Analysis of Red Brick Product Quality Improvement at UD. Batu Bata Bulan Using CRISP-DM and C4.5 Algorithm
DOI:
10.47709/brilliance.v4i2.4208Keywords:
Red Brick Defects, data mining, CRISP-DM and Algorithm C.45, UD. Batu Bata BulanDimension Badge Record
Abstract
UD Batu Bata Bulan is a home industry in Batu Bulan Village that produces red bricks. The industry has been operating for 20 years and has been producing bricks every day. The home industry is facing problems related to the quality of red bricks that require appropriate action to improve to meet the desired quality. In addition, the home industry is still experiencing difficulties in conducting product quality inspections due to the lack of inspection technology to help the process. The problems faced can be detrimental to UD. Batu Bata Bulan. Therefore, it is necessary to analyze the causes of defective products in the process of producing red bricks and improve the quality of red brick products. Therefore, the researcher conducted an analysis to address the problems that occurred in the company related to product quality. The solution that can be given is to classify the type of defective product using the role of data mining. In this study, the standard Cross Industry Standard Process For Data Mining (CRISP-DM) procedure and C.45 Algorithm were used in data processing.The result of this research indicate significant knowledge in classifying black color defect in data this could facilitate the quality inspection department in making accurate decisions.
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References
Andarista R.R., & Jananto A. (2022). Penerapan Data Mining Algoritma C4.5 Untuk Klasifikasi Hasil Pengujian Kendaraan Bermotor,” Jurnal Tekno Kompak, vol. 16, no. 2.
Christian Y. (2020). Penerapan K-Means pada Segmentasi Pasar untuk Riset Pemasaran pada Startup Early Stage dengan Menggunakan CRISP-DM,” JURIKOM (Jurnal Riset Komputer), vol. 9, no. 4, p. 966. doi: 10.30865/jurikom.v9i4.4486.
Dhewayani F.N., et al. (2022). Implementasi K-Means Clustering untuk Pengelompokkan Daerah Rawan Bencana Kebakaran Menggunakan Model CRISP-DM. Jurnal Teknologi dan Informasi, vol. 12. doi: 10.34010/jati.v12i1.
Fatimah A.I., & Saepudin S. (2022). "Penerapan Data Mining Dengan Metode Apriori Pada Penjualan Sembako (Studi Kasus: Grosir Sembako Lina. (Vol. 8, Issue 2). https://rekayasa.nusaputra.ac.id/index
Jollyta D., Siddik M., Mawengkang H., & Efendi S. (2021). Teknik Evaluasi Cluster Solusi Menggunakan Python Dan Rapidminer .1st ed. Yogyakarta: Deepublish.
Kamagi D.H., & Hansun S. (2019). Implementasi Data Mining dengan Algoritma C4.5 untuk Memprediksi Tingkat Kelulusan Mahasiswa,” J. Ultim., vol. 6, no. 1, pp. 15–20. doi: 10.31937/ti.v6i1.327.
Nikmatun I.A. (2019). Implementasi Data Mining Untuk Klasifikasi Masa Studi Mahasiswa Menggunakan Algoritma K-Nearest Neighbor. Jurnal SIMETRIS, vol. 10, no. 2.
Nurmuslimah S. (2022). Sistem Pendukung Keputusan Pada Teknologi Informasi. PT. Global Eksekutif Teknologi.
Pambudi R. H., & Setiawan B.D. (2019). Penerapan Algoritma C4.5 Untuk Memprediksi Nilai Kelulusan Siswa Sekolah Menengah Berdasarkan Faktor Eksternal,” Jurnal Pengembangan Tekonologi Informasi dan Ilmu Komputer, vol. 2, no. 7, pp. 2637–2643.[Online]. Available: http://j-ptiik.ub.ac.id
Permatasari S. (2019). Pengaruh Bahan Tambah Batu Bata Merah Terhadap Kuat Tekan Beton fc’21 Menggunakan Agregat Kasar PT. Amr dan Agregat Halus Desa Sunggup Kota Baru.
Putera A.K., & Wahyono. (2019). Pengaruh Kualitas Pelayanan,Citra Merek,Dan Kualitas Produk Terhadap Loyalitas Konsumen Melalui Kepuasan Konsumen. Management Analysis Journal, vol. 7, no. 1. [Online]. Available: http://maj.unnes.ac.id
Santoso J.B., (2019). Pengaruh Kualitas Produk, Kualitas Pelayanan, Dan Harga Terhadap Kepuasan Dan Loyalitas Konsumen (Studi Pada Konsumen Geprek Bensu Rawamangun). Jurnal Akuntansi dan Manajemen, vol. 16, no. 01.
Suhanda Y., Kurniati I., & Norma S. (2020). Penerapan Metode Crisp-DM Dengan Algoritma K-Means Clustering Untuk Segmentasi Mahasiswa Berdasarkan Kualitas Akademik. Jurnal Teknologi Informatika dan Komputer, vol. 6, no. 2, pp. 12–20. doi: 10.37012/jtik.v6i2.299.
Suiroh S., Astuti R., & Basysyar F.M. (2024). Implementasi Algoritma K-Means Pada Pengelompokan Data Penerimaan Peserta Didik Baru Di Smkn 1 Balongan. JATI (Jurnal Mahasiswa Teknik Informatika), 8(1), 1–8. https://doi.org/10.36040/jati.v8i1.8335
Sulistiyawati A., & Supriyanto E. (2021). Implementasi Algoritma K-means Clustring dalam Penetuan Siswa Kelas Unggulan. Jurnal Teknokompak. https://doi.org/10.33365/jtk.v15i2.1162
Tirtayasa S., Lubis A. P., & Khair H. (2021). Keputusan Pembelian: Sebagai Variabel Mediasi Hubungan Kualitas Produk dan Kepercayaan terhadap Kepuasan Konsumen. Jurnal Inspirasi Bisnis dan Manajemen vol. 5, no. 1, pp. 2579–9312. [Online]. Available: http://jurnal.unswagati.ac.id/index.php/jibm
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