Sentiment Analysis on Teacher Salary Policy in Indonesia 2025 Using Support Vector Machine: A Case Study on Instagram Data

Nur Hera Zabni; Mhd. Furqan

doi:10.47709/cnahpc.v7i3.6487

Authors

Nur Hera Zabni Departement of Computer Science, Faculty of Science and Technology, State Islamic University of North Sumatra, Indonesia
Mhd. Furqan Departement of Computer Science, Faculty of Science and Technology, State Islamic University of North Sumatra, Indonesia

DOI:

https://doi.org/10.47709/cnahpc.v7i3.6487

Keywords:

Instagram, Sentiment Analysis, Media Sosial, Support Vector Machine, Gaji Guru

Abstract

The government's policy regarding salary increases for both civil servant (ASN) and non-civil servant (honorary) teachers in 2025 has generated various responses from the public, especially on social media. This issue has sparked public debate, with the emergence of both positive and negative comments, particularly on the Instagram platform. This study employs the Support Vector Machine (SVM) approach to classify public sentiment based on Instagram comments. A total of 1,500 comments were collected from the @folkative account during December 2024. The data were analyzed through several preprocessing stages (cleaning, case folding, tokenization, filtering, stopword removal, and stemming), followed by TF-IDF word weighting, normalization, and SVM model training and testing with an 80% training and 20% testing data split. The developed model demonstrated excellent performance, achieving an accuracy of 86%, precision of 87%, recall of 99%, and F1-score of 93%. These results indicate that the SVM algorithm is effective in classifying public opinion on government policies. This research also contributes to the advancement of machine learning applications in policy analysis based on public opinion, which can serve as valuable input for formulating more responsive policies.

Downloads

Download data is not yet available.

References

Ayumi, V., Noprison, H., Utami, M., Putra, E. D., & Purba, M. (2023). Konsep Dasar Natural Language ProceSsing (NLP). CV. Jejak.

Badan Pusat Statistik Indonesia. (2024). Rata-Rata Upah/Gaji. Badan Pusat Statistik Indonesia. https://www.bps.go.id/id/statistics-table/2/MTUyMSMy/rata-rata-upah-gaji--rupiah-.html

Damayanti, D., Asbari, M., & Zaharantika, A. (2024). Guru Penggerak: Pengembangan Pendidikan Melalui Kepemimpinan Guru. Journal Of Information Systems and Management, 03(02), 05–10.

Dhobith, A. (2024). Analisis Kebijakan Gaji Guru Honorer Terhadap Kesejahteraan Hidup Guru Honorer Di Indonesia. Paramurobi: Jurnal Pendidikan Agama Islam, 7(1), 44–62. https://doi.org/10.32699/paramurobi.v7i1.6609

Furqan, M., Hasibuan, M. S., & Sapitri, B. (2023). Application of the support vector machine algorithm in the classification of livable houses. Jurnal Mantik, 7(3), 1643–1652.

Furqan, M., Ikhsan, M., & Aini, R. (2023). Algoritma Support Vector Machine Untuk Analisis Sentimen Masyarakat Indonesia Terhadap Pandemi Virus Corona Di Media Sosial. Kesatria?: Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen), 4(4), 908–915.

Furqan, M., Kurniawan, R., & HP, K. I. (2020). Evaluasi Performa Support Vector Machine Classifier Terhadap Penyakit Mental. Jurnal Sistem Informasi Bisnis, 10(2), 203–210. https://doi.org/10.21456/vol10iss2pp203-210

Furqan, M., & Nasir, A. F. A. (2024). Big Data Approach To Sentiment Analysis in Machine Learning-Based Microblogs: Perspectives of Religious Moderation Public Policy in Indonesia. Journal of Applied Engineering and Technological Science, 5(2), 955–965. https://doi.org/10.37385/jaets.v5i2.4498

Furqan, M., Putri, R. A., & Daulay, I. A. M. (2024). Implementasi Text Mining Dalam Identifikasi Cyber Hate Speech Menggunakan Support Vector Machine. JIKA(Jurnal Informatika) Universitas Muhammadiyah Tangerang, 8(4), 477–483.

Gemilang, W. S., Purwantoro, & Carudin. (2024). Analisis Sentimen Pengguna Instagram Pada Calon Presiden 2024 Menggunakan Algoritma Support Vector Machine. JATI (Jurnal Mahasiswa Teknik Informatika), 7(4), 2849–2855. analisis sentimen; Calon Presiden; Support Vector Machine; Knowledge in Discovery Database

Handayani, A., & Zufria, I. (2023). Analisis Sentimen Terhadap Bakal Capres RI 2024 di Twitter Menggunakan Algoritma SVM. Journal of Information System Research (JOSH), 5(1), 53–63. https://doi.org/10.47065/josh.v5i1.4379

Irfan, Muthalib, M. A., Kartika, & Meliala, S. (2023). Pengiraan Pose Model Manusia Pada Repetisi Kebugaran Ai Pemograman Python Berbasis Komputerisasi. INFOTECH journal, 9(1), 11–19. https://doi.org/10.31949/infotech.v9i1.4233

Isnain, A. R., Sakti, A. I., Alita, D., & Marga, N. S. (2021). Sentimen Analisis Publik Terhadap Kebijakan Lockdown Pemerintah Jakarta Menggunakan Algoritma Svm. Jurnal Data Mining dan Sistem Informasi, 2(1), 31. https://doi.org/10.33365/jdmsi.v2i1.1021

Nugraha, D., & Astuti, P. (2023). Analisis Sentimen Cyberbullying Pada Sosial Media Instagram Menggunakan Metode Support Vector Machine. Information System For Educators And Professionals, 8(2), 153–164.

Prasetyo, E. (2014). Data Mining Mengolah Data Menjadi Informasi Menggunakan Matlab. Penerbit ANDI Yogyakarta.

Putri, N. I., Hamzah, A., & Fatkhiyah, E. (2024). Analisis Sentimen Pada Media Sosisal Instagram Terhadap Perang Israel Vs Hamas Menggunakan Metode Naïve Bayes Dan SVM. Jurnal SCRIPT, 12(1), 30–38. https://doi.org/10.34151/script.v12i1.4806

Salam, R. R., Jamil, M. F., Ibrahim, Y., Rahmaddeni, R., Soni, S., & Herianto, H. (2023). Analisis Sentimen Terhadap Bantuan Langsung Tunai (BLT) Bahan Bakar Minyak (BBM) Menggunakan Support Vector Machine. MALCOM: Indonesian Journal of Machine Learning and Computer Science, 3(1), 27–35. https://doi.org/10.57152/malcom.v3i1.590

Syakur, A. (2021). Implementasi Metode Lexicon Base Untuk Analisis Sentimen Kebijakan Pemerintah Dalam Pencegahan Penyebaran Virus Corona Covid-19 Pada Twitter. Jurnal Ilmiah Informatika Komputer, 26(3), 247–260. https://doi.org/10.35760/ik.2021.v26i3.4720

Wajdi, F., & Perkasa, D. H. (2022). Pengaruh Gaji Guru dan Motivasi Kerja Terhadap Kinerja Guru pada SDIT Al-Muddatsiriyah. KALBISIANA Jurnal Sains, Bisnis dan Teknologi, 8(4), 3950–3963.

Wilyani, F., Arif, Q. N., & Aslimar, F. (2024). Pengenalan Dasar Pemrograman Python Dengan Google Colaboratory. Jurnal Pelayanan dan Pengabdian Masyarakat Indonesia, 3(1), 08–14. https://doi.org/10.55606/jppmi.v3i1.1087