PENERAPAN DATA MINING PEMASARAN PRODUK MENGGUNAKAN METODE CLUSTERING
Abstract
This study aims to build a data mining application that is able to classify products marketed by companies to find out the products needed for the following month. This application groups non-hierarchical data which is designed to divide existing data into two or more groups so that the same data can be entered into other groups. In this study, the data used is data from PT Cipta Niaga Semesta Mayora Group and the method used is clustering. Data mining is computer-based data processing to gain knowledge. By using data mining, processing sales data at PT Cipta Niaga Semesta Mayora Group becomes easier and gains useful knowledge to take steps to face competition. For this reason, the company's management foresight is needed in choosing technology to help work so that the costs incurred are proportional to the company's opinion. The development of this framework is completed through several stages starting with the first data collection, followed by the second stage of application design, the third stage of the four stages of program development and program implementation. Using data mining applications can help PT Cipta Niaga Semesta categorize the products it sells so that the company can predict the product inventory needed for the following month. So with the new information the company can find out what products customers want.
References
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[2] P. Adi, D. Prasetya, A. Setiawan, N. Nachrowie, and R. Arifuddin, “Design Of Tsunami Detector Based Sort Message Service Using Arduino and SIM900A to GSM/GPRS Module,” Proc. Proc. 2nd Int. Conf. Adv. Sci. Innov. ICASI 2019, 18 July, Banda Aceh, Indones., 2019, doi: 10.4108/eai.18-7-2019.2288588.
[3] P. Dani Prasetyo Adi and A. Kitagawa, “A performance of radio frequency and signal strength of LoRa with BME280 sensor,” TELKOMNIKA (Telecommunication Comput. Electron. Control., vol. 18, no. 2, p. 649, Apr. 2020, doi: 10.12928/telkomnika.v18i2.14843.
[4] P. D. P. Adi et al., “A Performance Evaluation of ZigBee Mesh Communication on the Internet of Things (IoT),” in 2021 3rd East Indonesia Conference on Computer and Information Technology (EIConCIT), Apr. 2021, pp. 7–13. doi: 10.1109/EIConCIT50028.2021.9431875.
[5] P. D. P. Adi and A. Kitagawa, “Quality of Service and power consumption optimization on the IEEE 802.15.4 pulse sensor node based on Internet of Things,” Int. J. Adv. Comput. Sci. Appl., 2019, [Online]. Available: http://www.scopus.com/inward/record.url?eid=2-s2.0-85066760495&partnerID=MN8TOARS
[6] V. M. M. Siregar and H. Sugara, Implementation of artificial neural network to assesment the lecturer ‘ s performance. 2018. doi: 10.1088/1757-899X/420/1/012112.
[7] P. D. P. Adi et al., “A Study of Programmable System on Chip (PSoC) Technology for Engineering Education,” J. Phys. Conf. Ser., vol. 1899, no. 1, p. 012163, May 2021, doi: 10.1088/1742-6596/1899/1/012163.
[8] I. Wahyudi, S. Bahri, and P. Handayani, “Aplikasi Pembelajaran Pengenalan Budaya Indonesia,” vol. V, no. 1, pp. 135–138, 2019, doi: 10.31294/jtk.v4i2.
[9] S. Sirait et al., “Selection of the Best Administrative Staff Using Elimination Et Choix Traduisant La Realite (ELECTRE) Method,” J. Phys. Conf. Ser., vol. 1933, no. 1, p. 012068, Jun. 2021, doi: 10.1088/1742-6596/1933/1/012068.
[10] J. Simatupang and S. Sianturi, “PERANCANGAN SISTEM INFORMASI PEMESANAN TIKET BUS PADA PO. HANDOYO BERBASIS ONLINE,” J. Intra Tech, vol. 3, no. 2, pp. 11–25, 2019.
[11] J. Simatupang and E. S. Hendarti, “Implementasi Sistem Informasi Job Portal Pada BPJS Ketenagakerjaan Berbasis Web,” J. Intra Tech, vol. 5, no. 2, pp. 48–59, 2021.
[12] W. Purba, S. Tamba, and J. Saragih, “The effect of mining data k-means clustering toward students profile model drop out potential,” J. Phys. Conf. Ser., vol. 1007, no. 1, p. 12049, 2018, [Online]. Available: http://stacks.iop.org/1742-6596/1007/i=1/a=012049
[13] V. Sihombing and G. J. Yanris, “PENERAPAN APLIKASI DALAM MENGOLAH ASET DESA (STUDI KASUS: KEPENGHULUAN SRI KAYANGAN),” J. Mantik Penusa, vol. 4, no. 1, pp. 12–15, 2020.
[14] S. Sumaizar, K. Sinaga, E. D. Siringo-ringo, and V. M. M. Siregar, “Determining Goods Delivery Priority for Transportation Service Companies Using SAW Method,” J. Comput. Networks, Archit. High Perform. Comput., vol. 3, no. 2, pp. 256–262, Nov. 2021, doi: 10.47709/cnahpc.v3i2.1154.
[15] S. P. Tamba, A. W. Tan, Y. Gunawan, and ..., “Penerapan Data Mining Untuk Pembuatan Paket Promosi Penjualan Menggunakan Kombinasi Fp-Tree Dan Tid-List,” … (Teknik Inf. dan …, vol. 4, 2021.
[16] V. Sihombing, V. M. M. Siregar, W. S. Tampubolon, M. Jannah, Risdalina, and A. Hakim, “Implementation of simple additive weighting algorithm in decision support system,” IOP Conf. Ser. Mater. Sci. Eng., vol. 1088, no. 1, p. 012014, Feb. 2021, doi: 10.1088/1757-899X/1088/1/012014.
[17] V. Sihombing et al., “Additive Ratio Assessment (ARAS) Method for Selecting English Course Branch Locations,” J. Phys. Conf. Ser., vol. 1933, no. 1, p. 012070, Jun. 2021, doi: 10.1088/1742-6596/1933/1/012070.
[18] Edric and S. P. Tamba, “Prediksi Penyakit Gagal Jantung Dengan Menggunakan Random Forest,” J. Sist. Inf. dan Ilmu Komput. Prima(JUSIKOM PRIMA), vol. 5, no. 2, pp. 176–181, 2022, doi: 10.34012/jurnalsisteminformasidanilmukomputer.v5i2.2445.
[19] Fricles Ariwisanto Sianturi, “Analisa metode teorema bayes dalam mendiagnosa keguguran pada ibu hamil berdasarkan jenis makanan,” Tek. Inf. dan Komput., vol. 2, no. 1, pp. 87–92, 2019, [Online]. Available: http://jurnal.murnisadar.ac.id/index.php/Tekinkom/article/view/78
[20] . F., F. T. Kesuma, and S. P. Tamba, “Penerapan Data Mining Untuk Menentukan Penjualan Sparepart Toyota Dengan Metode K-Means Clustering,” J. Sist. Inf. dan Ilmu Komput. Prima(JUSIKOM PRIMA), vol. 2, no. 2, pp. 67–72, 2020, doi: 10.34012/jusikom.v2i2.376.
[21] S. Aprilia, T. Informatika, U. Nahdlatul, U. Sumatera, F. Chaining, and Z. Plastik, “Aplikasi Sistem Pakar Mendeteksi Zat Berbahaya Pada Plastik Menggunakan Metode Backward Chaining,” pp. 19–28.
[22] I. T, “Penerapan Data Mining Dalam Dunia Bisnis Menggunakan Metode Clustering.,” J. Intsitution Sharia Financ., vol. 2, pp. 40–53, 2019.
[23] H. Annur, “Penerapan Data Mining Menentukan Strategi Penjualan Variasi Mobil Menggunakan Metode K-Means Clustering,” J. Inform. Upgris, vol. 5, no. 1, 2019, doi: 10.26877/jiu.v5i1.3091.
[24] S. P. Tamba, M. D. Batubara, W. Purba, M. Sihombing, V. M. Mulia Siregar, and J. Banjarnahor, “Book data grouping in libraries using the k-means clustering method,” J. Phys. Conf. Ser., vol. 1230, p. 012074, Jul. 2019, doi: 10.1088/1742-6596/1230/1/012074.
[25] E. D. Sikumbang, “Penerapan Data Mining Penjualan Sepatu Menggunakan Metode Algoritma Apriori,” J. Tek. Komput. AMIK BSI, vol. Vol 4, No., no. September, pp. 1–4, 2018.
[26] D. Riana et al., “Identifikasi Citra Pap Smear RepoMedUNM dengan Menggunakan K-Means Clustering dan GLCM,” J. RESTI (Rekayasa Sist. dan Teknol. Informasi), vol. 6, no. 1, pp. 1–8, 2022, doi: 10.29207/resti.v6i1.3495.
[27] D. W. T. Putra and R. Andriani, “Unified Modelling Language (UML) dalam Perancangan Sistem Informasi Permohonan Pembayaran Restitusi SPPD,” J. TeknoIf, vol. 7, no. 1, p. 32, 2019, doi: 10.21063/jtif.2019.v7.1.32-39.
Published
2022-06-30
How to Cite
MELLADIA, Melladia; PUTRA, Dian Eka; MUHELNI, Leila.
PENERAPAN DATA MINING PEMASARAN PRODUK MENGGUNAKAN METODE CLUSTERING.
Jurnal Teknik Informasi dan Komputer (Tekinkom), [S.l.], v. 5, n. 1, p. 160-167, june 2022.
ISSN 2621-3079.
Available at: <https://jurnal.murnisadar.ac.id/index.php/Tekinkom/article/view/458>. Date accessed: 08 july 2025.
doi: https://doi.org/10.37600/tekinkom.v5i1.458.
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Articles
