EVALUATION OF DISTANCE LEARNING SYSTEM (E-LEARNING): A SYSTEMATIC LITERATURE REVIEW

Research in the field of e-learning is currently experiencing rapid development, especially due to the covid 19 pandemic. The application of e-learning in the world of education is currently the main thing and requires evaluation of its use. This study aims to determine the evaluation of models and trends in the development of e-learning (Learning Management System). Applying the Kitchenham approach, this System Literature Review (SLR) uses three main databases including Science Direct, ACM, SCOPUS. The final result obtained 38 articles published between 2016 and 2021. From this SLR, it was found that there were 7 criteria, namely Platform, Evaluation Model, Evaluation, Model, Approach, Problem, Trend and Challenge. These 7 criteria can be used for further research on e-learning. Thus this research provides knowledge about criteria that can be used further in research on E-learning and provides insight into its state-of-the-art.

WEB-BASED GEOGRAPHIC INFORMATION SYSTEM FOR LAMPUNG GIFT STORE

In the face of increasing technological advances, the development of society refers to the ability to keep up with technological developments and the ability to access and present useful information. Lack of information and knowledge about the location of the gift store makes the public or tourists only visit the nearest store or those suggested by friends and people around. This study aims to develop a web-based geographic information system to make it easier for people to find the location of Lampung gift store. In this study using extreme programming as a development method. Based on the results of testing ISO 25010 that has been carried out involving 50 respondents, the conclusion that the quality of the software produced has a success percentage with a total average of 90.66%. So it can be concluded that the percentage value obtained shows the overall software quality has a "Very Good" scale and is feasible to use.

IMPLEMENTASI ALGORITMA YOLO DAN TESSERACT OCR PADA SISTEM DETEKSI PLAT NOMOR OTOMATIS

Currently, vehicle number plate detection systems in general still use the manual method. This will take a lot of time and human effort. Thus, an automatic vehicle number plate detection system is needed because the number of vehicles that continues to increase will burden human labor. In addition, the methods used for vehicle number plate detection still have low accuracy because they depend on the characteristics of the object being used. This study develops a YOLO-based automatic vehicle number plate detection system. The dataset used is a pretrained YOLOv3 model of 700 data. Then proceed with the number plate text extraction process using the Tesseract Optical Character Recognition (OCR) library and the results obtained will be stored in the database. This system is web-based and API so that it can be used online and on the cross-platform. The test results show that the automatic number plate detection system reaches 100% accuracy with sufficient lighting and a threshold of 0.5 and for the results using the Tesseract library, the detection results are 92.32% where the system is successful in recognizing all characters on the license plates of cars and motorcycles. in the form of Alphanumeric characters of 7-8 characters.