BAGUS AJI PRAKOSO, NPM 2109100108 (2025) IMPLEMENTASI ALGORITMA K-MEANS PADA MINAT KONTEN TIKTOK TERHADAP PERILAKU MASYARAKAT DESA LINGGA TIGA. Skripsi thesis, Universitas Labuhanbatu.
![[img]](http://repository.ulb.ac.id/style/images/fileicons/text.png) |
Text
COVER.pdf Download (555kB) |
|
Text
BAB I.pdf Download (245kB) |
|
Text
BAB II.pdf Download (286kB) |
|
Text
BAB III.pdf Download (514kB) |
|
Text
BAB IV.pdf Download (1MB) |
|
Text
BAB V.pdf Download (46kB) |
|
Text
DAFTAR PUSTAKA.pdf Download (117kB) |
Abstract
Penelitian ini bertujuan untuk mengelompokkan masyarakat Desa Lingga Tiga berdasarkan minat terhadap jenis konten TikTok serta menganalisis keterkaitannya dengan perilaku sosial yang ditunjukkan. Data dikumpulkan melalui kuesioner yang disebarkan kepada responden. Variabel penelitian mencakup durasi penggunaan TikTok, motivasi penggunaan aplikasi, fokus minat pada jenis konten tertentu, tingkat interaksi dalam aplikasi, partisipasi dalam pembuatan konten dan keterlibatan dalam percakapan sosial di luar platform. Analisis data dilakukan dengan metode K-Means Clustering menggunakan perangkat lunak RapidMiner untuk menemukan pola pengelompokan responden. Hasil pengolahan data menghasilkan tiga klaster utama yaitu: (1) Responden pengguna moderat dalam Cluster 1 termasuk dalam kategori pengguna moderat, (2) Responden dalam Cluster 2 tergolong sebagai pengguna aktif, serta (3) Responden dalam Cluster 3 diklasifikasikan sebagai pengguna pasif. Penelitian ini diharapkan dapat mengidentifikasi karakteristik konten TikTok yang paling sering diminati oleh masyarakat Desa Lingga Tiga, mengevaluasi persepsi dan respon masyarakat Desa Lingga Tiga terhadap konten-konten TikTok yang mereka tonton setiap hari, dan menerapkan algoritma K-Means dalam proses pengelompokan pola perilaku masyarakat Desa Lingga Tiga Kata Kunci: K-Means Clustering, TikTok, Minat Konten, Perilaku Sosial, Analisis Klaster ============================================== This study aims to categorize the residents of Lingga Tiga Village based on their interest in TikTok content and analyze its relationship to their social behavior. Data were collected through questionnaires distributed to respondents. Research variables included duration of TikTok use, motivation for using the app, focus of interest in specific content types, level of interaction within the app, participation in content creation, and engagement in social conversations outside the platform. Data analysis was conducted using the K-Means Clustering method using RapidMiner software to identify respondent grouping patterns. The data processing resulted in three main clusters: (1) Respondents with moderate users in Cluster 1 are categorized as moderate users, (2) Respondents in Cluster 2 are classified as active users, and (3) Respondents in Cluster 3 are classified as passive users. This study aims to identify the characteristics of TikTok content most frequently viewed by the residents of Lingga Tiga Village, evaluate the perceptions and responses of the residents of Lingga Tiga Village to the TikTok content they watch daily, and apply the K-Means algorithm to cluster the behavioral patterns of the residents of Lingga Tiga Village. Keywords: K-Means Clustering, TikTok, Content Interest, Social Behavior, Cluster Analysis
| Item Type: | Thesis (Skripsi) |
|---|---|
| Uncontrolled Keywords: | K-Means Clustering, TikTok, Minat Konten, Perilaku Sosial, Analisis Klaster===============K-Means Clustering, TikTok, Content Interest, Social Behavior, Cluster Analysis |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General) Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4450 Databases |
| Divisions: | Fakultas Sains Dan Teknologi > Sistem Informasi |
| Depositing User: | Unnamed user with email repository@ulb.ac.id |
| Date Deposited: | 21 Oct 2025 09:04 |
| Last Modified: | 21 Oct 2025 09:04 |
| URI: | http://repository.ulb.ac.id/id/eprint/1828 |
Actions (login required)
 |
View Item |
