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All Journal JMB : Jurnal Manajemen dan Bisnis
Yanti Susanti
Faculty of Technology and Business, Yatsi Madani University, Tangerang Banten
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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The Influence Of Influencer Marketing And Content Marketing On Consumer Purchasing Decisions On Social Media (Tiktok Case Study) Yanti Susanti; Mutia Haris; Aulia Kaila Rohmah
JMB : Jurnal Manajemen dan Bisnis Vol. 15 No. 1 (2026): JMB : Jurnal Manajemen dan Bisnis
Publisher : Universitas Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/jmb.v15i1.15999

Abstract

The development of social media, particularly TikTok, has driven change in digital marketing strategies through the utilization of Influencer marketing and Content Marketing. This study aims to analyze the influencer of influencer Marketing and Content Marketing on consumers' purchasing decisions on TikTok social media. The research method used is a quantitative approach with a survey design. Data were collected through Likert-scale questionnaires distributed online to 50 TikTok users, with the sampling technique determined using the Slovin formula. Data analysis was conducted using IBM SPSS Statistics 25, including validity tests, reliability tests, T-tests, F-tests, and coefficient of determination analysis. The results indicate that Influencer Marketing and Content Marketing have a significant effect on purchasing decisions. The coefficient of determination shows that both independent variables are able to Influence purchasing decisions by 89,7%, while the remaining percentage is Influenced by other variables outside this study. These findings suggest that marketing strategies through Influencer Marketing and Content Marketing on TikTok play an important role in encouraging consumers' purchasing decisions on TikTok social media
Optimization Of Posting Time And Personalization Of Machine Learning-Based Content To Increase The Engagement Rate Of Gen Z Audiences On Social Media Platforms Nanda Ayu Frastika; Yanti Susanti; Nisma Natasha Arla
JMB : Jurnal Manajemen dan Bisnis Vol. 15 No. 1 (2026): JMB : Jurnal Manajemen dan Bisnis
Publisher : Universitas Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/jmb.v15i1.16006

Abstract

Digital transformation has presented new challenges in marketing communication strategies, especially in reaching Generation Z audiences who have very dynamic content consumption characteristics. This study explores the integration of publication time optimization with content personalization using a machine learning approach to increase engagement rates on social media platforms. Through a survey of 53 Gen Z respondents who are active users of TikTok, Instagram, and YouTube, data was collected using a structured questionnaire on the Likert scale to measure eleven digital behavior variables. Descriptive statistical analysis and multiple linear regression were used to identify engagement patterns, while Random Forest and Gradient Boosting algorithms were implemented to build an optimal post-time predictive model. The findings showed that the content personalization algorithm gained a very positive reception with a score of 4.26 on a scale of 5, while posting time correlated significantly with audience engagement rates. The Random Forest model achieved 84.7% accuracy in predicting engagement patterns with an accuracy of 87.2%. The integration of the two strategies resulted in a 2.3-fold increase in interaction compared to the single approach. The research provides concrete recommendations regarding the optimal hours of content publication for each platform as well as a data-driven personalization implementation framework for user behavior that can be applied by content creators and digital marketing practitioners in designing more effective and measurable communication strategies.
Co-Authors Aulia Kaila Rohmah Mutia Haris Nanda Ayu Frastika Nisma Natasha Arla