Prediction Analysis of Retail Store Sales Level using Neural Network Algorithm Method based on Customer Segments
Analisis Prediksi Tingkat Penjualan Toko Ritel menggunakan Metode Algoritma Neural Network berbasis Segmen Pelanggan
DOI:
https://doi.org/10.21070/ups.4988Keywords:
Prediction, Retail Store Sales Level, Marketing Mix 4P, Neural Network, RapidMinerAbstract
Marketing activities have an important role in business and marketing mix is one of the strategies used to achive company goals. This study uses the Neural Network because it is commonly flexible in processing large amounts of data dan the use of RMSE must be used to determine the accuracy of the model used. The results state that the visual results in each segment show that between the actual value and the predicted value, the deviation is pretty close and can be said to be close to the value of the actual data. A 4P marketing mix strategy can be applied so that the company has the opportunity to increase the number of sales. The research concluded that the results of the prediction data set, visual prediction results, and RMSE using the Neural Network method can be used effectively and accurately to forecast sales and help company owners and management.
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References
M. I. Panjaitan, “Forecasting of Sales of Computer Equipment using Exponential Smooting Method,” J. Infokum, vol. 7, no. 2, pp. 53–57, 2019, [Online]. Available: http://infor.seaninstitute.org/index.php/infokum/index
S. S. Parameshwari, D. Herwanto, and R. Fitriani, “Analysis of Marketing Strategy in Increasing Sales Volume in the Onion Cracker Industry (Case Study of UMKM XYZ),” Appl. Ind. Eng., vol. 06, no. 1, pp. 71–75, 2023, doi: https://doi.org/10.36456/tibuana.6.1.6054.71-75.
R. Herman and A. Suyanto, “Analisis Strategi Pemasaran Pada Toko Future Computer,” eProceedings Telkom Univ., 2021, [Online]. Available: https://openlibrarypublications.telkomuniversity.ac.id/index.php/management/article/view/14929
W. Amalia, A. S. Rusdianto, M. Choiron, N. S. Mahardika, and D. I. Lestari, “Marketing Strategy Planning of Kahyangan Coffee Using Marketing Mix in Coffee Shops,” J. Sos. Ekon. Pertan., vol. 16, no. 3, pp. 287–300, 2023, doi: 10.19184/jsep.v16i3.43030.
N. Hermanto, A. Syafarudin, and A. Saluy, “The Influence of Marketing Mix, Costumer Value, and Customer Satisfaction on the Purchase Intention of Granite and Marble Natural Stone at PT. Intinusa Selareksa, Tbk, Jakarta,” MICOSS Mercu Buana Int. Conf. Soc. Sci., 2021, doi: 10.4108/eai.28-9-2020.2307364.
G. M. Oki Pranajaya, I. Suroso, and B. Irawan, “Pengaruh Bauran Pemasaran dalam Bisnis Konveksi Clothing Karikatur Bali Terhadap Kepuasan dan Loyalitas Konsumen Pada PT. Eka Jaya Makmur Bali,” e-Journal Ekon. Bisnis dan Akunt., vol. 6, no. 1, p. 1, 2019, doi: 10.19184/ejeba.v6i1.11065.
B. Kanetro et al., “How to Shape Purchase Decision? The Influence of Marketing Mix toward Purchase Decision on Food Product,” Int. J. Multidiscip. Res. Anal., vol. 06, no. 01, pp. 296–302, 2023, doi: 10.47191/ijmra/v6-i1-37.
V. Martah, D. U. Dewi, and D. Arif, “Digital Marketing And Price On Iswa Computer Sales Volume,” IQTISHADequity J. Manag., vol. 5, no. 1, pp. 1–5, 2023, doi: https://doi.org/10.51804/iej.v5i1.11885.
I. A. U. Dewi, I. K. N. A. Jaya, and K. O. Sanjaya, “Forecasting Number of COVID-19 in Bali Province Using Neural Network Algorithm,” J. Ilm. Merpati (Menara Penelit. Akad. Teknol. Informasi), vol. 9, no. 1, p. 72, 2021, doi: 10.24843/jim.2021.v09.i01.p07.
Yulyardo and S. M. Isa, “Predictive Business Intelligence: Consumer Goods Sales Forecasting Using Artificial Neural Network,” Int. J. Mech. Eng. Technol., vol. 10, no. 5, pp. 283–293, 2019, [Online]. Available: http://www.iaeme.com/ijmet/issues.asp?JType=IJMET&VType=10&IType=5http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=10&IType=5
K. Ofoegbu and A. Sajad Esmaeily, “A Comparative Analysis of Four Machine Learning Algorithms to Predict Product Sales for a Retail Store,” Dublin Bus. Sch., pp. 44–45, 2021.
B. D. Garang, “Penerapan Data Mining untuk Prediksi Penjualan Smarthphone Paling Laris menggunakan Metode K-Nearest Neighbor (Studi Kasus : Pusat Ponsel & Laptop),” Sekolah Tinggi Manajemen Informatika dan Komputer (STMIK) Palangkaraya, 2022.
R. Mayang Sari and Y. Apridonal M, “Data Mining Implementation for Printer Sales Prediction Using Naive Bayes Method,” vol. 4509, pp. 215–220, 2020.
Ridwan, H. Lubis, and P. Kustanto, “Implementasi Algoritma Neural Network dalam Memprediksi Tingkat Kelulusan Mahasiswa,” J. Media Inform. Budidarma, vol. 4, no. 2, p. 286, 2020, doi: 10.30865/mib.v4i2.2035.
H. M. Nawawi, J. J. Purnama, and A. B. Hikmah, “Komparasi Algoritma Neural Network Dan Naïve Bayes Untuk Memprediksi Penyakit Jantung,” J. Pilar Nusa Mandiri, vol. 15, no. 2, pp. 189–194, 2019, doi: 10.33480/pilar.v15i2.669.
D. Marfuah, N. K. Ulya, D. P. D. Kusudaryati, A. S. Wardana, and E. Nugroho, “Current Trends in Intelligent Control Neural Networks for Thermal Processing (Foods): Systematic Literature Review,” J. Robot. Control, vol. 3, no. 4, pp. 519–527, 2022, doi: 10.18196/jrc.v3i4.15232.
A. I. Lubis, D. Aulia, and S. S. Nasution, “The Influence of Hospital Marketing Mix on Inpatient Loyalty in Sarah Medan General Hospital,” Eur. J. Mol. Clin. Med. , vol. 8, no. 4, pp. 187–192, 2021.
Suriadi, Fadlina, and U. Rahman, “The Effect of Service Marketing Mix on Customer Satisfaction at PT. Bank Danamon Indonesia, Tbk Mamuju Unit Sub-Branch,” Jeinsa J. Ekon. Ichsan Sidenreng Rappang, vol. 1, no. 1, pp. 163–174, 2022, doi: https://doi.org/10.61912/jeinsa.v2i1.21.
E. Handayani, H. Justiana Astuti, A. Darmawan, and B. C. Pratama, “Emotional branding moderation on marketing mix selection of college in the Covid-19 pandemic period,” Int. J. Res. Bus. Soc. Sci., vol. 10, no. 4, pp. 375–382, 2021, [Online]. Available: https://www.e-journal.unair.ac.id/JPERPUS/article/view/23610/13088
N. Anika and T. Kato, “Modeling River Flow using Artificial Neural Networks: A Case Study on Sumani Watershed,” J. Sci. Technol., vol. 27, pp. 179–188, 2019.
L. Pujiastuti, M. Wahyudi, and Solikhun, “Analysis of Perceptron Quantum Artificial Neural Networks to Classify the Feasibility of Prospective Debtors,” J. Phys. Conf. Ser., vol. 1641, no. 1, 2020, doi: 10.1088/1742-6596/1641/1/012091.
B. Aprilia, Marzuki, and I. Taufiq, “Performance of Backpropagation Artificial Neural Network to Predict El Nino Southern Oscillation Using Several Indexes as Onset Indicators,” J. Phys. Conf. Ser., vol. 1876, no. 1, 2021, doi: 10.1088/1742-6596/1876/1/012004.
K. Muludi, M. S. Akbar, D. A. Shofiana, and A. Syarif, “Sentiment Analysis Of Energy Independence Tweets Using Simple Recurrent Neural Network,” IJCCS (Indonesian J. Comput. Cybern. Syst., vol. 15, no. 4, p. 339, 2021, doi: 10.22146/ijccs.66016.
A. M. Siregar and H. H. H, “Implementasi Algoritma Neural Network untuk Mendukung Keputusan di Desa Tamanmekar,” Petir, vol. 13, no. 1, pp. 21–32, 2020, doi: 10.33322/petir.v13i1.768.
T. Waluyo, A. Hermawan, and A. P. Wibowo, “Prediksi Penjualan Sepeda Motor HONDA menggunakan Jaringan Syaraf Tiruan,” Joism J. Inf. Syst. Manag., vol. 1, no. 1, pp. 31–35, 2019.
E. D. Madyatmadja, S. I. Jordan, and J. F. Andry, “Big data analysis using rapidminer studio to predict suicide rate in several countries,” ICIC Express Lett. Part B Appl., vol. 12, no. 8, pp. 757–764, 2021, doi: 10.24507/icicelb.12.08.757.
S. Marzukhi, N. Awang, S. N. Alsagoff, and H. Mohamed, “RapidMiner and Machine Learning Techniques for Classifying Aircraft Data,” J. Phys. Conf. Ser., vol. 1997, no. 1, 2021, doi: 10.1088/1742-6596/1997/1/012012.
I. M. Y. A. Dala, I. K. G. D. Putra, and P. W. Buana, “Forecasting Cases of Dengue Hemorrhagic Fever Using the Backpropagation, Gaussians and Support-Vector Machine Methods,” J. RESTI (Rekayasa Sist. dan Teknol. Informasi), vol. 5, no. 2, pp. 335–341, 2021, doi: 10.29207/resti.v5i2.2936.
S. Kurniawan, W. Gata, D. A. Puspitawati, I. K. S. Parthama, H. Setiawan, and S. Hartini, “Text Mining Pre-Processing Using Gata Framework and RapidMiner for Indonesian Sentiment Analysis,” IOP Conf. Ser. Mater. Sci. Eng., vol. 835, no. 1, 2020, doi: 10.1088/1757-899X/835/1/012057.
D. Wijaya and L. A. Abdillah, “Sentiment Analysis of Omicron COVID-19 Variant using Naïve Bayes Classifier and RapidMiner,” J. Data Sci., vol. 8, pp. 1–7, 2023, [Online]. Available: http://eprints.intimal.edu.my/1783/1/jods2023_08.pdf
H. Harini, D. P. Wahyuningtyas, Sutrisno, M. I. Wanof, and A. M. A. Ausat, “Marketing Strategy for Early Childhood Education (ECE) Schools in the Digital Age,” J. Obs. J. Pendidik. Anak Usia Dini, vol. 7, no. 3, pp. 2742–2758, 2023, doi: 10.31004/obsesi.v7i3.4454.
A. L. Hananto, S. Sulaiman, S. Widiyanto, and A. Y. Rahman, “Evaluation comparison of wave amount measurement results in brass-plated tire steel cord using RMSE and cosine similarity,” Indones. J. Electr. Eng. Comput. Sci., vol. 22, no. 1, p. 207, 2021, doi: 10.11591/ijeecs.v22.i1.pp207-214.
F. J. Harianto and F. F. Abdulloh, “Linear Regression Algorithm Analysis to Predict the Effect of Inflation on the Indonesian Economy.,” Indonesian Journal of Computer Science, vol. 12, no. 4. 2023. doi: 10.33022/ijcs.v12i4.3224.
N. Chukwudike, C. B. Ugoala, O. Maxwell, U.-I. Okezie, O. Bright, and U. Henry, “Forecasting Monthly Prices of Gold Using Artificial Neural Network,” J. Stat. Econom. Methods, vol. 9, no. 3, pp. 19–28, 2020, [Online]. Available: http://www.scienpress.com/Upload/JSEM/Vol 9_3_2.pdf
V. D. Purnomo, “The Effect of Housing Marketing Mix on Purchase Decisions for Type 36 Houses in Jenar, Purworejo Regency,” Asian J. Manag. Anal., vol. 2, no. 1, pp. 61–82, 2023, doi: 10.55927/ajma.v2i1.2414.
S. Marchelita, “Analisis Strategi Marketing Mix Menggunakan Konsep 4P (Product, Price, Place, Promotion) Pada Percetakan Anugerah Jaya,” Institut Agama Islam Negeri Batusangkar, 2021.
A. J. M. Intan, “The Effect of Marketing Mix (Product, Price, Place and Process) on Students’ Desire to Recommend Lectures in Tourism Academy of NHI Bandung,” Budapest Int. Res. Critics Inst. Humanit. Soc. Sci., vol. 3, no. 4, pp. 3933–3948, 2020, doi: 10.33258/birci.v3i4.1460.
A. Nurman and E. Harapan, “Marketing Mix Implementation on Products, Prices, Places, Promotions In Marketing of Education Services,” J. Pendidik. Tambusai, vol. 5, no. 2, pp. 5211–5220, 2021.
F. Y. Ernawati, S. Rochmah, and H. Silvia, “Pengaruh Marketing Mix terhadap Keputusan Pembelian pada Prima Freshmart Cabang Pekalongan,” Pros. Semin. Nas. Call Pap. STIE AAS, pp. 358–368, 2021.
F. Anjelika and T. M. Sinaga, “Influence of Marketing MIX 4P (Product, Price, Place, Promotion) on Purchase Decision at PT. Alfa Scorpii Setia Budi Branch Medan,” J. Mantik, vol. 5, no. 4, pp. 2239–2246, 2022.
H. Malau, “the 4P’S Marketing Mix Variables: an Assessment of Concept, Applicability and Impact on Organizational Goal From West Java’s Business Organizations,” J. Terap. Manaj. dan bisnis, vol. 3, no. 1, pp. 57–74, 2020.
A. F. Putra and M. A. Lubis, “Effect of Promotional Mix And Price On Consumer Subscription Decisions Mediated By Trust In Indihome Consumers In Medan" (Emperis Study On PT. Telkom Witel Medan),” J. Manag. Anal. Solut., vol. 1, no. 2, pp. 58–71, 2021, doi: 10.32734/jomas.v1i2.6286.
N. Rosdiana, F. A. Lubis, and R. D. Harahap, “Analisis Strategi Marketing Mix pada Toko Gopek Fashion,” J. Masharif al-Syariah J. Ekon. dan Perbank. Syariah, vol. 8, no. 30, pp. 322–336, 2023.
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