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All Journal Jurnal Informatika Teknologi dan Sains (Jinteks) E-JRM
Ulfa, Mariana
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance

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ANALISIS SENTIMEN REVIEW APLIKASI IDENTITAS KEPENDUDUKAN DIGITAL DI GOOGLE PLAY STORE MENGGUNAKAN KNN Ulfa, Mariana; Kusumodestoni, R. Hadapiningradja; Sucipto, Adi
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 6 No 4 (2024): EDISI 22
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v6i4.4963

Abstract

The Digital Population Identity Application (IKD) is a government digital solution designed to facilitate public access to population data via mobile devices. This study aims to analyze the sentiment of user reviews for the Digital Population Identity (IKD) application available on the Google Play Store, employing the K-Nearest Neighbor (KNN) algorithm. The methodology encompasses data collection, preprocessing, division of data into training and testing sets, and the application of KNN with varying values of k. The findings reveal that the model utilizing k=17 with a 70:30 ratio attained an accuracy of 82%, alongside precision of 79%, recall of 82%, F1 Score of 79%, and a micro AUC value of 0.91. This model demonstrates effective identification of positive and negative sentiments; however, it encounters challenges in classifying neutral reviews. The study concludes that the Digital Population Identity (IKD) application is still regarded as relatively ineffective, given the significant percentage of negative sentiment, which accounts for 71.86% of the reviews. While the KNN algorithm proves effective for classification, enhancements in performance concerning the neutral class remain essential. Furthermore, variations in the value of k impact classification accuracy, and adjustments to the k parameter can enhance the model's overall performance.
Pengaruh Content Marketing, Influencer Marketing dan Personalisasi Iklan Terhadap Keputusan Pembelian Pada Tiktok Shop (Studi Kasus Pada Mahasiswa FEB Universitas Islam Malang) Ulfa, Mariana; Wahono, Budi; Ramadhan, Tri Sugiarti
E-JRM : Elektronik Jurnal Riset Manajemen E-JRM : Elektronik Jurnal Riset Manajemen Vol. 14 No. 01
Publisher : UNIVERSITAS ISLAM MALANG

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Abstract

Abstract Goals of the research is to analyzing and testing the affect of content marketing, influencer marketing, and advertising personalization on purchasing decisions on the TikTok Shop platform. Using a quantitative approaches, that have the population within 688 respondents, used the Malhotra formula. In this study, using fixed 100 respondents. Analyzing data used multiple linear regression, t test, and f test, also SPSS software to help the test the research hypothesis. The results show that content marketing, influencer marketing, and advertising personalization affecting the purchasing decisions on TikTok Shop significantly, with both partial and simultaneous. Keywords: Content Marketing, Influencer Marketing, Advertising, Personalization, Purchasing Decisions
Co-Authors Adi Sucipto, Adi R Hadapiningradja Kusumodestoni Ramadhan, Tri Sugiarti