http://repository.kalbis.ac.id/handle/123456789/194 Skripsi Informatika Tahun 2022 2026-03-15T06:55:30Z http://repository.kalbis.ac.id/handle/123456789/716 Title: Pengembangan Aplikasi Analisis Sentimen Penerapan PPKM Level 3 Authors: Napitupulu, Jonas Ariston Abstract: This study aims to analyze tweets about the imposition of Community Activity Restrictions (PPKM) level 3 to find the number of positive, negative, and neutral responses by building webbased software to conduct sentiment analysis on tweets data with the keywords “PPKM level 3". This research consists of two increments. The first increment is modeling and sentiment analysis and the second increment is making a website for visualizing the results. The results in the first increment are a model to perform sentiment analysis with an accuracy of 76.59% for training and for testing, with an accuracy of f1-score 75% with the test results on the macro average precision 82%, recall 73%, f1-score 75% with support of 20 and weighted average precision 80%, recall 75%, f1-score 75% with support of 20 and dataset analysis results with 30.82% positive sentiments, 17.80% neutral sentiments, and 51.36% negative sentiments. The result in the second increment is a website for visualization. 2022-06-22T00:00:00Z http://repository.kalbis.ac.id/handle/123456789/633 Title: Pengembangan Aplikasi Clipboard Salin Tempel Karakter Teks dari Citra Digital Authors: Arnanda, Muhammad Evan Abstract: This study aims to build software that can perform text extraction on an image containing text. This research uses a software development method called incremental. The application is built using the Python programming language and the use of Tesseract as a model. The output of this application is in the form of text that is put into the clipboard so that the user can paste the output into the preferred place. This research produces an application that can perform text extraction on an image containing text. This application was tested using black box testing, from several tests on the available features, all test results were successful because the features tested could function and be used. 2022-08-15T00:00:00Z http://repository.kalbis.ac.id/handle/123456789/560 Title: Aplikasi Rekomendasi Musik Berdasarkan Klasifikasi Genre Menggunakan Convolutional Neural Networks Authors: Sukietra, Dewa Abstract: Convolutional Neural Network can be implemented on various deep learning approach for scientific or problem solving real world case. This research discusess implementing Convolutional Neural Network for music genre classification. Researcher will classified 8 genres music on this research. Music will be converted first to MFCC so its features can be extracted. Researcher use GTZAN Dataset as the base line for Convolutional Neural Network to learn each feature on a bunch of genres. Validation Accruacy with GTZAN dataset is 79% and Real world classification resulting in 60%. The classification progam can be used on android devices. This research also serve music suggestions based the result of predicted genre 2022-06-17T00:00:00Z http://repository.kalbis.ac.id/handle/123456789/493 Title: Pengembangan Aplikasi Klasifikasi Sepatu Air-Jordan Berbasis Web Authors: Adipratama, Virya Abstract: This research is motivated by the number of series and the similarities of Air Jordan sneakers so that the series of the Air Jordan sneakers is hard to recognize. Therefore, this research intends to solve the Air Jordan sneakers classification problem with building a web-based application to classify Air Jordan sneakers images. This research aims to develop a web-based software to classify Air Jordan sneakers images. The data that are used in this research are 11641 Air Jordan sneakers images for training and 560 Air Jordan sneakers images for testing with 35 classes. The methods that are used in this research is incremental methods which is made with two increments. The first increment produces a classification model and the second increment produces an application that implemented the classification model. The result of this research is a web-based application that can classify an Air Jordan sneakers image with the output of the predicted series of that Air Jordan sneakers image. 2022-08-19T00:00:00Z