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All Journal Angkasa: Jurnal Ilmiah Bidang Teknologi Jurnal INFOTEL
Santosa, Bagas Dwi
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Computer Science & IT Electrical & Electronics Engineering

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Analisa Jaringan dan Pola Penyedia Layanan Judi Online di Twitter menggunakan Social Network Analysis Santosa, Bagas Dwi; Fatimah, Nurul; Kusumaningtyas, Netania Indi; Aesyi, Ulfi Saidata
Angkasa: Jurnal Ilmiah Bidang Teknologi Vol 15, No 2 (2023): November
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/angkasa.v15i2.1778

Abstract

Lonjakan kasus perjudian online di Indonesia telah menyebabkan banyak individu kecanduan dan mengalami dampak negatif. Twitter kini menjadi platform yang sering digunakan oleh penyedia perjudian online yang menggunakan berbagai taktik pemasaran untuk menarik perhatian masyarakat. Oleh karena itu, analisis menjadi penting untuk mengidentifikasi jaringan pemain perjudian online dan memahami strategi yang digunakan oleh penyedia layanan tersebut. Dengan menggunakan Analisis Jaringan Sosial (SNA), penelitian ini mengungkapkan wawasan kunci, seperti akun Twitter dominan, hashtag yang sering digunakan, pola foto profil, dan kata kunci yang persuasif. Dalam jaringan ini, @slot_gacor_hari menonjol sebagai tokoh sentral dalam jaringan hashtag #slotgacor. Nilai tinggi dalam Degree Centrality, Closeness Centrality, Betweenness Centrality, dan Eigenvector Centrality menegaskan peran penting mereka dalam interaksi dan penyebaran informasi. Analisis ini membantu badan pemerintah, penegak hukum, dan lembaga terkait dalam menangani penyedia perjudian online dan merancang langkah pencegahan yang lebih efektif.
Sentimen Topik Menggunakan Regresi Logistik dan Alokasi Dirichlet Laten sebagai Model Analisis Kepuasan Pelanggan Cahyo, Puji Winar; Aesyi, Ulfi Saidata; Santosa, Bagas Dwi
JURNAL INFOTEL Vol 16 No 1 (2024): February 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i1.1081

Abstract

Buying and selling goods now is more interesting through e-commerce or marketplaces because of the ease of carrying out online transactions. Each transaction usually generates a response from the customer. The transaction response on the Shopee platform is still in paragraph form and needs to be more specific. Therefore, this research aims to build a model analysis of customer satisfaction using the best algorithm between support vector machine (SVM), random forest, and logistic regression. This research method uses sentiment classification with logistic regression because the logistic regression algorithm has the best accuracy, with an accuracy of 90.5. Meanwhile, the SVM algorithm achieved an accuracy of 90.4, and random forest reached 90.2. The three algorithms were tested three times, splitting data train:test at 80:20, 70:30, and 60:40. The best results were obtained by splitting data at 60:40. The best model is used to predict data without labels. The prediction produces 12,844 positive sentiment comment data, 112 negative sentiment comment data, and 70 neutral sentiment comment data. The results of this research continued to topic modeling using latent dirichlet allocation (LDA) to generate a trending topic of customer satisfaction on sales products. Implications of discussing each trend topic can be used as a reference for improving products and services, especially in communicating with customers.
Co-Authors Kusumaningtyas, Netania Indi Nurul Fatimah Puji Winar Cahyo Ulfi Saidata Aesyi