Sri Suning Kusumawardani

Statistical-based machine translation for prepositional phrase using Link Grammar

The Internet provides most information in English language. However, most people are non-English speaker. Hence, it will be a great advantage for the people to have reliable machine translation. The expectation from the Machine Translation (MT) is sentences translation in a natural way based on the contexts.

Developing Academic Executive Information System Uses Kimball Methodology: Case Study in an Indonesia Higher Education System

Muhammadiyah University of Magelang (UMM) has integrated academic information systems in terms of both data and applications. This system has been constructed 6 years ago and has been used by the service level to the policy level. However, until today, there is no data can be presented in an appropriate format for the decision-maker, since the data are functionally separated. In addition, reporting data is not easily used by decision-makers because it does not apply the concept of the data warehouse. So that the information can be used by decision-makers, the data warehouse must be constructed using appropriate methods. In this paper, Kimball methodology is chosen because the design starts from user needs. The methodology causes the system to be able to present complete and appropriate data presentation as well as the user wants. UMM Academic Executive Information System (EIS) has been successfully constructed using the data warehouse. As a result, the system is able to present the integrated data and is able to demonstrate factual data from a variety of dimensions as required by decision-makers. By using the EIS, the decision-maker can trace the problem source that happened in their education system.

Big data analytic for estimation of origin-destination matrix in Bus Rapid Transit system

In the field of transportation, the origin-destination matrix is one of the main and important components, especially in analyzing, planning, and managing a public transport network. The traditional survey can be used to determine passengers travel patterns and generate origin-destination matrix, but it is inefficient and cost a lot of resources. In the recent years, various methods have been studied to estimate origin-destination matrix to reduce costs and increase the accuracy of passengers flow. Many of them take advantages of big data technology to gather passengers travel information, mostly using smart card data. In this paper, we perform origin-destination matrix estimation using information from the smart card that was collected from automatic fare collection systems in Jakartas Bus Rapid Transit. There are approximately 160 million records from 20 months of transactions between June 2014 and January 2016. This study utilized trip chaining algorithm that generates 610 daily OD matrices, 87 weekly OD matrices and 20 monthly OD matrices. The analysis is performed at a station and a line level, with an addition of passenger behavioral pattern.

Performance analysis of objective function MRHOF and OF0 in routing protocol RPL IPV6 over low power wireless personal area networks (6LoWPAN)

6LoWPAN is one of the implementations of WSN that using IPv6 as sensor addressing. 6LoWPAN is categorized in the new technology and still being developed. This causes issues about the networks performance to create the communication path and collecting data. Routing Protocol for Low-power-loosy (RPL) is a routing protocol used in 6LoWPAN. In RPL, there are two kind of objective functions development. Objective function is path selection mechanism when formation of the networks. This research is focus on performance analysis in two objective functions RPL that are Minimum Rank with Hysteresis Objective Function (MRHOF) and Objective Function Zero (OFO). This research observed using COOJA as a WSN simulator. The parameter that observed in this research are: networks convergence time, power consumption, ETX, hop, Packet Delivery Ratio (PDR), latency, PDR in mobility node. Based on the simulation we concluded that MRHOF give better performance than OF0 in terms of network quality. The implementation of MRHOF is suitable for use in sensor network that require data delivery in the reliable network. While OF0 is suitable for use in sensor network that require fast formation network link and low power consumption.

A review of an information extraction technique approach for automatic short answer grading

The requirement for automatic short answer grading (ASAG) system brings researchers to discover more knowledge about this field. Many techniques have been developed to reach the highest accuration. It can be processed by following stages: creating data set, pre-processing, model building, grading, and model evaluation. One of the techniques which commonly used is information extraction technique. Information extraction is a technique that employing finding fact on the student answers as patterns and then matches these to the teacher answer. The accuration is pointed out in computer and human raters agreement. The goal of this paper is to present a review of several ASAG research which using information extraction technique. However, this paper does not conclude the best method which can be used for general cases.

Design adaptive learning system using metacognitive strategy path for learning in classroom and intelligent tutoring systems

Adaptive learning (AL) is a learning process focusing on students’ personality through of recommendation-based learning and inquiry-based learning. This research intends to create a system capable of giving AL recommendation in the form of learning path (LP) in which LP will then be used as a recommendation for the teacher in constructing a learning process. In this research, LP was obtained through the identification of students’ metacognitive with the use of Metacognitive Awareness Index (MAI) respectively. The system itself was developed using Naive Bayer Classifiers (NBC) and rule-based system to construct the LP. Accuracy of the machine learning for learner style module was of 97.25% and black box test indicated that the system was functionally acceptable. From these results, it can be concluded that the system was functionally acceptable and capable of representing an expert (seeing as it could produce an output that conformed to the expected condition). An expert in education had declared the LP wa...

Development of semi-supervised named entity recognition to discover new tourism places

Tourism information needs are increasing in line with tourism that has been a primary need for some people. This has an impact on the growth of the tourism information provider. The amount of available information sometimes makes tourist confuse to the information that they needed. Currently, the search systems only rely on indexing web pages so that the information obtained by the tourist is still unfavorable because it only shows a web page with keywords that exist on the article. A support system to recognize tourism places on the web pages is required to produce better information presentation. In this study, the recognition system based on Yet Another Two Stage Idea (YATSI) Semi-Supervised Learning with the Naïve Bayes classifier is used to address the problem. Results obtained by classifying candidate entities on a hundred web pages demonstrate 74% precision with 70% recall.

Forecasting Avian Influenza incidence in Java and Madura area

Avian Influenza is a disease that becomes serious outbreak within animal population at Indonesia. The outbreak not only gives impact on economic losses for farmers but also threats human health. Time series forecasting of Avian Influenza incidence is implemented to predict the occurrence of disease in the future. The result is valuable for the decision maker to make strategic planning to control the outbreaks. This research applied ARIMA method to forecast Avian Influenza incidence in Java and Madura Island. The data were obtained from Animal Disease Investigation Center of Wates Yogyakarta. ARIMA is used because it can be updated rapidly in order to adapt to new data. The relationship between dependent and independent variable in ARIMA model is easy to interpret. The result shows that ARIMA may represent the future incident model in the case of Avian Influenza in Java and Madura Island. ARIMA has MSE=623.4764, Theils U1=0.447343 and Theils U2=0.908758.

Performance of Repeat-Accumulate Codes (RAC) for decode-and-forward wireless relay channel

Repeat-Accumulate Codes (RAC) are one of alternative choice code besides turbo codes and low-density parity-check (LDPC) codes. This paper presented decode-and-forward protocol for wireless relay channel by utilizing repeat-accumulate codes as the coding scheme in the relay. The main advantages of the RAC over another code that makes the RAC is more considered for this research are the complexity of encoding is linear in the code length, have a simpler design, and easier to combine with modulator or detector. Simplicity is the main factor for using RAC in this research because in the multihop wireless communication concept, the information processing that occurs in every node or in every relay should not be complicated. In this paper, RAC is employed in wireless relay channel for the LOS model and urban model. The result shows that in the LOS model, RAC only show BER improvement when the relay position is exactly in the mid between information source (S) and destination (D). In urban channel model, the BER improvement can be observed, whether the relay is positioned ¼, ½ or ¾ between the information source (S) and the destination (D).