Optical Marketplace and POS Integration Based on Content- Based Filtering
DOI:
https://doi.org/10.69916/jkbti.v5i3.580Keywords:
Optical Marketplace, Point of Sale (PoS), Content-Based Filtering, Recommendation System, System Integration, Cosine SimilarityAbstract
Manual transaction management in optical businesses often results in stock data discrepancies, delays in report preparation, and limited marketing reach. This study aims to develop an optical marketplace integrated with a Point of Sales (PoS) system to synchronize transaction and stock data in real-time. In addition, a Content-Based Filtering algorithm is implemented with binary product attribute weighting and customer preference profiles based on transaction frequency, combined with multi-channel Cosine Similarity calculations to generate product recommendations based on product characteristics and customer purchase history. The study was conducted through the stages of needs analysis, system design, implementation, and functional testing using the Black-box Testing method. The results show that the integration of the marketplace and PoS successfully maintains the consistency of transaction and stock data, while the Content-Based Filtering algorithm is able to provide product recommendations that match customer preferences. This study shows that the integration of the marketplace, Point of Sales, and recommendation systems can support the digitalization of optical businesses through more efficient data management and an improved customer shopping experience.
Downloads
References
K. D. Nurmayangsari and S. Widiono, “Transformasi Digital Layanan Laundry melalui Mobile Tracking untuk Meningkatkan Transparansi dan Efisiensi Operasional UMKM,” Edumatic J. Pendidik. Inform., vol. 9, no. 3, pp. 885–894, Dec. 2025, doi: 10.29408/edumatic.v9i3.32601.
D. Samputri and Halimah, “Pengembangan Sistem Manajemen Stok dan Penjualan Berbasis Web Dalam Mendukung Transformasi Digital Menggunakan Metode Prototype Pada Butik Merry’s Fashion Lampung,” J. Algoritma, vol. 23, no. 1, May 2026, doi: 10.33364/algoritma/v.23-1.3432.
M Romadhoni Adi Setiawan and Muhammad Yasin, “Peran E-Commerce dalam Meningkatkan Akses Pasar Industri UMKM,” Trending J. Manaj. Dan Ekon., vol. 4, no. 1, pp. 157–165, Jan. 2026, doi: 10.30640/trending.v4i1.5523.
Nurul Noviyana and Muhammad Irwan Padli Nasution, “Penerapan Teknologi Informasi Untuk Efektivitas dan Efisiensi Pengolahan Data Mahasiswa,” J. Ilm. Res. Dev. Stud., vol. 2, no. 1, pp. 152–160, Jan. 2024, doi: 10.59024/jis.v2i1.578.
Yuda Ardiansyah Pratama, Ahmad Jazuli, and Esti Wijayanti, “Rancang Bangun Sistem Informasi Manajemen Stok dan Penjualan Berbasis Website pada Toko Vanila Aksesoris,” J. Ekon. Manaj. Sist. Inf., vol. 6, no. 6, pp. 3817–3833, Jul. 2025, doi: 10.38035/jemsi.v6i6.5517.
Jonathan Arya Wibowo, Rachelina Putri Arta Saragih, and I. M. Insan, “Implementasi sistem Point of Sale (POS) pada UMKM Warung Makan Toba,” J. Pemanfaat. Teknol. Untuk Masy. J. Pengabdi. Masy., vol. 4, no. 5, Feb. 2026, doi: 10.59328/JAPATUM.2025.4.5.120.
I. Zhafirah, F. Wajidi, and A. A. Asnan Cirua, “Implementasi Hybrid Filtering (Collaborative dan Content Based) untuk Rekomendasi Kedai Kopi: Implementasi Hybrid Filtering (Collaborative dan Content Based) untuk Rekomendasi Kedai Kopi,” J. SISKOM-KB Sist. Komput. Dan Kecerdasan Buatan, vol. 9, no. 2, Mar. 2026, doi: 10.47970/siskom-kb.v9i2.919.
G. M. F. Fahmi, I. Tahyudin, and F. S. Utomo, “Peningkatan Akurasi Sistem Rekomendasi E-Commerce Collaborative Filtering dan Negative Sampling untuk Mengatasi Masalah Sparsity,” J. Algoritma, vol. 23, no. 1, May 2026, doi: 10.33364/algoritma/v.23-1.3198.
R. M. Harahap and A. N. Rachman, “SISTEM REKOMEDASI FILM BERDASARKAN KEMIRIPAN DESKRIPSI CERITA MENGGUNAKAN METODE CONTENT BASED FILTERING,” J. Inform. Dan Tek. Elektro Terap., vol. 13, no. 3, Jul. 2025, doi: 10.23960/jitet.v13i3.6577.
T. Ocsiana and R. A. Wijaya, “Sistem Informasi Web untuk Optimasi Stok dan Laporan Penjualan Beras di Toko Nurbila Sebagai Transformasi Digitalisasi UMKM Pangan,” J. Autom. Comput. Inf. Syst., vol. 5, no. 2, pp. 194–205, Nov. 2025, doi: 10.47134/jacis.v5i2.131.
B. Imran, M. N. Karim, and N. I. Ningsih, “Klasifikasi Berita Hoax Terkait Pemilihan Umum Presiden Republik Indonesia Tahun 2024 Menggunakan Naïve Bayes Dan Svm,” Din. Rekayasa, vol. 20, no. 1, pp. 1–9, 2024, doi: 10.20884/1.dinarek.2024.20.1.27.
B. Imran, H. Hambali, A. Subki, Z. Zaeniah, A. Yani, and M. R. Alfian, “Data Mining Using Random Forest, Naïve Bayes, and Adaboost Models for Prediction and Classification of Benign and Malignant Breast Cancer,” J. Pilar Nusa Mandiri, vol. 18, no. 1, pp. 37–46, 2022, doi: 10.33480/pilar.v18i1.2912.
D. H. Firdaus, B. Imran, L. D. Bakti, and E. Suryadi, “Klasifikasi Penyakit Katarak Pada Mata Menggunakan Metode Convolutional Neural Network ( Cnn ) Berbasis Web Web-Based Classification of Cataract in the Eyes Using Convolutional Neural Network ( Cnn ) Method,” J. Kecerdasan Buatan dan Teknol. Inf., vol. 1, no. 3, pp. 18–26, 2022.
R. Mujahiddin, Zaeniah, and B. Imran, “Rancang Bangun Sistem Pakar Diagnosa Penyakit Pada Tanaman Cabai Dengan Metode Certainty Factor,” J. Kecerdasan Buatan dan Teknol. Inf., vol. 2, no. 1, pp. 11–19, 2023.
A. Subki, B. Imran, and S. Erniwati, “Pengembangan Sistem Informasi Geografis Berbasis Android Pada Wisata Daerah Lombok, Nusa Tenggara Barat,” Infotek J. Inform. dan Teknol., vol. 4, no. 2, pp. 259–269, 2021, doi: 10.29408/jit.v4i2.3667.
M. Asadullah et al., “Evaluation of machine learning techniques for hypertension risk prediction based on medical data in Bangladesh,” Indones. J. Electr. Eng. Comput. Sci., vol. 31, no. 3, pp. 1794–1802, 2023, doi: 10.11591/ijeecs.v31.i3.pp1794-1802.
Z. Mutaqin, B. Imran, and S. Rosida, “SISTEM INFORMASI PENJUALAN ONLINE (E-COMMERCE) BERBASIS WEB PADA TOKO MATAHARI PRAYA,” J. Comput. Technol., vol. 1, no. 2, pp. 29–36, 2023, doi: https://doi.org/10.69916/comtechno.v1i2.46.
Sahidi and Z. Mutaqin, “Sistem Informasi Pariwisata Desa Senaru Berbasis Website Menggunakan Metode RAD,” J. Comput. Technol., vol. 1, no. 1, pp. 1–5, 2023.
Z. Muahidin and B. Imran, “Klasifikasi Kondisi Biji Kopi Berbasis Deep Learning Menggunakan CNN dengan EfficientNetB0,” Explore, vol. 15, no. 2, 2025.
B. Imran, E. Wahyudi, S. Riadi, Z. Muahidin, S. Erniwati, and W. A. Wahyuni, “A Comparative Hybrid Approach for Python Bug Detection Using Syntactic Features, Random Forest, and Neural Network,” CommIT J., vol. 19, no. 2, pp. 141–150, 2025, doi: https://doi.org/10.21512/commit.v19i2.13183.
Downloads
Published
Scite Metrics
Altmetric
How to Cite
Issue
Section
License
Copyright (c) 2026 Dystian En Yusgiantoro, Ari Hidayatullah
This work is licensed under a Creative Commons Attribution 4.0 International License.
menuterbaru
