Anik Nur Handayani

Predicting Quality of Answer in Collaborative Q/A Community

Community Question Answering (CQA) services have emerged allowing information seekers pose their information need which is questions and receive answers from their fellow users, also participate in evaluating the questions or answers in a variety of topics. Within this community information seekers could interact and get information from a wide range of users, forming a heterogeneous social networks and interaction between users. A question may receive multiple answers from multiple users and the asker or the fellow users could choose the best answer. Freedom and convenience in participation, led to the diversity of the information. In this paper we present a general model to predict quality of information in a CQA by using non textual features. We showing and testing our quality measurement to a collection of question and answer pairs. In the future our models and predictions could be useful for predictor quality information as a recommender system to complete a collaborative learning.

Question Answering System for an Effective Collaborative Learning

The increasing advances of Internet Technologies in all application domains have changed life styles and interactions. With the rapid development of E-Learning, collaborative learning is an important for teaching, learning methods and strategies. Interaction between the students also student with the teacher is important for student to gain knowledge. Based on the four basic teaching styles formal authority, demonstrator or personal model, facilitator and delegator, today combined between facilitator and delegator style is responsible for student learning. It is student centered and the teacher as facilitates the material and activities, but learning becomes part of valuable and effective when they collaborate with each other, and as the teacher who will delegates and facilitates the responsibility of learning to the students. In this paper, we introduce an effective question answering Q&A system for collaborative learning, which can act not just like a virtual teacher, but also virtual discussion for student. With the proposed system, brings a new Q&A system, student can attach their question when they want collaborate using collaborative learning capitalize on one anothers resources and skills. Students can ask their questions to the group when they want to collaborate with others, asking one another for information, evaluating one anothers ideas, then each of the answer will compare with encyclopedia data base. In this research, the Q&A system for the Senior High School in Indonesia, in this subject of Information Communication Technology implemented. From the the 40 question and 120 answer, the result is 90,48% precision 50% recall.

Developing portable instrument based on Internet of Things for Air Quality Information System

This paper describes the proposed system, which is able to monitor, record and give indicator about air quality information especially the CO values in the environment. The system is designed to work real time using web-based and android applications. A portable gas detector was developed using micro controller. In order to detect the CO value, TGS2600 is used; here an additional function is added by using a thermal sensor to detect the temperature in the environment. Furthermore, a WiFi module is attached to the micro controller to send the data and communicate with the web-based server. The advantage of the proposed system is that, the users can monitor, record and get a warning about the CO value portably. Moreover, the user can also setup the threshold level of each parameter. The proposed system was to be tested using by Black-box method to test the functionality. The results showed that the system runs well with 0% error and can show the CO and temperature values in real time.

Vocational high school student’s readiness to work in internet service provider enterprise: Based on mastery vocational competence, internship and job interest

Work readiness of graduate students of vocational high school (SMK) can be influenced by successful learning in school and implementation of field industrial practice in business world/ industry world. One of indicators that shows work readiness of graduate students of Expertise Package of Computer Network Engineering (TKJ) in Internet Service Provider (ISP) enterprise can be seen from achievement of vocational competence, implementation of field industrial practice, and students’ work interests. This research uses quantitative approach. Sampling technique that is used is proportional random sampling by 205 0f 420 students of XI grade of SMK expertise package TKJ as samples. Research data collection for implementation of field industrial practice variable, students’ work interests variable, and work readiness in ISP enterprise variable done using questionnaires, while for achievement of competence network server administration skill uses score documentation. Data analysis that is used to the test hypothes...

Predicting Quality of Answer in Collaborative Question Answer Learning

Studies over the years shown that students had actively and more interactively involved in a classroom discussion to gain their knowledge. By posting questions for other participants to answer, students could obtain several answers to their question. The problem is sometimes the answer chosen by student as the best answer is not necessarily the best quality answer. Therefore, an automatic recommender system based on student activity, may improve these situations as it will choose the best answer objectively. On the other side, in the implementation of collaborative learning, in addition to sharing information, sometimes students also need a reference or domain knowledge which relevant with the topic. In this paper, we proposed answer quality predictor in collaborative question answer (CQA) learning, to predict the quality of answer either from recommender system based on users activity or domain knowledge as reference information.

E-Learning System Utilizing Learners’ Characteristics Recognized Through Learning Processes with Open Simulator

E-learning system utilizing learners’ characteristics which is recognized through learning processes with Open Simulator for overcoming week points is proposed. Through dialogs with avatars in the Open Simulator, it is possible to understand learners’ week points. Using learners’ characteristics, most appropriate subjects and achievement tests are provided by the proposed e-learning system. Experimental results show that the proposed e-learning system is much effective than the conventional e-learning system without utilizing learners’ characteristics.