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All Journal JURNAL MULTIDISIPLIN ILMU AKADEMIK Journal of Information Systems and Business Technology
Adit Pradika Yoga Putra
Universitas Pamulang
Religion Humanities Computer Science & IT Law, Crime, Criminology & Criminal Justice Library & Information Science Medicine & Pharmacology Social Sciences

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ANALISIS DAN PERANCANGAN SISTEM INFORMASI MANAJEMEN PARKIR BERBASIS WEBSITE MENGGUNAKAN METODE PROTOTYPE DENGAN STANDAR ISO/IEC 25010 (ON PROJECT: PT. TEKNOLOGI INFORMATIKA SOLUSINDO) Delia Ramadani; Adit Pradika Yoga Putra; Chairul Anwar
JURNAL MULTIDISIPLIN ILMU AKADEMIK Vol. 3 No. 3 (2026): JUNI
Publisher : CV. KAMPUS AKADEMIK PUBLISHING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/jmia.v3i3.10367

Abstract

Perkembangan teknologi informasi mendorong berbagai institusi untuk menerapkan sistem digital guna meningkatkan efektivitas dan efisiensi operasional, termasuk dalam pengelolaan parkir. PT. Teknologi Informatika Solusindo masih menggunakan sistem parkir manual yang menimbulkan kendala pada proses pencatatan kendaraan, monitoring, dan pelaporan data parkir. Penelitian ini bertujuan untuk merancang dan membangun Sistem Informasi Manajemen Parkir berbasis website menggunakan metode Prototype serta melakukan pengujian kualitas sistem berdasarkan standar ISO/IEC 25010. Sistem dikembangkan menggunakan framework Laravel, database MySQL, dan antarmuka berbasis Bootstrap, kemudian diuji melalui delapan karakteristik ISO/IEC 25010 dengan melibatkan 31 responden. Hasil pengujian menunjukkan persentase keseluruhan sebesar 82% dengan kategori Sangat Baik, sehingga sistem dinilai mampu membantu proses pengelolaan parkir menjadi lebih efektif, terstruktur, dan mendukung kegiatan operasional secara optimal.
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 Bintang Maldini Chairul Anwar Delia Ramadani Muhammad Balad Al-Amin