Application of the Naïve Bayes Algorithm in Predicting Sales Prices for Snacks
DOI:
https://doi.org/10.55123/jomlai.v2i2.2444Keywords:
Naïve Bayes, Predictions, Price, Sale, SnackAbstract
This study aims to apply the Naïve Bayes Algorithm in predicting the selling price of snacks at Toko Timbul II. The data used in this study were obtained from January to December 2018-2021, covering various variables relevant to snack sales. The data collected is divided into two parts, namely Data Training and Data Testing. The Training Data consists of 20 alternatives, which are used to train the prediction model of the Naïve Bayes Algorithm. While Data Testing consists of 16 alternatives, which are used to test the extent of the model's ability to predict the selling price of snacks. Testing was carried out using the Rapid Miner application. The test results show that the implemented model achieves an accuracy rate of 100% in predicting the selling price of snacks. These results indicate that the Naïve Bayes Algorithm has great potential in predicting the selling price of snacks at Timbul II Stores. These findings can provide valuable insights for store managers and snack food industry stakeholders, as well as encourage the use of predictive analytical methods in similar contexts. It is hoped that the results of this study can contribute to optimizing sales strategies and making more informed decisions in the future.
References
M. I. T. B. N. Sumadi, R. Putra, and A. Firmansyah, “Peran Perkembangan Teknologi Pada Profesi Akuntan dalam Menghadapi Industri 4.0 dan Society 5.0,” Journal of Law, Administration, and Social Science, vol. 2, no. 1, pp. 56–68, 2022, doi: 10.54957/jolas.v2i1.162.
S. Maesaroh, R. R. Lubis, L. N. Husna, R. Widyaningsih, and R. Susilawati, “Efektivitas Implementasi Manajemen Business Intelligence pada Industri 4.0,” ADI Bisnis Digital Interdisiplin Jurnal, vol. 3, no. 2, pp. 1–8, 2022, doi: 10.34306/abdi.v3i2.764.
R. Edi Santoso, A. G. Prawiyogi, U. Rahardja, F. P. Oganda, and N. Khofifah, “Penggunaan dan Manfaat Big Data dalam Konten Digital,” ADI Bisnis Digital Interdisiplin Jurnal, vol. 3, no. 2, pp. 88–91, 2022, doi: 10.34306/abdi.v3i2.836.
H. Purba and Irwansyah, “User Generated Content dan Pemanfaatan Media Sosial Dalam Perkembangan Industri Pariwisata: Literature Review,” Professional: Jurnal Komunikasi dan Administrasi Publik, vol. 9, no. 2, pp. 229–238, 2022.
A. Wilandari and Y. A. Permadi, “Evaluasi Strategi Marketing Bisnis Ritel Skala Kecil Tradisional Kota Purwokerto Di Masa Pandemi Covid-19,” Jurnal Administrasi Bisnis, vol. 1, no. 1, pp. 1–8, 2021, doi: 10.31294/jab.v1i1.296.
B. A. Intansari, “Pengaruh merchandising sensorik dalam neuromarketing terhadap keputusan pembelian pelanggan di toko kelontong modern,” Journal of Environment and Management, vol. 3, no. 2, pp. 125–134, 2022, doi: 10.37304/jem.v3i2.5504.
S. S. Mukrimaa et al., “Analisis Dampak Toko Modern Terhadap Keberadaan Usaha Mikro, Kecil, Menengah Di Kota Padangsidimpuan,” Jurnal AT-TAWASSUTH, vol. 4, no. 1, pp. 208–230, 2019.
Renggo Ais Aprilian, Putri Citra Devi, and Muhammad Yasin, “Menganalisis Anggaran Untuk Penerimaan Pada Industri Surabaya,” SAMMAJIVA : Jurnal Penelitian Bisnis dan Manajemen, vol. 1, no. 2, pp. 265–277, 2023, doi: 10.47861/sammajiva.v1i2.258.
I. W. S. BatuBara and A. I. L. Nasution, “Strategi Pengembangan dalam Pemberdayaan Masyarakat Pesisir Tanjung Leidong Melalui Pengelolahan Udang Menjadi Kerupuk Udang,” Jurnal Informatika Ekonomi Bisnis, vol. 5, no. 2, pp. 537–542, 2023, doi: 10.37034/infeb.v5i2.281.
R. Watrianthos, W. A. Ritonga, A. Rengganis, A. Wanto, and M. Isa Indrawan, “Implementation of PROMETHEE-GAIA Method for Lecturer Performance Evaluation,” Journal of Physics: Conference Series, vol. 1933, no. 1, p. 012067, 2021, doi: 10.1088/1742-6596/1933/1/012067.
T. Imandasari, M. G. Sadewo, A. P. Windarto, A. Wanto, H. O. Lingga Wijaya, and R. Kurniawan, “Analysis of the Selection Factor of Online Transportation in the VIKOR Method in Pematangsiantar City,” Journal of Physics: Conference Series, vol. 1255, no. 1, p. 012008, Aug. 2019, doi: 10.1088/1742-6596/1255/1/012008.
M. Widyasuti, A. Wanto, D. Hartama, and E. Purwanto, “Rekomendasi Penjualan Aksesoris Handphone Menggunakan Metode Analitycal Hierarchy Process (AHP),” Konferensi Nasional Teknologi Informasi dan Komputer (KOMIK), vol. I, no. 1, pp. 27–32, 2017.
P. Alkhairi, L. P. Purba, A. Eryzha, A. P. Windarto, and A. Wanto, “The Analysis of the ELECTREE II Algorithm in Determining the Doubts of the Community Doing Business Online,” in Journal of Physics: Conference Series, Institute of Physics Publishing, Sep. 2019, p. 012010. doi: 10.1088/1742-6596/1255/1/012010.
S. R. Ningsih, R. Wulansari, D. Hartama, A. P. Windarto, and A. Wanto, “Analysis of PROMETHEE II Method on Selection of Lecturer Community Service Grant Proposals,” Journal of Physics: Conference Series, vol. 1255, no. 012004, pp. 1–7, 2019, doi: 10.1088/1742-6596/1255/1/012004.
N. Arminarahmah, A. D. GS, G. W. Bhawika, M. P. Dewi, and A. Wanto, “Mapping the Spread of Covid-19 in Asia Using Data Mining X-Means Algorithms,” IOP Conference Series: Materials Science and Engineering, vol. 1071, no. 1, p. 012018, 2021, doi: 10.1088/1757-899x/1071/1/012018.
M. A. Hanafiah, A. Wanto, and P. B. Indonesia, “Implementation of Data Mining Algorithms for Grouping Poverty Lines by District/City in North Sumatra,” IJISTECH (International Journal of Information System and Technology), vol. 3, no. 36, pp. 315–322, 2020.
F. S. Napitupulu, I. S. Damanik, I. S. Saragih, and A. Wanto, “Algoritma K-Means untuk Pengelompokkan Dokumen Akta Kelahiran pada Tiap Kecamatan di Kabupaten Simalungun,” Building of Informatics, Technology and Science (BITS) Volume, vol. 2, no. 1, pp. 55–63, 2020.
A. Wanto et al., “Epoch Analysis and Accuracy 3 ANN Algorithm using Consumer Price Index Data in Indonesia,” in Proceedings of the 3rd International Conference of Computer, Environment, Agriculture, Social Science, Health Science, Engineering and Technology (ICEST), 2021, pp. 35–41. doi: 10.5220/0010037400350041.
A. Wanto et al., “Levenberg-Marquardt Algorithm Combined with Bipolar Sigmoid Function to Measure Open Unemployment Rate in Indonesia,” in The 3rd International Conference ofComputer, Environment, Agriculture, Social Science, Health Science, Engineering andTechnology (ICEST), 2021, pp. 22–28. doi: 10.5220/0010037200220028.
B. K. Sihotang and A. Wanto, “Analisis Jaringan Syaraf Tiruan Dalam Memprediksi Jumlah Tamu Pada Hotel Non Bintang,” Jurnal Teknologi Informasi Techno, vol. 17, no. 4, pp. 333–346, 2018.
W. Saputra, J. T. Hardinata, and A. Wanto, “Resilient method in determining the best architectural model for predicting open unemployment in Indonesia,” IOP Conference Series: Materials Science and Engineering, vol. 725, no. 1, p. 012115, Jan. 2020, doi: 10.1088/1757-899X/725/1/012115.
A. Pradipta, D. Hartama, A. Wanto, S. Saifullah, and J. Jalaluddin, “The Application of Data Mining in Determining Timely Graduation Using the C45 Algorithm,” IJISTECH (International Journal of Information System & Technology), vol. 3, no. 1, p. 31, 2019, doi: 10.30645/ijistech.v3i1.30.
T. H. Sinaga, A. Wanto, I. Gunawan, S. Sumarno, and Z. M. Nasution, “Implementation of Data Mining Using C4.5 Algorithm on Customer Satisfaction in Tirta Lihou PDAM,” Journal of Computer Networks, Architecture, and High-Performance Computing, vol. 3, no. 1, pp. 9–20, 2021, doi: 10.47709/cnahpc.v3i1.923.
M. Widyastuti, A. G. Fepdiani Simanjuntak, D. Hartama, A. P. Windarto, and A. Wanto, “Classification Model C.45 on Determining the Quality of Custumer Service in Bank BTN Pematangsiantar Branch,” Journal of Physics: Conference Series, vol. 1255, no. 1, p. 012002, Aug. 2019, doi: 10.1088/1742-6596/1255/1/012002.
H. D. Wijaya and S. Dwiasnati, “Implementasi Data Mining dengan Algoritma Naïve Bayes pada Penjualan Obat,” Jurnal Informatika, vol. 7, no. 1, pp. 1–7, 2020, doi: 10.31311/ji.v7i1.6203.
F. Rizki, A. Faisol, and F. Santi Wahyuni, “Penerapan Metode Naive Bayes Untuk Memprediksi Penjualan Pada Ud. Hikmah Pasuruan Berbasis Web,” JATI (Jurnal Mahasiswa Teknik Informatika), vol. 4, no. 1, pp. 26–34, 2020, doi: 10.36040/jati.v4i1.2379.
Putri, E. Ucha, Sanni Irawan, and F. Rizky, “Implementasi Data Mining Untuk Prediksi Penjualan Pestisida Pada CV MITRA ARTHA SEJATI Menggunakan ALgoritma Naive Bayes,” KESATRIA( jurnal penerapan Sistem informasi dan manajemen, vol. 2, no. 1, pp. 39–46, 2021.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Maleakhi Gulo, Sumarno Sumarno, Fitri Anggraini

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Copyright (c) 2022 The authors. Published by Yayasan Literasi Indonesia This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License
The author(s) whose article is published in the JOMLAI journal attain the copyright for their article and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. By submitting the manuscript to JOMLAI, the author(s) agree with this policy. No special document approval is required.
The author(s) guarantee that:their article is original, written by the mentioned author(s),
- has never been published before,
- does not contain statements that violate the law, and
- does not violate the rights of others, is subject to copyright held exclusively by the author(s), and is free from the rights of third parties, and that the necessary written permission to quote from other sources has been obtained by the author(s).
The author(s) retain all rights to the published work, such as (but not limited to) the following rights:
- Copyright and other proprietary rights related to the article, such as patents,
- The right to use the substance of the article in its own future works, including lectures and books,
- The right to reproduce the article for its own purposes,
- The right to archive all versions of the article in any repository, and
- The right to enter into separate additional contractual arrangements for the non-exclusive distribution of published versions of the article (for example, posting them to institutional repositories or publishing them in a book), acknowledging its initial publication in this journal (JOMLAI: Journal of Machine Learning and Artificial Intelligence).
Suppose the article was prepared jointly by more than one author. Each author submitting the manuscript warrants that all co-authors have given their permission to agree to copyright and license notices (agreements) on their behalf and notify co-authors of the terms of this policy. JOMLAI will not be held responsible for anything that may arise because of the writer's internal dispute. JOMLAI will only communicate with correspondence authors.
Authors should also understand that their articles (and any additional files, including data sets, and analysis/computation data) will become publicly available once published. The license of published articles (and additional data) will be governed by a Creative Commons Attribution-ShareAlike 4.0 International License. JOMLAI allows users to copy, distribute, display and perform work under license. Users need to attribute the author(s) and JOMLAI to distribute works in journals and other publication media. Unless otherwise stated, the author(s) is a public entity as soon as the article is published