Cooking Recipe is a culinary element that often attracts culinary lovers. A cooking recipe is a guidance for preparing the ingredients, how to cook and serve the dish. The collection of recipes which documented in the printing media have not been able to meet the needs of culinary lovers with high mobility. This study aims to develop an Android-based recipe application to meet the culinary lovers need of a technology for storing recipes collection that can be accessed easily. We apply the  Luther multimedia development method, which consists of the concept, design, material collecting, assembly and testing phases. The Android platform will provide the recipe application features, and the website platform will provide the content management features for managing the contents in the recipe application. The result of black box testing on the application shows that the features in the recipe application perform according to the expected concept and design. For the future research, to improve the application performance, we will build social media features for the members and a data mining system for processing big data from the recipe collection to produce valuable information.

Searching is one of the important features on the website, but it is not uncommon for users to make typos when typing keywords. Typing errors of these keywords is usually referred to as typo. This study aims to build a system by providing suggestions for correcting typos in the search feature. Keywords search correction are obtained using the Damerau-Levenshtein Distance Approximate String Matching algorithm by to calculate the editing distance of each word in a keywords with each word in the Indonesian word dictionary. Testing was carried out as many as 40 experiments, with 10 keywords and 250 articles taken randomly. The test results show the Damerau-Levenshtein Distance algorithm is able to provide precision and recall values of 91.24% and 89.58% in providing keyword improvement suggestions. With the improvement of the system, each trial increases with precision value of 0.80 and recall value of 0.98.

The recording of student attendance aims to monitor the student attendance quantity and educate students to be disciplined. Student attendance records that are currently done manually on the paper can be improved to increase the quality of the attendance data processing, service quality and system in the School. This study aims to build an Attendance application based on Android platform that can be used on the teacher's mobile device. Waterfall is the method which is used to develop the attendance application in this study. Then, to ensure the application performance, the attendance application will be tested by the blackbox testing method. The test results using the blackbox testing show that the features in the attendance application perform according to its purpose. This attendance application can facilitate the homeroom teacher to carry out the student attendance recording process daily and to create the student attendance data recapitulation.

Social media, blogs and online groups become a forum that makes is easy for the Indonesian people to express their opinions, suggestions, complaints and even criticisms of a subject liberally. Sentiment analysis is a method for classifying positive, neutral, and negative polarity of the opinions that expressed by the internet users. Sarcasm is one of the challenges to classsifying the sentiments of an opinion. This research is a literature review to examine several studies to find out the methods for detecting sarcasm and to know the effect of sarcasm on the sentiment classification accuracy. The result of this literature review can be used as a reference for developing the sarcasm detection methods.

The practice of plagiarism among students in working on their thesis might happen. Plagiarism is done considering to the limited workmanship and lack of motivation to try with their own ability. It is necessary to provide a tool to prevent the act of plagiarism among the students. In this research, we built an application to detect the plagiarism on the thesis proposal. The application applies the Jaro Winkler Distance algorithm to detect the similarity from several documents. The first phase to detect the similarity of the thesis proposals is The text preprocessing phase of the document such as case folding, tokenizing,  stopwords removal and stemming. Precision and Recall formula will be used to analyze the performance of the method in application. The test result of the data set shows the application could find the 80% relevant data that indicated the similarity. It means the application could contribute to detect the plagiarism on the thesis proposal document.