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All Journal Jurnal Infra JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Teknik Informatika (JUTIF) Eduvest - Journal of Universal Studies Semar : Jurnal Sosial dan Pengabdian Masyarakat
Satria Adi Nugraha
Universitas Ciputra Surabaya
Aerospace Engineering Humanities Computer Science & IT Health Professions Neuroscience Social Sciences Other

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Aplikasi Analisa Sentimen Bilingual dan Emoji pada Komentar Media Sosial Instagram Menggunakan Metode Support Vector Machine Satria Adi Nugraha; Henry Novianus Palit; Hans Juwiantho
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Indonesia is ranked 4th as the most Instagram user in the world. This makes business people triggered to promote their products and services to content creators to make reviews and upload them on Instagram. Business people need to evaluate uploads to assess whether the promotions carried out get a positive or negative response from netizens. Evaluation can be done by checking the comments column. Instagram comments not only contain comments in Indonesian but in English along with emojis. However, checking manually will certainly take a lot of time. Therefore, it is necessary to build an application system that can detect bilingual sentiments and emojis in Instagram comments. This system was built using the Support Vector Machine method to classify language, Indonesian sentiment, and English sentiment and then evaluated using the accuracy value. The data used is a sample of uploaded comments in the form of posts, reels, and IGTV. The combination of preprocessing cleansing, normalization, stopwords removal, and stemming as well as parameter tuning using GridSearchCV was also tested to find the best model. The model is divided into language classification models with Indonesia, Inggris, and Campuran labels, Indonesian sentiment classifications, and English sentiment classifications with positive, neutral, and negative labels. The best accuracy obtained by the model for language classification, Indonesian sentiment, and English sentiment is 88.77%, 73.10%, and 71.56%, respectively. In addition, emojis need to be analyzed because the model that analyzes emojis has 3.875% better accuracy than the model that ignores emoji.
SMART TEACHING: PENERAPAN KECERDASAN BUATAN UNTUK MENDUKUNG EFEKTIVITAS PENGAJARAN Tjahjono, Laura Mahendratta; Sword, Felicia; Nugraha, Satria Adi; Jodhinata, Andreas
SEMAR : Jurnal Sosial dan Pengabdian Masyarakat Vol. 3 No. 1 (2025): Semar : Jurnal Sosial dan Pengabdian Masyarakat
Publisher : CV. Kalimasada Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59966/semar.v3i1.1616

Abstract

This research aims to explore the use of artificial intelligence (AI) in supporting teaching effectiveness and easing teachers' workload through the Smart Teaching: AI Solutions to Ease the Burden of Teachers training program. This activity was carried out in the form of a webinar organized by Ciputra University (UC) Informatics Online on January 23, 2025. The research method used is a qualitative descriptive study with an applied experiment approach, where webinar participants are introduced to various AI tools and directly practice their use in making lesson plans and developing AI-based teaching materials. The results showed a significant improvement in participants' understanding and skills related to the application of AI in teaching. A total of 92% of participants reported that they felt more prepared to integrate AI in the learning process, while 87% stated that the material provided was very relevant and applicable. The publication of research results is carried out through national journals with ISSN and mass media to expand the impact of this program. Additional outputs from this study include copyright-related training modules as evidence of innovative contributions in technology-based education. This study confirms that the use of AI in teaching can be an effective solution in easing the burden on teachers while improving the quality of education. Therefore, the sustainable development of AI-based training programs is recommended to support digital transformation in the world of education.
PENERAPAN LEXICON BASED UNTUK ANALISIS SENTIMEN MASYARAKAT INDONESIA TERHADAP DANANTARA Adi Nugraha, Satria
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 3 (2025): JATI Vol. 9 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i3.13836

Abstract

Investasi strategis melalui sovereign wealth fund (SWF) menjadi kebijakan yang semakin banyak diterapkan oleh berbagai negara, termasuk Indonesia yang baru saja meresmikan Badan Pengelola Investasi Daya Anagata Nusantara (Danantara) pada Februari 2025. Meskipun memiliki tujuan utama untuk meningkatkan efisiensi pengelolaan aset strategis dan menarik investasi global, keberadaan Danantara menimbulkan beragam opini publik, terutama di media sosial seperti Twitter. Penelitian ini bertujuan untuk menganalisis sentimen masyarakat Indonesia terhadap Danantara menggunakan metode Lexicon-Based Sentiment Analysis. Penelitian ini diharapkan dapat memberikan wawasan bagi pemerintah dan pemangku kepentingan dalam meningkatkan strategi komunikasi, transparansi kebijakan, serta membangun kepercayaan publik terhadap pengelolaan investasi nasional. Data dikumpulkan dari Twitter dan diolah melalui tahapan pre-processing serta pencocokan dengan kamus sentimen berbahasa Indonesia. Hasil analisis menunjukkan bahwa sentimen publik terhadap Danantara cenderung beragam dengan dominasi negatif (44.9%) sedikit lebih banyak daripada positif (44.1%) dan sisanya merupakan sentimen netral (14%). Faktor-faktor seperti transparansi kebijakan dan persepsi terhadap pengelolaan investasi berkontribusi terhadap variasi sentimen ini.
Actual Purchase on Live Streaming TikTok Shop: The Influence of Trust, Flow Experience, and IT Affordance Nugraha, Satria Adi; Widjanarko Otok, Bambang
Eduvest - Journal of Universal Studies Vol. 5 No. 1 (2025): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v5i1.1565

Abstract

The use of live streaming technology has transcended its marketing function, evolving into a platform for fostering deeper interactions between sellers and consumers. The accessibility of technology, trust, and the flow experience play crucial roles in facilitating transactions within the context of live streaming commerce. These factors influence consumer desire to make purchases and ultimately drive actual purchases. This research aims to investigate the influence of these factors on purchase intention and actual purchases within the context of live streaming commerce services in Indonesia. The data analysis method employed is SEM-PLS, with TikTok as the research subject. TikTok, through its TikTok Shop platform, has become one of the primary choices for live streaming commerce services in Indonesia, with 6 million users as sellers and 7 million users as affiliates. The results of this study show that visibility affordance, metavoicing affordance, and guidance shopping affordance can affect purchase intention which in turn affects actual purchases by customers through trust in seller, trust in platform, and immersion. This research not only provides valuable insights for practitioners and sellers in the field of live streaming commerce, but also provides a foundation for the development of technology platforms that meet market needs.
Comparative Analysis of IndoBERT and mBERT for Online Gambling Comment Detection in Indonesian Social Media Nugraha, Satria Adi; Lestari, Citra; Sanjaya, Karyna Budi; Naya, Rafi Abhista; Jolie, Jocelyn
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 2 (2026): JUTIF Volume 7, Number 2, April 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.2.5677

Abstract

The rapid growth of illegal online gambling promotions in Indonesian social media comments requires automated detection systems capable of handling informal and noisy text. This study aims to evaluate the effectiveness of Transformer-based language models for detecting online gambling-related comments in Indonesian Twitter and YouTube data. Two pre-trained models, IndoBERT and mBERT, were fine-tuned and compared using a labeled dataset consisting of gambling and non-gambling comments. Model performance was evaluated using accuracy, precision, recall, and F1-score. Experimental results show that IndoBERT achieved 98% accuracy and F1-score, outperforming mBERT, which achieved 96% on the same dataset. Additionally, performance was compared against a recurrent neural network baseline to validate the effectiveness of Transformer-based architectures. The findings demonstrate that language-specific pre-training provides measurable advantages for detecting domain-specific content in Indonesian social media. This study contributes empirical evidence supporting the application of Transformer models for automated moderation of harmful online content in Indonesian digital platforms.
Co-Authors Andreas Bambang Widjanarko Otok Citra Lestari Hans Juwiantho Henry Novianus Palit Jolie, Jocelyn Laura Mahendratta Tjahjono Naya, Rafi Abhista Sanjaya, Karyna Budi Sword, Felicia