Klasifikasi Teks Komentar Penggunaan Listrik Gratis di Youtube Menggunakan Metode Naïve Bayes

2026-05-07T23:42:02+07:00

The growth of social media has made YouTube one of the platforms used by the public to express opinions regarding government policies, including the free electricity program. The large number of comments makes manual analysis difficult; therefore, a text classification method is needed to automatically categorize comments. This study aims to classify YouTube user comments related to the free electricity program using the Naïve Bayes algorithm. The research data were obtained through a crawling process from ten YouTube videos discussing the free electricity policy, resulting in 910 comments, which were reduced to 906 comments after data cleaning. The data processing stages included cleaning, case folding, tokenizing, normalization, stopword removal, stemming, and term weighting using TF-IDF. Furthermore, the data were classified into four categories: Public Discussion and Information, Policy Support and Appreciation, Complaints and Technical Issues, and Non-Electricity. Model evaluation was conducted using a confusion matrix with accuracy, precision, recall, and F1-score metrics. The results showed that the Naïve Bayes algorithm provided fairly good classification performance with an accuracy of 70.9%, precision of 0.62, recall of 0.80, and F1-score of 0.70. The Non-Electricity category achieved the best performance with precision of 0.77, recall of 0.90, and F1-score of 0.83. Based on these findings, the Naïve Bayes method is considered effective for classifying public opinion from social media comment data.

Penerapan Engineering Design Process dalam Pengembangan Tong Sampah Berbasis QR Code Terintegrasi Website untuk Pengelolaan Sampah Berbasis Masyarakat

2026-05-09T01:19:56+07:00

Community-based waste management remains a challenge in residential environments, particularly due to low community participation in reporting waste bin conditions and the lack of information media for waste management activities. This condition highlights the need for technological innovation that can increase community involvement in waste management more effectively. This study aims to develop a technology-based innovation grounded in real community needs through the implementation of the Engineering Design Process (EDP). The research stages began with field observations to identify problems, followed by recording and grouping findings, formulating problems and solutions, creating initial sketches, comparing ideas with similar innovations, and selecting a solution in the form of a QR Code-based waste bin integrated with a website. Furthermore, a 3D design of the waste bin and a website interface were developed, followed by the construction of a simple prototype of the QR Code-based waste bin and a localhost-based website. The website provides features including a homepage, community profile, activity schedule, reporting, educational content, suggestion forms, and an admin page for data management. System testing was conducted through user testing involving community residents as system users. The results indicate that the majority of respondents considered the system easy to use, useful, and aligned with environmental needs, as reflected by positive feedback from all participants during interview-based testing. The study demonstrates that applying the Engineering Design Process through direct field observation can produce technological innovations that are relevant and provide tangible benefits for community-based waste management.

TIN: Terapan Informatika Nusantara

Klasifikasi Teks Komentar Penggunaan Listrik Gratis di Youtube Menggunakan Metode Naïve Bayes

Penerapan Engineering Design Process dalam Pengembangan Tong Sampah Berbasis QR Code Terintegrasi Website untuk Pengelolaan Sampah Berbasis Masyarakat