieve the answer only from unstructured text resources such as collection of news or pages. According to our observation from Yahoo!Answer, users sometimes ask in complex natural language questions which contain structured and unstructured features. Generally, answering the complex questions needs to consider not only unstructured but also structured resource. In this work, researcher propose a new idea to improve accuracy of the answers of complex questions by recognizing the structured and unstructured features of questions and them in the web. Our framework consists of three parts: Question Analysis, Resource Discovery, and Analysis of The Relevant Answer. In Question Analysis researcher used a few assumptions and tried to find structured and unstructured features of the questions. In the resource discovery researcher integrated structured data (relational database) and unstructured data (web page) to take the advantage of two kinds of data to improve and to get the correct answers. We can find the best top fragments from context of the relevant web pages in the Relevant Answer part and then researcher made a score matching between the result from structured data and unstructured data, then finally researcher used QA template to reformulate the questions. Penelitian yang ada pada saat ini mengenai Question Answer (QA) biasanya mendapatkan jawaban dari sumber teks yang tidak terstruktur seperti kumpulan berita atau halaman. Sesuai dengan observasi peneliti dari pengguna Yahoo!Answer, biasanya mereka bertanya dalam natural language yang sangat kompleks di mana mengandung bentuk yang terstruktur dan tidak terstruktur. Secara umum, menjawab pertanyaan yang kompleks membutuhkan pertimbangan yang tidak hanya sumber tidak terstruktur tetapi juga sumber yang terstruktur. Pada penelitian ini, peneliti mengajukan suatu ide baru untuk meningkatkan keakuratan dari jawaban pertanyaan yang kompleks dengan mengenali bentuk terstruktur dan tidak terstruktur dan mengintegrasikan keduanya di web. Framework yang digunakan terdiri dari tiga bagian: Question Analysis, Resource Discovery, dan Analysis of The Relevant Answer. Pada Question Analysis peneliti menggunakan beberapa asumsi dan mencoba mencari bentuk data yang terstruktur dan tidak terstruktur. Dalam penemuan sumber daya, peneliti mengintegrasikan data terstruktur (relational database) dan data tidak terstruktur (halaman web) untuk mengambil keuntungan dari dua jenis data untuk meningkatkan dan untuk mencapai jawaban yang benar. Peneliti dapat menemukan fragmen atas terbaik dari konteks halaman web pada bagian Relevant Answer dan kemudian peneliti membuat pencocoka skor antara hasil dari data terstruktur dan data tidak terstruktur. Terakhir peneliti menggunakan template QA untuk merumuskan pertanyaan.
Semantic Commerce for Developing Country Wardani, Dewi Wisnu
IJID (International Journal on Informatics for Development) Vol 1, No 1 (2012): IJID May
Publisher : Universitas Islam Negeri Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (397.041 KB) | DOI: 10.14421/ijid.2012.01103


The recent real challenges of semantic technology is not in the core of the technology but much more in implementing the semantic technology in the real problem. The common domain in any world is economics. One of the most important domain in economics is marketing. Company moreover small company from developing country desperated in increasing to make their company's product are known wider, around the world as well. Product from developing countries usually has a good quality, unique and cheaper but lack to be known. This paper present idea how semantic technology will give a benefit in marketing strategies for business in developing countries. The short goal is how the common famous search engine will be more understand the company both product and profile, thus present those information in better form and possible to the next processing in the others semantic technology.
FoFA: Diet Information for Children with Autism with Semantic Technology in Android Based Application Febrianto, Lutfi Aristian; Wardani, Dewi Wisnu; Wijayanto, Ardhi
JOIN (Jurnal Online Informatika) Vol 5, No 2 (2020)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v5i2.615


The number of people with autism in Indonesia increases by 0.15% or 6,900 children per year. One of the actions that can be done to overcome developmental disorders of children with autism is to do Feingold and Failsafe Diet, Specific Carbohydrate Diet (SCD diet), and Casein-Free Gluten Free diet (CFGF diet) on foodstuffs given to children with autism. There is a need for socialization and presentation of information regarding the regulation of food items given to children with autism. Currently, there is no presentation of information in the form of mobile-based applications as a forum for parents to exchange information, especially those that utilize semantic technology. By utilizing semantic technology, the Food For Autism (FoFA) application was created to share knowledge for users related to food and beverage diet menus for children with autism. The test results show that the application of FoFA can apply semantic technology related to diet and food diets for children with autism.