| dc.contributor.advisor | Neyman, Shelvie Nidya | |
| dc.contributor.author | NAPOLEON, BERLIN | |
| dc.date.accessioned | 2026-07-27T13:16:03Z | |
| dc.date.available | 2026-07-27T13:16:03Z | |
| dc.date.issued | 2026 | |
| dc.identifier.uri | http://repository.ipb.ac.id/handle/123456789/175994 | |
| dc.description.abstract | Mahasiswa perguruan tinggi merupakan kelompok rentan terhadap ancaman
keamanan siber akibat tingginya intensitas penggunaan teknologi digital. Penelitian
ini bertujuan mengukur tingkat literasi keamanan siber, mengelompokkan profil
mahasiswa, mengidentifikasi karakteristik setiap klaster, dan menyusun
rekomendasi edukasi adaptif. Survei dilakukan terhadap 204 mahasiswa IPB
University yang belum mengambil mata kuliah keamanan informasi, terdiri dari
130 mahasiswa IT dan 74 mahasiswa Non-IT, menggunakan instrumen berbasis
skala Likert empat poin pada dimensi Knowledge dan Attitude. Uji reliabilitas
dengan Cronbach's Alpha menghasilkan nilai 0,912 (Knowledge IT), 0,797
(Attitude IT), 0,768 (Knowledge Non-IT), dan 0,770 (Attitude Non-IT), seluruhnya
memenuhi ambang batas reliabel. Algoritma K-Means Clustering dengan
Silhouette Score (K=2 optimal: IT=0,442; Non-IT=0,414) menghasilkan dua
klaster pada masing-masing kelompok. Klaster IT Literasi Tinggi (n=68) memiliki
skor kumulatif 3,182, sedangkan Klaster IT Literasi Medium (n=62) memperoleh
2,254. Pada Non-IT, Klaster Literasi Tinggi (n=37) memperoleh 3,576 dan Klaster
Literasi Medium (n=37) memperoleh 2,966. Analisis tujuh tema literasi
menunjukkan Social Engineering sebagai kelemahan utama kelompok IT,
sementara WiFi & Safe Browsing menjadi kelemahan utama klaster Non-IT Literasi
Medium. Rekomendasi edukasi disusun secara terdiferensiasi per klaster untuk
meningkatkan efektivitas intervensi keamanan siber di lingkungan perguruan tinggi | |
| dc.description.abstract | University students are a vulnerable group to cybersecurity threats due to
their high intensity of digital technology use. This study aims to measure students'
cybersecurity literacy levels, cluster their profiles, identify cluster characteristics,
and develop adaptive educational recommendations. A survey was conducted on
204 IPB University students who had not taken information security courses,
comprising 130 IT students and 74 Non-IT students, using a four-point Likert scale
instrument measuring Knowledge and Attitude dimensions. Reliability testing using
Cronbach's Alpha yielded values of 0.912 (IT Knowledge), 0.797 (IT Attitude),
0.768 (Non-IT Knowledge), and 0.770 (Non-IT Attitude), all meeting the reliability
threshold. K-Means Clustering with Silhouette Score (optimal K=2: IT=0.442;
Non-IT=0.414) produced two clusters for each group. The IT High Literacy cluster
(n=68) achieved a cumulative score of 3.182, while the IT Medium Literacy cluster
(n=62) scored 2.254. For Non-IT students, the High Literacy cluster (n=37) scored
3.576 and the Medium Literacy cluster (n=37) scored 2.966. Analysis of seven
literacy themes revealed Social Engineering as the primary weakness for IT groups,
while WiFi and Safe Browsing was the main weakness for Non-IT Medium Literacy
cluster. Differentiated educational recommendations were developed per cluster to
improve the effectiveness of cybersecurity interventions in higher education settings. | |
| dc.description.sponsorship | | |
| dc.language.iso | id | |
| dc.publisher | IPB University | id |
| dc.title | Analisis Klasterisasi Profil Keamanan Siber Mahasiswa untuk Penentuan Strategi Edukasi | id |
| dc.title.alternative | Cluster Analysis of Student Cybersecurity Profiles for Determining Educational Strategies | |
| dc.type | Skripsi | |
| dc.subject.keyword | keamanan siber | id |
| dc.subject.keyword | K-Means clustering | id |
| dc.subject.keyword | literasi siber | id |
| dc.subject.keyword | Mahasiswa | id |
| dc.subject.keyword | Silhouette Score | id |
| dc.subject.keyword | cybersecurity literacy | id |
| dc.subject.keyword | Cybersecurity | id |
| dc.subtype | Undergraduate Theses | |