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All Journal Journal of Communication Studies Prosiding SENTIMETER : Seminar Nasional Teknologi Informasi, Mekatronika, dan Ilmu Komputer
Bayu Putra
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Languange, Linguistic, Communication & Media Social Sciences

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Eksplorasi dan Analisis Data Mining untuk Prediksi Pola Konsumen Menggunakan Teknik Klasifikasi dan Clustering Muhammad Fajar Satria Adam; Bayu Putra; Syachra Indyra Puteri; Alfian Fajrissiddiq; Wafaunnisa; Lusiana Sani Parwati
Prosiding Seminar Nasional Teknologi Informasi, Mekatronika, dan Ilmu Komputer Vol 4 (2025): Sentimeter 2025
Publisher : Prosiding Seminar Nasional Teknologi Informasi, Mekatronika, dan Ilmu Komputer

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Abstract

Di era digital saat ini, pemahaman yang mendalam terhadap perilaku konsumen menjadi faktor kunci dalam merancang strategi bisnis yang efektif. Penelitian ini bertujuan untuk menerapkan teknik data mining dalam memprediksi pola perilaku konsumen melalui pendekatan klasifikasi dan clustering. Dataset yang digunakan mencakup informasi demografis, riwayat transaksi, preferensi produk, serta interaksi digital konsumen. Metodologi yang digunakan menggabungkan pendekatan kuantitatif dan kualitatif, dengan menerapkan algoritma Random Forest dan Support Vector Machine (SVM) untuk klasifikasi, serta K-Means dan Hierarchical Clustering untuk segmentasi. Proses analisis diawali dengan data preprocessing seperti pembersihan data, normalisasi, dan seleksi fitur. Hasil klasifikasi menunjukkan bahwa algoritma Random Forest mampu mencapai akurasi hingga 85%, sementara SVM mencapai 82% dalam memprediksi kecenderungan pembelian konsumen. Selain itu, hasil clustering berhasil mengidentifikasi lima segmen konsumen dengan karakteristik perilaku yang berbeda, yang dapat menjadi dasar pengembangan strategi pemasaran yang lebih tepat sasaran. Temuan ini menunjukkan bahwa integrasi metode klasifikasi dan clustering dapat memberikan wawasan strategis yang bernilai bagi pengambilan keputusan bisnis berbasis data.
Sentiment Analysis and Communication Networks Towards Ridwan Kamil in #PilkadaJakarta2024 on Social Media X (Twitter) Bayu Putra; Yasir; Auradian Marta
Journal of Communication Studies Vol. 5 No. 2 (2025): JCS: Journal of Communication Studies
Publisher : Program Studi Komunikasi dan Penyiaran Islam, Fakultas Dakwah, Institut Agama Islam Sunan Giri Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37680/jcs.v5i2.7749

Abstract

The development of social media has changed the landscape of political communication, especially in shaping public opinion towards political actors ahead of regional head elections. This study aims to analyze public sentiment and the structure of communication networks towards Ridwan Kamil in the context of the 2024 Jakarta Pilkada on social media X (Twitter). The methods used include sentiment classification with the Naïve Bayes Classifier (NBC) algorithm and network analysis using the Social Network Analysis (SNA) approach through the Gephi software. A total of 2,000 tweets were analyzed after undergoing pre-processing stages, including cleaning, case folding, tokenizing, stopword removal, and stemming using TF-IDF. The classification results show that 45.6% of tweets are positive, 31.8% are neutral, and 22.6% are negative, with a model accuracy of 62.90% and a margin of error of ±2.56%. In terms of communication structure, the network was found to be fragmented and influenced by informal nodes such as @BungkusTukang, @NalarPolitik_, and @irenejuliency, while the @ridwankamil account played a strategic role as a liaison between clusters. The communication patterns formed followed the configuration of a personal star ego network and a bridge-type one. These findings indicate that digital political communication is dominated not only by official actors but also by non-institutional actors who significantly influence public discourse
Co-Authors Alfian Fajrissiddiq Auradian Marta Lusiana Sani Parwati Muhammad Fajar Satria Adam Syachra Indyra Puteri Wafaunnisa Yasir