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Functional Requirement Design for Optimizing Tourism Promotion of DKI Jakarta based on Descriptive Research Method
Get PDFThis study presents data collected as sample from two places of tourism spots, TMII and MONAS. Furthermore, additional data has also been collected from public places such as campuses to support current data collection. The data is collected in order to recognize the visitors’ responses according to their tourism information needs in preparing their traveling activities. Descriptive research method adopted using self-designed questionnaires focusing on “what” is applied to investigate the questions which are related with the topic of the study. The results of data analysis would be referred as foundation in designing the system functionalities required to develop an application for the future development. Furthermore, more data is observed from some data resources such as Central Bureau of Statistics (BPS) of DKI Province and Global Destination Cities Index to recognize the performance of DKI Jakarta in receiving visitors within the last three years compared to other cities in some neighboring countries such as Bangkok, Kuala Lumpur and Singapore. Thirty respondents are involved in the study to identify what potential information which can be explored. The information which is related to visitors’ travel preparation becomes imperative to be analyzed to optimize the tourism promotion. Descriptive research method helps researchers in obtaining data on functional needs according to the current state of society, in the scope of travel activities and preparations. The system design viewed from the functional needs shows what people can do based on the results of the analysis
Feature Selection on Pregnancy Risk Classification Using C5.0 Method
Get PDFThe maternal mortality rate in Indonesia is still relatively high. This is caused by several factors, including the ignorance of pregnant women about the risk status of pregnancy. Several methods are proposed for early detection of the risk of a mother's pregnancy. However, no one has highlighted what features are most influential in the process of classifying the risk of pregnancy. In this research, we use data of pregnant women in one of the health centers in Malang, Indonesia, as a dataset. The dataset has 107 features, therefore, feature selection is needed for the classification process. We propose to use the C5.0 method to select important features while classifying dataset into low, high, and very high risk of pregnancy. C5.0 was chosen because this method has a better pruning algorithm and requires relatively smaller memory compared to C4.5. Another classification method (SVM, Naive Bayes, and Nearest Neighbor) is then used to compare the accuracy values between datasets that use all features with datasets that only use the selected features. The test results show that feature selection can increase accuracy by up to 5%
Integrated Information System Teaching Plan in College Using FAST Method and Twitter Bootstrap
Get PDFAbstractTeaching plan is one of the obligations that must be made by lecturer before conducting any lecture because teaching plan will be used by lecturer as a reference in determining Learning Outcomes (LO) and providing recovery materials in each semester. Unfortunately, there are still many existing teaching plans in College which are still manually developed. Thus, they may undermine head courses and Institute of Educational Development Study and Majors to perform learning monitoring and evaluation in the department.This research developes a system application which facilitates lecturer in managing teaching plan recovery and facilitates the Institute of Educational Development Study and Majors in evaluating the learning effectiveness, the suitability of the teaching journal and the achievement of Learning Outcomes. The system is developed using FAST method (Framework for the Application of System Thinking) and designed using a responsive Twitter Bootstrap template. The information generated system can also be used to support the cccreditation of Program Study. The testing process in this system uses blackbox testing to check the stability of the deployed system. The result of the test shows that all functions in the system runs perfectly, and the lecturers are more easily managing the Teaching plan, and the head of the Department can evaluate the suitability of the Teaching plan with teaching journal
Generating Indonesian Question Automatically Based on Bloom’s Taxonomy Using Template Based Method
Get PDFIn education field, evaluation is needed to know the extent to which the learning process has been done. The evaluation process can be done through the provision of questions with varying degrees of difficulty. However, making questions with varying degrees of difficulty is not easy. Someone must understand the whole new materials to make the question. If there are a lot of materials, it takes a little time to change them to be a question. Therefore, it is necessary to automate the question generation process, in order to facilitate and accelerate the question generation process. This research introduces a template-based method to generate questions based on New Bloom's Taxonomy. There were 4 stages in this research, dataset collection, pattern identification process, question generating process & classification, and final evaluation process result. The dataset consists of 60 samples of paragraphs that derived from 9 courses of study courses Informatics Engineering. The 60 paragraphs produced 278 sentences and 654 questions. The proposed method is capable of producing an accuracy of 81.65% to generate questions using New Bloom's Taxonomy classification. So it can be concluded that the proposed method can be used to generate questions with varying difficulty levels in accordance with New Bloom's Taxonomy
A Modified Real-Time Fault-Tolerant Task Allocation Scheme for Wireless Sensor Networks
Get PDFIn WSNs, the sensor nodes are at risk of failure and malicious attacks (selective forwarding). This may have a profound negative effect when you consider real-time WSNs, making them challenging to deploy. When there is a delay in tasks allocation execution processes in real-time WSNs because of sensor nodes failures, this will cause disastrous consequences if the systems are safety-critical, e.g. aircraft, nuclear power plant, forest fire detection, battlefield monitoring, thus the need to developed a real-time system that is fault-tolerable. This paper developed a modified real-time fault-tolerant task allocation scheme (mRFTAS) for WSNs (wireless sensor networks), using active replication techniques. mRFTAS and RFTAS performance were compared using time of execution of the task, network lifetime and reliability cost. The mRFTAS performance showed an improvement over that of RFTAS when it comes to reducing the time it takes for task execution by 45.56% and reliability cost of 7.99% while prolonging the network lifetime by 36.35%
Increasing Smoke Classifier Accuracy using Naïve Bayes Method on Internet of Things
Get PDFThis paper proposes fire alarm system by implementing Naïve Bayes Method for increasing smoke classifier accuracy on Internet of Things (IoT) environment. Fire disasters in the building of houses are a serious threat to the occupants of the house that have a hazard to the safety factor as well as causing material and non-material damages. In an effort to prevent the occurrence of fire disaster, fire alarm system that can serve as an early warning system are required. In this paper, fire alarm system that implementing Naïve Bayes classification has been impelemented. Naïve Bayes classification method is chosen because it has the modeling and good accuracy results in data training set. The system works by using sensor data that is processed and analyzed by applying Naïve Bayes classification to generate prediction value of fire threat level along with smoke source. The smoke source was divided into five types of smoke intended for the classification process. Some experiments have been done for concept proving. The results show the use of Naïve Bayes classification method on classification process has an accuracy rate range of 88% to 91%. This result could be acceptable for classification accuracy
Keystroke Dynamic Authentication Using Combined MHR (Mean of Horner’s Rules) and Standard Deviation
Get PDFKeystroke Dynamic Authentication used a behavior to authenticate the user and one of biometric authentication. The behavior used a typing speed a character on the keyboard and every user had a unique behavior in typing. To improve classification between user and attacker of Keystroke Dynamic Authentication in this research, we proposed a combination of MHR (Mean of Horner’s Rules) and standard deviation. The results of this research showed that our proposed method gave a high accuracy (93.872%) than the previous method (75.388% and 75.156%). This research gave an opportunity to implemented in real login system because our method gave the best results with False Acceptance Rate (FAR) is 0.113. The user can be used as a simple password and ignore a worrying about an account hacking in the system
Comparison of Acquisition Software for Digital Forensics Purposes
Get PDFDigital Forensics, a term that is increasingly popular with internet needs and increasing cybercrime activity. Cybercrime is a criminal activity with digital media as a tool for committing crimes. The process for uncovering cybercrime is called digital forensics. The initial stage in digital forensics is an acquisition. The acquisition phase is very important because it will affect the level of difficulty and ease in investigating cybercrime. Software acquisition will affect the abandoned artefacts and even overwrite important evidence by the software, therefore investigators must use the best software for the acquisition stage. This study shows the difference in software for the acquisition of the best Random Access Memory (RAM) such as processing time, memory usage, registry key, DLL. This research presents five acquisition software such as FTK Imager, Belkasoft RAM Capturer, Memoryze, DumpIt, Magnet RAM Capturer. Results of this study showed that FTK Imager left about 10 times more artefacts than DumpIt and Memoryze. Magnet RAM Capture the most artefacts, 4 times more than Belkasot RAM Capturer. Software acquisition with many artefacts, namely Capture RAM Magnet and FTK Imager, while for the fastest time is DumpIt and Capture RAM Magnet for software that takes a long time
Impact of H-Index Toward Citations Using Linear Regression on Science and Technology Index
Get PDFNumber of Journals in Indonesia is quite a lot and various disciplines. Until March 15, 2018, registered 50,889 online and print ISSN by Indonesian Institute of Science (LIPI). The government through Ministry of Research, Technology, and Higher Education of Republic Indonesia (Kemenristekdikti) set regulated on journal index, that is Science and Technology Index (SINTA) assigned to rank quality content and management divided by six categories called S1 to S6 which of the data is taken from Google Scholar and Scopus. This research applies S1 that these journals are accredited “A” by Kemenristekdikti and or index by Scopus. That’s data is shown ranking by sorted based on h-index and citations. S1 shown that journal which has highest h-index uncertain have highest citations too, even some have zeroes. That’s data on S1 become strange and awkward when compared with S2 to S6 because some value of h-index and citations S1 is lower than S2 to S6. This research focus to find how strong correlation or impact h-index toward citations using linear regression. The test result shows that value of Multiple R = 0.78 indicates the correlative is very close, a value of R Square = 0.61 indicates the impact of h-index toward citations achieve 61% and the rest 39% affected by others factor