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All Journal Journal of Information Systems and Business Technology
Bintang Maldini
Universitas Pamulang
Computer Science & IT Library & Information Science

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Analisis dan Perancangan Sistem Informasi Kursus Online Berbasis Website Menggunakan Standar ISO/IEC 25010 Bintang Maldini; Muhammad Putra Nugraha; Chairul Anwar
Journal of Information Systems and Business Technology Vol 2 No 3 (2026): Journal of Information Systems and Business Technology
Publisher : PT Jurnal Cendekia Indonesia

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Abstract

Transformasi digital dalam sektor pendidikan menuntut adanya sistem manajemen pembelajaran yang efisien dan terintegrasi. Penelitian ini bertujuan untuk melakukan analisis dan perancangan Sistem Informasi Kursus Online berbasis website pada studi kasus PT Teknologi Informatika Solusindo. Pengembangan sistem ini difokuskan untuk mengatasi kendala inefisiensi administrasi, pengelolaan data peserta, dan penyampaian materi yang belum terstruktur. Guna mencapai tujuan tersebut, penelitian ini mengimplementasikan metode prototype sebagai pendekatan rekayasa perangkat lunak yang iteratif dan responsif terhadap dinamika kebutuhan pengguna. Pasca tahap perancangan dan konstruksi, sistem dievaluasi secara komprehensif menggunakan standar mutu internasional ISO/IEC 25010. Pengujian kelayakan ini melibatkan pengukuran objektif terhadap delapan karakteristik utama kualitas perangkat lunak, yakni Functional Suitability, Performance Efficiency, Compatibility, Usability, Reliability, Security, Maintainability, dan Portability. Hasil pengujian secara akumulatif menunjukkan persentase kelayakan yang diklasifikasikan ke dalam kategori "Sangat Baik". Pencapaian ini mengindikasikan bahwa seluruh fitur sistem mampu beroperasi secara presisi, memiliki tingkat keandalan yang terjamin, serta memberikan kemudahan akses di berbagai platform. Sebagai kesimpulan, rancang bangun sistem informasi kursus online yang diusulkan dinilai sangat layak diimplementasikan guna mengotomatisasi proses bisnis pendidikan dan menunjang efektivitas operasional di PT Teknologi Informatika Solusindo.
Analisis Segmentasi Produk Menggunakan Algoritma K-Means Clustering pada Dataset Tokopedia Product Reviews 2025 Bintang Maldini; Muhammad Balad Al-Amin; Adit Pradika Yoga Putra
Journal of Information Systems and Business Technology Vol 2 No 3 (2026): Journal of Information Systems and Business Technology
Publisher : PT Jurnal Cendekia Indonesia

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Abstract

The rapid growth of e-commerce in Indonesia, particularly on the Tokopedia platform, has generated a large volume of customer review data that can be utilized to support business decision-making. This study aims to develop product segmentation based on customer review characteristics using data mining techniques to support Business Intelligence in e-commerce marketplaces. The dataset used is the Tokopedia Product Reviews 2025 dataset from Kaggle, consisting of 5,521 unique products aggregated from the original review data. The study follows the CRISP-DM methodology, including Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. Feature engineering was performed to generate analytical attributes, and the K-Means clustering algorithm was applied with the optimal number of clusters (k = 3), determined using the Elbow Method and Silhouette Score. The clustering results identified three product segments: High Quality (2,749 products), High Demand (one outlier product with exceptionally high sales), and High Volume (2,771 products). The resulting dataset was implemented as a Business Intelligence-ready dataset to support product performance monitoring and data-driven marketing strategy development.
Co-Authors Adit Pradika Yoga Putra Chairul Anwar Muhammad Balad Al-Amin Muhammad Putra Nugraha