Rancangan Arsitektur Sistem Analisis Sentimen Kinerja POLRI Berbasis Cloud PaaS dan IndoBERT
DOI:
https://doi.org/10.5281/zenodo.18366548Keywords:
Analisis Sentimen, IndoBERT, AHP, Cloud Computing, PaaS, Kinerja POLRIAbstract
Pada era ini, kepercayaan publik terhadap institusi penegak hukum seperti POLRI sangat dipengaruhi oleh opini yang berkembang di media sosial. Namun, analisis terhadap data masif (Big Data) ini menghadapi dua tantangan utama yaitu keterbatasan metode klasik dalam memahami konteks bahasa Indonesia (seperti sarkasme dan bahasa gaul) serta tingginya kebutuhan sumber daya komputasi untuk menjalankan model Deep Learning. Penelitian ini bertujuan untuk merancang sebuah kerangka kerja sistem analisis sentimen terintegrasi yang tidak hanya akurat, tetapi juga efisien secara infrastruktur dan strategis dalam pengambilan keputusan. Metodologi penelitian ini menggabungkan model IndoBERT untuk klasifikasi teks kontekstual, metode Analytic Hierarchy Process (AHP) untuk pembobotan prioritas kinerja, dan arsitektur Cloud Platform as a Service (PaaS) sebagai lingkungan implementasi. Hasil penelitian ini berupa rancangan arsitektur sistem yang memanfaatkan layanan serverless dan GPU berbasis cloud untuk efisiensi biaya dan skalabilitas otomatis. Simulasi sistem menunjukkan bahwa integrasi IndoBERT mampu mendeteksi sentimen negatif terselubung, sementara AHP berhasil mentransformasi data sentimen menjadi daftar prioritas perbaikan yang dapat ditindaklanjuti (actionable insights). Penelitian ini menyimpulkan bahwa adopsi arsitektur berbasis Cloud PaaS adalah solusi paling layak (feasible) untuk mengimplementasikan model NLP mutakhir di lingkungan pemerintahan tanpa investasi perangkat keras yang masif.
Downloads
References
Aprinando, A., Simarmata, P., & Sasongko, T. B. (2025). Sentiment Analysis on BRImo Application Reviews Using IndoBERT. In Journal of Applied Informatics and Computing (JAIC) (Vol. 9, Issue 3). http://jurnal.polibatam.ac.id/index.php/JAIC
Asmoro, D., & Riswadi. (2024). Legal Deliberation and Police Reform To Increase Transparency and Accountability In Law Enforcement (Vol. 3). https://edunity.publikasikupublisher.com
Azzabi, S., Alfughi, Z., & Ouda, A. (2024). Data Lakes: A Survey of Concepts and Architectures. In Computers (Vol. 13, Issue 7). Multidisciplinary Digital Publishing Institute (MDPI). https://doi.org/10.3390/computers13070183
Cahyawijaya, S., Lovenia, H., Fikri Aji, A., Indra Winata, G., Wilie, B., Koto, F., Mahendra, R., Wibisono, C., Romadhony, A., Vincentio, K., Santoso, J., Moeljadi, D., Wirawan, C., Hudi, F., Satrio Wicaksono, M., Halim Parmonangan, I., Alfina, I., Firdausi Putra, I., Rahmadani, S., … Authors, M. (2023). NusaCrowd: Open Source Initiative for Indonesian NLP Resources. Association for Computational Linguistics. https://indonlp.github.io/
Costa, C. J., Aparicio, M., Aparicio, S., & Aparicio, J. T. (2024). The Democratization of Artificial Intelligence: Theoretical Framework. Applied Sciences (Switzerland), 14(18). https://doi.org/10.3390/app14188236
Dhendra, & Gayuh Utomo, V. (2025). Benchmarking IndoBERT and Transformer Models for Sentiment Classification on Indonesian E-Government Service Reviews. Jurnal Transformatika, 23(1), 86–95. https://doi.org/10.26623/transformatika.v23i1.12095
Geni, L., Yulianti, E., & Sensuse, D. I. (2023). Sentiment Analysis of Tweets Before the 2024 Elections in Indonesia Using Bert Language Models. Jurnal Ilmiah Teknik Elektro Komputer Dan Informatika, 9(3), 746–757. https://doi.org/10.26555/jiteki.v9i3.26490
Gumilang, M. A., Abdillah, F., Amin, M. Y., & Hasan, M. (2024). Sentiment Analysis of Indonesian Ministries Social Media: Citizen Responses Utilizing TextBlob Analyser. Jurnal Sosioteknologi, 23(2), 203–216. https://doi.org/10.5614/sostek.itbj.2024.23.2.5
Hafizah, R., Saragih, T. H., Muliadi, M., Indriani, F., & Mazdadi, M. I. (2025). Machine Learning Implementation for Sentiment Analysis on X/Twitter: Case Study of Class Of Champions Event in Indonesia. Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics, 7(2), 370–386. https://doi.org/10.35882/ijeeemi.v7i2.81
Hoffmann, J., Borgeaud, S., Mensch, A., Buchatskaya, E., Cai, T., Rutherford, E., Casas, D. de Las, Hendricks, L. A., Welbl, J., Clark, A., Hennigan, T., Noland, E., Millican, K., Driessche, G. van den, Damoc, B., Guy, A., Osindero, S., Simonyan, K., Elsen, E., … Sifre, L. (2022). Training Compute-Optimal Large Language Models. http://arxiv.org/abs/2203.15556
Ilmi, M. H., & Puspitarani, Y. (2024). Visualization of Sentiment Analysis Results of Public Opinion on Indonesian Public Figures in Electronic Media and Social Media. Proceedings of the Widyatama International Conference on Engineering 2024 (WICOENG 2024). https://doi.org/10.2991/978-94-6463-618-5_34
Jonnala, N. S., Ram Teja, A. V. S., Rajeswari, S. R., Jakeer, S., Dheeraj, A., Bansal, S., Prakash, K., Singh, S., Faruque, M. R. I., & Al-mugren, K. S. (2025). Leveraging hybrid model for accurate sentiment analysis of Twitter data. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-025-09794-2
Koto, F., Rahimi, A., Lau, J. H., & Baldwin, T. (2020). IndoLEM and IndoBERT: A Benchmark Dataset and Pre-trained Language Model for Indonesian NLP. COLING 2020 - The 28th International Conference on Computational Linguistics. https://huggingface.co/
Kumar C, Y. (2024). Review of Cloud Migration Strategies: Exploring Advantages, Challenges and Cost Analysis. INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT, 08(06), 1–5. https://doi.org/10.55041/IJSREM35549
Kumar, L., Sharma, J., & Kaur, R. (2022). Catalytic Performance of Cow-Dung Sludge in Water Treatment Mitigation and Conversion of Ammonia Nitrogen into Nitrate. Sustainability (Switzerland), 14(4). https://doi.org/10.3390/su14042183
Kutzner, C., Kniep, C., Cherian, A., Nordstrom, L., Grubmüller, H., De Groot, B. L., & Gapsys, V. (2022). GROMACS in the Cloud: A Global Supercomputer to Speed Up Alchemical Drug Design. Journal of Chemical Information and Modeling, 62(7), 1691–1711. https://doi.org/10.1021/acs.jcim.2c00044
Li, H., Ota, K., Dong, M., Vasilakos, A. V., & Nagano, K. (2020). Multimedia Processing Pricing Strategy in GPU-Accelerated Cloud Computing. IEEE Transactions on Cloud Computing, 8(4), 1264–1273. https://doi.org/10.1109/TCC.2017.2672554
Md Suhaimin, M. S., Ahmad Hijazi, M. H., Moung, E. G., Nohuddin, P. N. E., Chua, S., & Coenen, F. (2023). Social media sentiment analysis and opinion mining in public security: Taxonomy, trend analysis, issues and future directions. In Journal of King Saud University - Computer and Information Sciences (Vol. 35, Issue 9). King Saud bin Abdulaziz University. https://doi.org/10.1016/j.jksuci.2023.101776
Nawrocki, P., & Osypanka, P. (2021). Cloud Resource Demand Prediction using Machine Learning in the Context of QoS Parameters. Journal of Grid Computing, 19(2). https://doi.org/10.1007/s10723-021-09561-3
Oluwatobi, H. (2023). Cloud Computing and the Democratization of Artificial Intelligence in Business. https://www.researchgate.net/publication/391163241
Puspasari, H. M., Mustaqim, I. Z., Utami, A. T., Syalevi, R., & Ruldeviyani, Y. (2024). Evaluation of Indonesia’s police public service platforms through sentiment and thematic analysis. IAES International Journal of Artificial Intelligence, 13(2), 1596–1607. https://doi.org/10.11591/ijai.v13.i2.pp1596-1607
Sanh, V., Webson, A., Raffel, C., Bach, S. H., Sutawika, L., Alyafeai, Z., Chaffin, A., Stiegler, A., Scao, T. Le, Raja, A., Dey, M., Bari, M. S., Xu, C., Thakker, U., Sharma, S. S., Szczechla, E., Kim, T., Chhablani, G., Nayak, N., … Rush, A. M. (2022). Multitask Prompted Training Enables Zero-Shot Task Generalization. ICLR 2022. http://arxiv.org/abs/2110.08207
Seritan, S., Thompson, K., & Martínez, T. J. (2020). Tera Chem Cloud: A High-Performance Computing Service for Scalable Distributed GPU-Accelerated Electronic Structure Calculations. Journal of Chemical Information and Modeling, 60(4), 2126–2137. https://doi.org/10.1021/acs.jcim.9b01152
Shojaee Rad, Z., & Ghobaei-Arani, M. (2024). Data pipeline approaches in serverless computing: a taxonomy, review, and research trends. Journal of Big Data, 11(1). https://doi.org/10.1186/s40537-024-00939-0
Sri Nandhini, A. R., & Joseph, A. (2020). Impact of Implementing Cloud Native Applications in Replacement to on-Premise Applications. International Journal of Engineering Research & Technology (IJERT). www.ijert.org
Wulf, F., Dresden, T. U., Lindner, T., Westner, M., Regensburg, O., & Strahringer, S. (2021). IaaS, PaaS, or SaaS? The Why of Cloud Computing Delivery Model Selection-Vignettes on the Post-Adoption of Cloud Computing. Proceedings of the 54th Hawaii International Conference on System Sciences. https://hdl.handle.net/10125/71378
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Novantri Prasetya Putra (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
Share
Similar Articles
- Shobrun Jamil Bagastio, M.Ahyar Harizillah, Muhammad Arya Pramudya Subekti, PERAN PROSES BISNIS DALAM TRANSFORMASI DIGITAL UKM: SYSTEMATIC LITERATURE REVIEW MENGENAI TEKNOLOGI YANG DIADOPSI , SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan: Vol. 1 No. 1 (2024): January
- Rifki Nugraha Nurilahi, Mohammad Miswan, RD. Rokhmad Saedudin, PROSES BISNIS MANAGEMENT OPEN API MEDICAL RECORD PASIEN BERBASIS CLOUD COMPUTING , SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan: Vol. 1 No. 1 (2024): January
- Fannzy Bayu Askar Prajaya, Riko Reky Londong, Syifa Nuurunnisa Wijaksana, ANALISIS PERBANDINGAN SIX SIGMA DAN LEAN MANAGEMENT UNTUK PENINGKATAN KUALITAS OPERASIONAL PADA BIDANG USAHA BERBASIS LAYANAN : A LITERATUR REVIEW , SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan: Vol. 1 No. 1 (2024): January
- Putry Wahyu Setyaningsih, Putri Taqwa Prasetyaningrum, Implementasi Business Intelligence Untuk Menganalisis Jumlah Mahasiswa Baru Tahun 2024 di Universitas Mercu Buana Yogyakarta , SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan: Vol. 2 No. 1 (2025): January
- Alaric Rasendriya Aniko, Alif Noorachmad Muttaqin, Muhamad Ivan Fadilah, BUSINESS PROCESS MANAGEMENT IN IT COMPANY: SYSTEMATIC LITERATURE REVIEW , SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan: Vol. 1 No. 2 (2024): July
- Mercy Kristina Possumah, Yulio Ferdinand, Neca Aqila, Muharman Lubis, Peran Manajemen Pengetahuan dalam Pengembangan Kompetisi dan Kinerja Pegawai di Perguruan Tinggi : Pendekatan Study Literature Review , SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan: Vol. 2 No. 3 (2025): July
- Nida Nida Lutfiyah, A. Hamdani, Cahyo Prabowo, Perancangan Dashboard Digital Untuk Monitoring Kinerja Organisasi Serta Informasi Untuk Pelanggan Pada PT PLN (Persero) UP3 Banyuwangi , SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan: Vol. 2 No. 4 (2025): October
- Nenden Eva, Rahma Karina, Septiya Mutiara, RD. Rohmat Saedudin, ANALISIS JAMINAN KUALITAS SISTEM KEAMANAN SIBER PADA SISTEM INFORMASI : SEBUAH STUDI LITERATUR , SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan: Vol. 1 No. 2 (2024): July
- Cindy Muhdiantini, Mega Fitri Yani, Ilham Auliya Rahman, Ati Maryati, Data Mining Clustering and Correlation Analysis of Marine Potential Insights from Capture Fisheries Coral Reef Quantity and Plankton Abundance , SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan: Vol. 2 No. 1 (2025): January
- Fima Yardhaka Kabira, Bagus Saputro, Dewi Setiowati, Peran Mahasiswa IT dalam Meningkatkan Kesadaran Privasi di Media Sosial pada Era Digital , SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan: Vol. 2 No. 4 (2025): October
You may also start an advanced similarity search for this article.
