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All Journal International Journal of Social Science, Educational, Economics, Agriculture Research, and Technology (IJSET)
Norita Tampubolon
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Education

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THE PROBLEM OF CYBERBULLYING IN THE DIGITALIZATION ERA WHICH HAS A NEGATIVE IMPACT ON PUBLIC LIFE Lewika Tampubolon; Zailani Sinabariba; Norita Tampubolon; Penggabean Siahaan; Muhammad Amin
International Journal of Social Science, Educational, Economics, Agriculture Research and Technology (IJSET) Vol. 4 No. 12 (2025): NOVEMBER
Publisher : RADJA PUBLIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/ijset.v4i12.1551

Abstract

In the era of rapidly developing information and communication technology, social interactions have shifted significantly to digital platforms. While this progress brings many benefits, such as ease of communication and access to information, information technology can also have significant negative impacts, one of which is the emergence of cyberbullying. Cyberbullying is behavior intended to humiliate, intimidate, injure, or cause harm to a vulnerable party using information technology communication tools. In other countries, there are many cases of cyberbullying that end in more serious incidents such as suicide. This paper uses a qualitative method with a literature review approach. This approach was chosen to in-depth explore various literature and previous research related to the topic of bullying among the community, especially teenagers in the digital era. The results of the study indicate that the negative impact of information technology on cyberbullying cases has occurred at a fairly large rate (28%), but the impact is not very serious. From the answers given, it can be concluded that many people do not understand cyberbullying and its potential impacts. This study also explores the roles, responsibilities, and actions of teenagers, parents, schools, and law enforcement.
IMPLEMENTATION OF DEEP LEARNING ALGORITHM FOR PT GROWTH SUMATERA'S FACE DETECTION ATTENDANCE SYSTEM Norita Tampubolon; Penggabean Siahaan; Lewika Tampubolon; Zailani Sinabariba; Muhammad Syahputra Novelan
International Journal of Social Science, Educational, Economics, Agriculture Research and Technology (IJSET) Vol. 4 No. 12 (2025): NOVEMBER
Publisher : RADJA PUBLIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/ijset.v4i12.1552

Abstract

Attendance is a data collection activity to determine the number of employees present, arrival times, and departure times in a company. Attendance is divided into two types: manual and automatic. Manual attendance is an attendance process carried out using a handwritten note or signature form. Automatic attendance is an attendance process that involves technology. With facial recognition technology, an attendance system can be developed. Facial recognition technology is a computer technology that functions to determine facial location, facial size, feature detection, background image ignoring, and facial image identification. Facial recognition involves several variables, such as source images, processed images, extracted images, and a person's identity data. Deep learning with Convolutional Neural Networks is one method used to predict and classify different human facial images. This facial detection attendance system application is designed and built on a desktop platform, using the Python programming language. The application of deep learning algorithms with convolutional neural networks (CNN) in this facial detection attendance system can streamline the existing attendance system.
Co-Authors Lewika Tampubolon Muhammad Amin Muhammad Syahputra Novelan Penggabean Siahaan Zailani Sinabariba