Penerapan Metode Weighted Product Berbasis Visualisasi Graph Database dalam Merekomendasikan Parfum Isi Ulang
DOI:
https://doi.org/10.30865/json.v4i4.6181Keywords:
Weighted Product, Graph Database, PerfumeAbstract
Perfume is useful for increasing self-confidence, creating satisfaction, eliminating bad odors, and making self-assessment more attractive. Refill perfumes are made from certain perfume seeds dissolved in a suitable solvent. Perfume has many types and strengths of aroma, but there are obstacles when people want to choose the desired perfume scent. This problem becomes research material because it is expected that this problem can be solved. To determine perfume recommendations, it is calculated using the Weighted Product method and visualized using a graph database. In the Neo4j Graph Database visualization, the perfume category and perfume name are used as nodes and the ranking results are used as edges. From the ranking results using the Weighted Product method, 21 perfumes for each category are entered into the Graph Database visualization and a total of 63 perfumes will appear in the perfume recommendation system.Refill perfume is a perfume made from certain perfume seeds dissolved in the appropriate solvent.References
G. Begum et al., “World Journal of Pharmaceutical Sciences A Review on Microencapsulation,†Rev. Microencapsulation. World J Pharm Sci, vol. 6, no. 4, hal. 25–36, 2018, [Daring]. Tersedia pada: http://www.wjpsonline.org/
L. Egisnawati, “Laporan Tugas Akhir Lisna Egisnawati Universitas Bhakti Kencana FakultasFarmasi Program Strata IFarmasi Bandung LEMBAR PENGESAHAN Laporan Tugas Akhir Lisna Egisnawati,†2020.
A. Kurniawati, “Pengaruh Jenis Pelarut Pada Proses Ekstraksi Bunga Mawar Dengan Metode Maserasi Sebagai Aroma Parfum Info Articles,†J. Creat. Student, vol. 2, no. 2, hal. 74–83, 2019, [Daring]. Tersedia pada: http://journal.unnes.ac.id/nju/index.php/jcs
N. Allysa, N. Maharani, dan S. Estri, “Pengaruh Kualitas Produk terhadap Keputusan Pembelian pada Ozon Parfum Fragrance,†Pros. Manaj., hal. 775–779, 2018.
Rassel, M. K. A. Rozaq, dan M. F. Apriyanto, “Representasi Aroma Parfum Dengan Pendekatan Metafora Dalam Fotografi Produk,†SpectÄ J. Photogr. Arts, Media, vol. 2, no. 2, hal. 123–134, 2018, doi: 10.24821/specta.v2i2.2552.
N. Marpaung, M. Handayani, dan R. Yesputra, “Sistem Pendukung Keputusan Pemilihan Dosen Terbaik Dengan Metode Weighted Product (WP) Pada STMIK Royal,†Semin. Nas. R. 2018, vol. 9986, no. September, hal. 267–270, 2018.
Z. Alamsyah dan D. Gustian, “Sistem Pendukung Keputusan Menggunakan Metode Weighted Product Dan Simple Additive Weighting Terhadap Penerimaan Guru,†J. IKRA-ITH Inform., vol. 3, no. 1, hal. 129–137, 2019, [Daring]. Tersedia pada: http://journals.upi-yai.ac.id/index.php/ikraith-informatika/article/view/310
C. Rizal, S. R. Siregar, S. Supiyandi, S. Armasari, dan A. Karim, “Penerapan Metode Weighted Product (WP) Dalam Keputusan Rekomendasi Pemilihan Manager Penjualan,†Build. Informatics, Technol. Sci., vol. 3, no. 3, hal. 312–316, 2021, doi: 10.47065/bits.v3i3.1094.
M. S. Arrosyid, “Penerapan Graph Database Pada Jalur Sanad Perawi Hadits Menggunakan Neo4J,†hal. 1–55, 2018.
M. Macak, M. Stovcik, dan B. Buhnova, “The suitability of graph databases for big data analysis: A benchmark,†IoTBDS 2020 - Proc. 5th Int. Conf. Internet Things, Big Data Secur., no. IoTBDS, hal. 213–220, 2020, doi: 10.5220/0009350902130220.
F. Gong, Y. Ma, W. Gong, X. Li, C. Li, dan X. Yuan, “Neo4j graph database realizes efficient storage performance of oilfield ontology,†PLoS One, vol. 13, no. 11, hal. 1–16, 2018, doi: 10.1371/journal.pone.0207595.
J. Monteiro, F. Sa, dan J. Bernardino, “Experimental Evaluation of Graph Databases: JanusGraph, Nebula Graph, Neo4j, and TigerGraph,†2023.
Q. A’yuni, “Sistem pendukung keputusan pemilihan parfum perempuan dengan analytical hierrachy process,†vol. 2, no. 2, 2020.
H. Pohan dan D. E. Sinaga, “Penerapan Metode Moora Dalam Menentukan Parfume Terbaik Berdasarkan Kepribadian,†KESATRIA J. Penerapan Sist. Inf. (Komputer Manajemen), vol. 1, no. 2, hal. 59–63, 2020, doi: 10.30645/kesatria.v1i2.21.
M. Tbk, I. Syarief, dan P. Mauliana, “APLIKASI PEMILIHAN KUALITAS PARFUM TERBAIK MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING ( SAW ) ( STUDI PADA PT . PRISKILA,†vol. 2, no. 1, hal. 113–120, 2021.
E. dwi sri mulyani, C. rahmat hidayat, dan G. safinaz julyani, “Perbandingan Sistem Pendukung Keputusan Menggunakan Metode SAW Dengan WP Dalam Pemberian Pinjaman,†CogITo Smart J., vol. 5, no. 2, hal. 239–251, 2019, doi: 10.31154/cogito.v5i2.151.239-251.
m. syauq. hanif Ardani, “IMPLEMENTASI GRAPH DATABASE UNTUK MENENTUKAN RUTE PERJALANAN TRANSPORTASI UMUM,†2019.
P. Nikam, S. Bhoite, dan A. Shenoy, “Neo4j Graph Database Implementation for LinkedIn,†Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol., no. February 2022, hal. 339–342, 2020, doi: 10.32628/cseit206665.
I. A. Fitri, “Sistem Pendukung Keputusan Penentuan Guru Terbaik Menggunakan Metode Weighted Product (studi kasus: SDS Muhammadiyah Duri),†2021.
C. Fan, M. Chen, X. Wang, J. Wang, dan B. Huang, “A Review on Data Preprocessing Techniques Toward Efficient and Reliable Knowledge Discovery From Building Operational Data,†Front. Energy Res., vol. 9, no. March, hal. 1–17, 2021, doi: 10.3389/fenrg.2021.652801.
