Penerapan Business Intelligence Terhadap Data Penjualan UMKM (Foodendez) Menggunakan Metode Algoritma Apriori Dalam Menentukan Segmentasi Pasar
DOI:
https://doi.org/10.30865/mib.v6i3.4338Keywords:
Apriori Algorithm, Business Intelligence, Foodendez, Market segmentation, MSMEAbstract
MSMEs in Indonesia are MSMEs with a business scale level of 98.7% are micro-enterprises and this MSME-scale assessment category was assessed or researched 10 years ago, the results are still the same as the previous assessment, due to the average MSMEs in Indonesia not having a way or the right innovation in developing its business, especially in terms of the products produced and other things, an example of MSMEs experiencing this is MSME Foodendez, which causes these MSMEs to not have significant sales progress. Therefore, to improve the quality and progress of the Foodendez MSME business, the current sales data is used to recapitulate and evaluate the Foodendez MSME market segmentation. By using the a priori algorithm, the sales data can be used to find out predictive information on consumer interest based on age, gender, and sales location criteria. The application of business intelligence uses an a priori algorithm so that it can help provide predictive information on consumer interest in a product and can clearly know its market segmentation by collecting data through product sales in the marketplace it can be seen which products are most interested in by consumers, then data on the amount followers, comments, and likes in every post on social media in order to determine engagement (promotional strategies through social media). In this research, testing is carried out based on the location of sales at Foodendez SMEs so as to produce market segmentation data. The conclusion from the temporary test results, the frequency of sales in the marketplace is the highest at 52%, then the lowest frequency of sales is 12% in sales through exhibition bazaars.
References
S. Sarfiah, H. Atmaja, dan D. Verawati, “UMKM Sebagai Pilar Membangun Ekonomi Bangsa,†J. REP (Riset Ekon. Pembangunan), vol. 4, no. 2, hal. 1–189, 2019, doi: 10.31002/rep.v4i2.1952.
D. Penjualan dan P. Pt, “Business intelligence,†vol. 5, no. 2, hal. 76–85, 2020.
H. Kusumo, E. Sediyono, dan M. Marwata, “Analisis Algoritma Apriori untuk Mendukung Strategi Promosi Perguruan Tinggi,†Walisongo J. Inf. Technol., vol. 1, no. 1, hal. 49, 2019, doi: 10.21580/wjit.2019.1.1.4000.
F. F. Adiwijaya dan A. Hadiana, “Realtime Business Intelligence Menggunakan Algoritma Apriori dengan Data Stream Mining (Studi Kasus: Penjadwalan PT. Citra Tiara Global),†J. Tata Kelola dan Kerangka Kerja Teknol. Inf., vol. 4, no. 2, hal. 62–67, 2018, doi: 10.34010/jtk3ti.v4i2.1987.
D. Astuti, “Penentuan Strategi Promosi Usaha Mikro Kecil Dan Menengah (UMKM) Menggunakan Metode CRISP-DM dengan Algoritma K-Means Clustering,†J. Informatics, Inf. Syst. Softw. Eng. Appl., vol. 1, no. 2, hal. 60–72, 2019, doi: 10.20895/inista.v1i2.71.
T. R. Ariani, K. D. Tania, dan D. R. Indah, “Penerapan Business Intelligence Pada Sistem Informasi Penjualan Barang PT. WINSA (STUDI KASUS DI PT. WINSA PALEMBANG),†J. Sist. Inf., hal. 103–110, 2016.
D. Nurmalasari, “Implementasi Business Intelligence Dashboard pada Data Pasien Puskesmas Kecamatan Rokan,†J. Komput. Terap., vol. 7, no. 2, hal. 174–183, 2021.
M. P. Tana, F. Marisa, dan I. D. Wijaya, “Penerapan Metode Data Mining Market Basket Analysis Terhadap Data Penjualan Produk Pada Toko Oase Menggunakan Algoritma Apriori,†J I M P - J. Inform. Merdeka Pasuruan, vol. 3, no. 2, hal. 17–22, 2018, doi: 10.37438/jimp.v3i2.167.
R. Fitriana, J. Saragih, dan N. Luthfiana, “Model business intelligence system design of quality products by using data mining in R Bakery Company,†IOP Conf. Ser. Mater. Sci. Eng., vol. 277, no. 1, 2017, doi: 10.1088/1757-899X/277/1/012005.
M. A. Firdaus, A. Putra, dan D. I. Rosa, “Analisis Business Intelligence pada Pengelolaan Data Alumni : Upaya Mendukung Monitoring Kualitas Alumni di Perguruan Tinggi ( Studi Kasus di Fakultas Ilmu Komputer Universitas Sriwijaya ),†J. Generic, vol. 8, no. 2, hal. 221–229, 2013.
M. Ahmad, “Penerapan Business Intelligence Untuk Menampilkan Keuntungan Pada data Superstore Dengan Menggunakna Metode OLAP,†J. ALGOR, vol. 1, hal. 48–56, 2020.
J. Ming, L. Zhang, J. Sun, dan Y. Zhang, “Analysis models of technical and economic data of mining enterprises based on big data analysis,†2018 3rd IEEE Int. Conf. Cloud Comput. Big Data Anal. ICCCBDA 2018, hal. 224–227, 2018, doi: 10.1109/ICCCBDA.2018.8386516.
S. Saefudin dan S. DN, “Penerapan Data Mining Dengan Metode Algoritma Apriori Untuk Menentukan Pola Pembelian Ikan,†JSiI (Jurnal Sist. Informasi), vol. 6, no. 2, hal. 36, 2019, doi: 10.30656/jsii.v6i2.1587.
A. Zikri, J. Adrian, A. Soniawan, R. Azim, R. Dinur, dan R. Akbar, “Implementasi Business Intelligence untuk Menganalisis Data Persalinan Anak di Klinik Ani Padang dengan Menggunakan Aplikasi Tableau Public,†J. Online Inform., vol. 2, no. 1, hal. 20, 2017, doi: 10.15575/join.v2i1.70.
D. Yuanita, “Peran key opinion leader dalam strategi public relations pada komunikasi krisis perusahaan,†PRofesi Humas J. Ilm. Ilmu Hub. Masy., vol. 6, no. 1, hal. 23, 2021, doi: 10.24198/prh.v6i1.29693.
A. Q. Syarli, Rosmawati Tamin, “Perancangan Business Intelligence System Pada Gudang Farmasi Dinas Kesehatan Kabupaten Mamasa,†JUTEKS (Jurnal Keteknikan dan Sains), vol. 1, no. 1, hal. 7–14, 2018.
A. F. Budiantara dan C. Budihartanti, “Implementasi Data Mining Dalam Manajemen Inventory Pada Pt . Mastersystem Infotama Menggunakan Metode Algoritma Apriori,†Prosisko, vol. 7, no. 1, hal. 26–31, 2020.
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