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All Journal Jurnal Sintak Statistika
Arrafi, Adamsyam
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Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Decision Sciences, Operations Research & Management Mathematics

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The Influence of Post Frequency and Type of Platform Used on Follower Interest Levels Azzahra, Nabila; Utami, Bulan Purnama; Arrafi, Adamsyam; Handayani, Vitri Aprilla
JURNAL SINTAK Vol. 3 No. 1 (2024): SEPTEMBER 2024
Publisher : LPPM-ITEBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62375/jsintak.v3i1.381

Abstract

This study examines the influence of social media platform types and posting frequency on the level of follower interest in a content creator's account. The analysis results show that the type of platform (Instagram or TikTok) does not have a significant impact on follower interest. However, posting frequency is proven to have a substantial influence, with weekly frequency showing the most positive impact. The interaction between platform type and posting frequency does not demonstrate a significant effect. These findings suggest that content creators can focus on adjusting their posting frequency, particularly with a weekly schedule, to increase follower interest, without needing to worry about choosing between Instagram or TikTok platforms.
Analysis of International Tourist Visits Based on Nationality and Tourism Travel Characteristics Using Complete Linkage Handayani, Vitri Aprilla; Sulistyono, Eko; Arrafi, Adamsyam; Hayati, Nahrul
Statistika Vol. 25 No. 1 (2025): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v25i1.5801

Abstract

Abstract. This research aims to analyze the characteristics of international tourists in Indonesia using Clustering Method: Complete Linkage. The study successfully identified 5 distinct clusters based on nationality and tourism travel characteristics. The analysis showed significant differences between clusters in terms of country of origin, travel patterns, preferences, expenditure, and tourist activities. Cluster 1 was dominated by ASEAN and Middle Eastern countries with stable visitation patterns influenced by geographical proximity and cultural and business relationships. Cluster 2 was the largest group, encompassing various countries with holiday and business tourism characteristics, longer stays, and higher expenditure. Clusters 3, 4, and 5 each consisted of a single country: Timor Leste, Hong Kong, and Papua New Guinea respectively, with unique visitation patterns. Each cluster showed differences in travel purposes, length of stay, expenditure, and activities of interest. A deep understanding of each tourist group’s characteristics was crucial for developing more targeted tourism marketing strategies. The clustering results could be utilized for infrastructure planning, resource allocation, promotional strategies, and service improvements tailored to each group’s characteristics, thereby enhancing tourist experiences and Indonesia’s overall tourism competitiveness.
Co-Authors Azzahra, Nabila Eko Sulistyono Sulistyono Handayani, Vitri Aprilla Nahrul Hayati Utami, Bulan Purnama