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All Journal Jurnal Teknologi Informasi, Komputer, dan Aplikasinya (JTIKA ) IT-Edu: Jurnal Information Technology and Education
Deiva Verlyn Marjuki
Universitas Negeri Surabaya
Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering

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PENERAPAN DATA MINING MENGGUNAKAN ALGORITMA K-MEANS UNTUK ANALISIS DATA BELANJA ONLINE MAHASISWA Deiva Verlyn Marjuki; Mutyara Safitri; Harun Al Rosyid
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 8 No 1 (2026): Maret 2026
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v8i1.553

Abstract

This study was conducted to analyze the online shopping behavior of college students using the K-Means algorithm as a clustering technique in data mining. This study was motivated by the lack of systematic segmentation of student shopping behavior, which limits the understanding of purchasing characteristics within this consumer group. Unlike previous studies that mostly examine general retail customers or broad e-commerce users, this study specifically focuses on university students by integrating demographic and behavioral attributes. The originality of this study is reflected in the simultaneous use of six variables, namely gender, shopping time, product type, expenditure level, payment method, and purchase decision factors. Data were collected through an online survey involving 200 active college students. The research stages consisted of data cleaning, data category transformation using One-Hot Encoding, clustering model construction using the K-Means algorithm, and cluster evaluation using the Silhouette method. The evaluation results showed that the optimal number of clusters was k = 3, achieving the of 0.0913. Three distinct segments of college students' online shopping behavior were identified, providing insights that can support more targeted marketing strategies and student-oriented e-commerce services.
Pengembangan LMS EduDB Menggunakan PjBL untuk Meningkatkan Kemampuan Kognitif Siswa Pada Elemen Basis Data Deiva Verlyn Marjuki; Ersha Aisyah Elfaiz
IT-Edu : Jurnal Information Technology and Education Vol. 11 No. 03 (2026): Volume 11 No. 03 (2026)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/it-edu.v11i03.80064

Abstract

Data dasar pembelajaran di SMK Krian 1 Sidoarjo masih bersifat teoritis dan belum optimal menerapkan Project-Based Learning (PjBL), menyebabkan rendahnya pemahaman siswa. Penelitian ini bertujuan mengembangkan Learning Management System (LMS) berbasis Moodle dengan pendekatan PjBL untuk meningkatkan kemampuan kognitif siswa pada elemen basis data. Penelitian menggunakan metode Research and Development (R&D) dengan model ADDIE. Subjek penelitian adalah siswa kelas XI RPL 1 (kelas eksperimen) dan XI RPL 2 (kelas kontrol), masing-masing 36 siswa. Instrumen pengumpulan data meliputi wawancara, observasi, dan angket validasi ahli. Hasil Validasi ahli menunjukkan LMS EduDB sangat layak dengan persentase validasi: media pembelajaran (92,82%), materi pembelajaran (98,75%), modul terbuka (97,64%), dan soal (96%). Uji blackbox menunjukkan fungsionalitas optimal. Peningkatan kemampuan kognitif siswa menunjukkan nilai N-Gain kelas eksperimen 0,61 (kategori sedang), sedangkan kelas kontrol 0,06 (kategori rendah). LMS berbasis Moodle dengan PjBL terbukti efektif meningkatkan kemampuan kognitif siswa pada elemen basis data.
Co-Authors Ersha Aisyah Elfaiz Harun Al Rosyid Mutyara Safitri