Articles

Found 3 Documents
Search
Journal : Journal of Information Technology and Its Utilization

RABIN-CARP IMPLEMENTATION IN MEASURING SIMALIRITY OF RESEARCH PROPOSAL OF STUDENTS Herman, Herman; Syafie, Lukman; Tasmil, Tasmil; Resha, Muhammad
Journal of Information Technology and Its Utilization Vol 3, No 1 (2020)
Publisher : Balai Besar Pengembangan SDM dan Penelitian Komunikasi dan Informatika Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30818/jitu.3.1.3210

Abstract

Plagiarism is the use of data, language and writing without including the original author or source. The place where palgiate practice occurs most often is the academic environment. In the academic world, the most frequently plagiarized thing is scientific work, for example thesis. To minimize the practice of plagiarism, it is not enough to just remind students. Therefore we need a system or application that can help in measuring the level of similarity of student thesis proposals in order to minimize plagiarism practice. In computer science, the Rabin-Karp algorithm can be used in measuring the level of similarity of texts. The Rabin-Karp algorithm is a string matching algorithm that uses a hash function as a comparison between the search string (m) and substrings in text (n). The Rabin-Karp algorithm is a string search algorithm that can work for large data sizes. The test results show that the use of values on k-gram has an effect on the results of the measurement of similarity levels. In addition, it was also found that the use of the value 5 on k-gram was faster in executing than the values 4 and 6.
SCHEDULING USING GENETIC ALGORITHM AND ROULETTE WHEEL SELECTION METHOD CONSIDERING LECTURER TIME Herman, Herman; Syafie, Lukman; Irawati, Irawati; Hayati, Lilis Nur; Harlinda, Harlinda
Journal of Information Technology and Its Utilization Vol 2, No 1 (2019)
Publisher : Balai Besar Pengembangan SDM dan Penelitian Komunikasi dan Informatika Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30818/jitu.2.1.2243

Abstract

Scheduling lectures is not something easy, considering many factors that must be considered. The factors that must be considered are the courses that will be held, the space available, the lecturers, the suitability of the credits with the duration of courses, the availability of lecturers' time, and so on. One algorithm in the field of computer science that can be used in lecture scheduling automation is Genetic Algorithms. Genetic Algorithms can provide the best solution from several solutions in handling scheduling problems and the selksi method used is roulette wheel. This study produces a scheduling system that can work automatically or independently which can produce optimal lecture schedules by applying Genetic Algorithms. Based on the results of testing, the resulting system can schedule lectures correctly and consider the time of lecturers. In this study, the roulette wheel selection method was more effective in producing the best individuals than the rank selection method.
IMPLEMENTATION OF MOMENT INVARIANT IN RECOGNIZING OF ELECTRICAL METER NUMBERS Syafie, Lukman; Herman, Herman; Alam, Nur; Tasmil, Tasmil
Journal of Information Technology and Its Utilization Vol 3, No 1 (2020)
Publisher : Balai Besar Pengembangan SDM dan Penelitian Komunikasi dan Informatika Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30818/jitu.3.1.3194

Abstract

Implementation of computer vision can be done in the introduction of images or pictures of characters of numbers or letters. Based on this, then the computer vision can be used in the introduction of numbers on the electric meter or commonly called kWh meter. The underlying thing for the electric meter to be the object of research is to look at the situation, where the electric meter recorder keeps the record using the camera. Furthermore, the value shown on the electric meter will be inputted manually. Manual input requires a relatively long time because the amount of electricity meter input value is not small data. One method that can be used in recognizing the shape of the image in computer vision is the invariant moment. The results of this study indicate that the quality of the image gives effect, both in terms of the extraction of features and the accuracy of the recognition of the figure on the image of the electric meter. In addition to this, the threshold value of the euclidian distance method should also be used to limit the recognition process.