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All Journal snimed Seminar Nasional Aplikasi Teknologi Informasi (SNATI) JUPITER (Jurnal Pendidikan Teknik Elektro) Proceeding SENDI_U JMAI (Jurnal Multimedia & Artificial Intelligence) Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat Infotech: Journal of Technology Information Proceeding of International Conference Health, Science And Technology (ICOHETECH) Bengawan :Jurnal Pengabdian Masyarakat Journal Of Artificial Intelligence And Software Engineering Jurnal Sains, Nalar, dan Aplikasi Teknologi Informasi
Suryani, Fajar
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Medicine & Pharmacology Social Sciences Other

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Journal : Journal Of Artificial Intelligence And Software Engineering

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Instagram Influencer Recommendation System Based On Content-Based Filtering To Support Digital Marketing Strategy Az Zahra, Erika Oktaviana; Pramono, Pramono; Suryani, Fajar
Journal of Artificial Intelligence and Software Engineering Vol 5, No 2 (2025): Juni On-Progress
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i2.6939

Abstract

Influencer marketing is a popular promotional strategy on Instagram that involves influential individuals or public figures to promote products. However, there are problems where companies still find it difficult to find the right influencers. This research aims to build a Content-Based Filtering-based Instagram influencer recommendation system to support digital marketing strategies. The system development method used is Rapid Application Development (RAD) with 4 stages, namely requirements planning, system design, development, and implementation. With this system, users can recommend other influencers who have similar characteristics such as number of followers, average likes, and comments, engagement rate, and growth rate. System testing was conducted on 10 test data with different inputs. The results showed that 9 out of 10 tests matched the user input, indicating a system accuracy of 90% and has the potential to assist users in selecting relevant influencers.
Modeling Of Centralized Exchange (CEX) Crypto Asset Platform Recommendation System Using Collaborative Filtering Utomo, Diva Reihan Ferdian; Nastiti, Faulinda Ely; Suryani, Fajar
Journal of Artificial Intelligence and Software Engineering Vol 5, No 3 (2025): September
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i3.7179

Abstract

The rapid growth of crypto assets and the variety of Centralized Exchange (CEX) platforms make it difficult for traders to choose a platform that fits their preferences. This research aims to model a recommendation system for CEX platforms using Collaborative Filtering. User rating data for several CEX (Binance, Bybit, Bitget, Tokocrypto, Indodax) were collected via questionnaire. The K-Nearest Neighbors With Means (KNN With Means) method with cosine similarity is used to predict ratings based on the similarity of preferences between users. The model was trained and tested with a 75:25 train-test split. Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) were used as evaluation metrics. Test results show low MAE and RMSE values (around below 1.0 on a 1–5 rating scale), indicating that the recommendations generated are quite accurate. It can be concluded that the Collaborative Filtering approach is effective in recommending CEX platforms according to user needs. This recommendation system is expected to assist traders – especially beginners – in choosing the right exchange more objectively.
Co-Authors Abdul Aziz, Fitroh Ahmad Agustina Sri Rahayu Agustina Srirahayu Az Zahra, Erika Oktaviana Brima Aribowo Cipto Utomo, Bangun Prajadi Dwi Hartanti Faulinda Ely Nastiti Fitri Amelia Ganesan, Thinesh Indra Adidaya Iswardani, Ardymulya Moh. Muhtarom, Moh. Nahrin, Sari Nuralita Nurchim Nurchim Permatasari, Dian Anggraheni Pramono Pramono Prasetya, Ian Putra Rahadian Kurniawan Rahman, Farid Fadlu Rudi Susanto Sasmito, Dinda Eling Kartikaning Triyono Triyono Triyono Utomo, Diva Reihan Ferdian Yuliana, Margaretha Evi