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All Journal Elkom: Jurnal Elektronika dan Komputer CESS (Journal of Computer Engineering, System and Science) Sinkron : Jurnal dan Penelitian Teknik Informatika JISTech (Journal of Islamic Science and Technology) IJISTECH (International Journal Of Information System & Technology) JURTEKSI JOURNAL OF SCIENCE AND SOCIAL RESEARCH Simtek : Jurnal Sistem Informasi dan Teknik Komputer Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Technologia: Jurnal Ilmiah TIN: TERAPAN INFORMATIKA NUSANTARA Teknosains : Jurnal Sains,Teknologi dan Informatika Journal of Computer Networks, Architecture and High Performance Computing Journal of Intelligent Computing and Health Informatics (JICHI) Jurnal Teknologi Informasi dan Komunikasi IJISTECH Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Journal of Dinda : Data Science, Information Technology, and Data Analytics Jurnal IPTEK Bagi Masyarakat Journal of Computer Science and Informatics Engineering Jurnal Ilmu Komputer dan Teknologi (IKOMTI) Jurnal Informatika Teknologi dan Sains (Jinteks) Sistem Pendukung Keputusan dengan Aplikasi DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Internet of Things and Artificial Intelligence Journal Jurnal Ekonomi, Teknologi dan Bisnis Jurnal Pengabdian Masyarakat VISA: Journal of Vision and Ideas
Aidil Halim Lubis
Universitas Islam Negeri Sumatera Utara
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Journal : TIN: TERAPAN INFORMATIKA NUSANTARA

 1 
Sentiment Analysis of Public Opinion on Facebook Monetization in Social Media Using the SVM Algorithm Nurmaiyah, Nurmaiyah; Lubis, Aidil Halim
TIN: Terapan Informatika Nusantara Vol 6 No 3 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i3.8210

Abstract

Sentiment analysis on Facebook’s monetization policy has become a significant topic in the era of rapid digital transformation. This study examines public opinion on the policy by analyzing TikTok user comments that specifically discuss Facebook monetization. TikTok was chosen as the data source because it reflects spontaneous and real-time public reactions, including discussions about other platform policies. A total of 5,000 TikTok comments were collected using web scraping techniques. The data underwent several preprocessing stages, including text cleaning, tokenization, normalization, stopword removal, and stemming. Sentiment labeling was carried out using the Indonesian Sentiment Lexicon (InSet), while feature extraction employed the Term Frequency–Inverse Document Frequency (TF-IDF) method. The classification process was conducted using the Support Vector Machine (SVM) algorithm with a linear kernel. The dataset was split into training and testing sets with an 80:20 ratio. The classification achieved an accuracy of 80%, with a precision of 80% for both positive and negative sentiments, recall scores of 81% and 79%, and F1-scores of 81% and 79%, respectively. These findings demonstrate that integrating TF-IDF weighting with the SVM algorithm is effective for automatically classifying public sentiment toward social media monetization policies. Furthermore, this study provides insights into public reactions to Facebook monetization from the perspective of TikTok users, thereby contributing to an understanding of how monetization policies influence user sentiment on social media platforms.
Sistem Deteksi Kecenderungan Perilaku Agresif Akibat Pengaruh Smartphone Terhadap Psikologis Anak Menggunakan Metode Teorema Bayes dan Certainty Factor Wahyudi, Wahyudi; Zufria, Ilka; Lubis, Aidil Halim
TIN: Terapan Informatika Nusantara Vol 4 No 12 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v4i12.5112

Abstract

The ease of obtaining information and having complete functions in one hand makes an individual tend not to be separated from a smartphone even for a while because the individual has felt dependent on the smartphone function. Excessive smartphone use in children can have a negative impact on their psychological health, especially in terms of aggressive behavior. Excessive use of smartphones can make children more impulsive, irritable, and prone to aggressive actions. Therefore, a system is needed that can detect the tendency of aggressive behavior in children due to the influence of smartphones to prevent the encouragement of aggressive behavior in children that can make these children capable of committing criminal acts and other negative actions using an expert system. The methods used in this research are the certainty factor method and the Bayes theorem method. Bayes theorem is used to classify and calculate the probability value of a child's tendency to aggressive behavior due to the influence of smartphones. While the certainty factor method is used to determine the confidence value of the probability value obtained using the Bayes theorem. The results of this study illustrate the feasibility of the proposed framework in correctly recognizing the tendency of coercive behavior influenced by smartphone use among children. By utilizing Bayes' theorem and certainty factor, it is expected that this research can help in conducting early detection of the level of aggressive behavior tendencies due to the influence of smartphones. Based on the research that has been done, the system successfully detects 3 (three) levels of tendency, namely low, medium, and high with a percentage of 100% with the results of the Bayes theorem and certainty factor calculations showing in class P3 with a combination of CFcombine(CFold_4,CF_13) has a percentage of 94.17% confidence level and judging from the results of the calculation of the certainty factor combination formula above, it can be concluded that, the child has a tendency to High aggressive behavior.
Co-Authors Abdul Halim Hasugian Adjie Prakasa Viragupty Algifahri, Muhammad Dzar Annisa Aprilia Armansyah Artika, Priti Rindi As’Ary Sahlul Irsyad Darisma Daulay Desmi Roma Putra Lubis Dimas, Dimas Erma Julita, Erma Fadiga, Muhammad Faris Jihad Galang Desdwiansyah Harahap, Yunus Fadillah Hazizah Ulfa Nasution Husein Nur Ansyari Ilka Zufria istiqomah istiqomah Jihan Ulfa Deski Kiki Widya Pratiwi Lia Putri Ashari Lubis M Alif Fahrezy Mhd Furqan Monica Situmeang Muhammad Alwi Baihaqi Muhammad Ihsan Nugraha Muhammad Ikhsan Muhammad Ikhsan Muhammad Siddik Hasibuan Muhammad Zarlis, Muhammad Ningrum, Indri Ayu Nurmaiyah, Nurmaiyah Pandu Wicaksono Putra, Donny Dwi Qori Siagian Rahman, Anisa Rahman, Elsa Azila Rakhmat Kurniawan R Ridho Rizky Nasution Rizky Pulungan, Miftahul Santoso, Heri Saragih, Ahmad Fadhly Sani Shella Fahdilla Sari Sihombing, Rizki Andika Siregar, Muhaimi Rizki Siregar, Romadon Goring Sri Wahyuni Sriani Sriani Sriani Suhardi Suhardi, Suhardi Supiyandi Supiyandi Tasya, Yulianda Wahyudi Wahyudi Yunus Fadillah Harahap Yusuf Ramadhan Nasution Zulfi, Tio Fahreza Zulfi