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All Journal JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Buffer Informatika
Andin Sabilla Janna
Universitas Sriwijaya
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Mathematics

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Klasifikasi Pengalaman Pengguna pada Platform Digital Menggunakan Algoritma Random Forest Andin Sabilla Janna; M. Syaikh Azka; Zakirah Sabrina Putri Pasha; M. Putra Willy Nailis; Allsela Meiriza; Ken Ditha Tania; Ahmad Rifai
JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 8 No. 1 (2026): Juni 2026
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jasiek.v8i1.16915

Abstract

User experience on digital platforms was an important factor in determining service quality and platform success. This study classified user experience orientation based on User Interface (UI) and User Experience (UX) attributes using the Random Forest algorithm. The dataset was obtained from the Mendeley Data repository and contained 2,271 user evaluation records related to visual and functional elements across various digital platforms. The research stages included data normalization, label generation based on composite visual and functional scores, and model evaluation using 10-fold cross-validation. The results showed that Random Forest classified user experience orientation accurately and consistently, with an accuracy of 86.79%. Feature importance analysis indicated that Visual Hierarchy, Images and Multimedia, and Layout were the most influential attributes. These findings demonstrated that Random Forest was effective for analyzing user experience data and supporting digital platform improvement.
Analisis Pola Keputusan Pembelian di Tokopedia berbasis Machine Learning untuk Customer Relationship Management Andin Sabilla Janna; Tamara Juliyanti; Muhammad Bayu Samudra; Ali Ibrahim; Fathoni
Buffer Informatika Vol. 12 No. 1 (2026): Buffer Informatika
Publisher : Department of Informatics Engineering, Faculty of Computer Science, University of Kuningan, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/buffer.v12i1.571

Abstract

Pertumbuhan pesat platform e-commerce telah memengaruhi keputusan pembelian konsumen, khususnya pada marketplace seperti Tokopedia. Penelitian ini bertujuan menganalisis pola keputusan pembelian produk makanan dan minuman serta merumuskan implikasinya terhadap strategi Customer Relationship Management (CRM) berbasis data. Metode yang digunakan adalah pendekatan kuantitatif dengan dataset sebanyak 9.711 ulasan pelanggan yang diperoleh melalui Kaggle. Analisis dilakukan menggunakan Naive Bayes untuk klasifikasi keputusan pembelian ulang dan FP-Growth untuk menemukan pola asosiasi antara rating, harga, dan keputusan pembelian. Tahapan praproses meliputi pembersihan data, transformasi atribut, diskretisasi, serta pemrosesan teks menggunakan TF-IDF. Hasil penelitian menunjukkan bahwa Naive Bayes menghasilkan akurasi 60,18% dengan precision kelas Y sebesar 94,30%, namun recall masih dipengaruhi oleh ketidakseimbangan data. FP-Growth menunjukkan bahwa rating bintang 5 merupakan faktor paling dominan dalam pembelian ulang, dengan kombinasi rating bintang 5 dan harga sedang menghasilkan confidence tertinggi sebesar 98,6%. Temuan ini menegaskan pentingnya kepuasan pelanggan dan mendukung perumusan strategi CRM yang lebih terarah.
Co-Authors Ahmad Rifai Ali Ibrahim Allsela Meiriza Fathoni Ken Ditha Tania M. Putra Willy Nailis M. Syaikh Azka Muhammad Bayu Samudra Tamara Juliyanti Zakirah Sabrina Putri Pasha