Klasifikasi Kerusakan Barang Dengan Menggunakan Komparasi Algoritma C4.5 Dan Naive Bayes
DOI:
https://doi.org/10.55123/jumintal.v1i1.303Keywords:
Comparison, Data mining, Naïve Bayes, C4.5, Damage of GoodsAbstract
Process control is needed to prevent goods from being damaged both in the production and delivery processes. Therefore, in this study, a classification of conditions was carried out whether the goods that experienced the incident could still be used or not. This study uses a classification model with the C4.5 and Naïve Bayes algorithms, by evaluating using the confusion matrix method, the best accuracy in the C4.5 algorithm is 73.9% recall 72.9% and 88% precision, with these results it can be said that algorithm C 4.5 is good to be implemented in this decision support system model
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References
Embu, W. S., 2020. liputan6. [Online]
Available at: https://www.liputan6.com/bisnis/read/4119505/industri-makanan-dan-minuman-jadi-andalan-tekan-defisit-neraca-dagang
[Accessed 17 Januari 2020].
Fiandra, Y. A., Defit, S. & Yuhandri, Y., 2017. Penerapan Algoritma C4. 5 untuk Klasifikasi Data Rekam Medis berdasarkan International Classification Diseases (ICD-10). Jurnal RESTI, 1(2), p. 82–89.
Mukminin, A. & Riana, D., 2017. Komparasi Algoritma C4.5, Naïve Bayes Dan Neural Network Untuk Klasifikasi Tanah. Jurnal Informatika, 4(1), pp. 21-31.
Romli, I., Kharida, F. & Naya, C., 2020. Penentuan Kepuasan Pelanggan Terhadap Pelayanan Kantor Pelayanan Pajak Menggunakan C4.5 dan PSO. Jurnal RESTI, 4(2), pp. 296-302.
Santoso, T. B., 2014. Analisa Dan Penerapan Metode C4. 5 Untuk Prediksi Loyalitas Pelanggan. Jurnal Ilmiah Fakultas Teknik LIMIT’S, 10(1), p. 1–10.
Tempola, F., Muhammad, M. & Khairan, A., 2018. Perbandingan Klasifikasi Antara KNN dan Naive Bayes pada Penentuan Status Gunung Berapi dengan K-Fold Cross Validation. JTIIK, 5(5), p. 577.
Indah Agustina, N. (2018). PENGARUH JUMLAH PENDUDUK MISKIN DAN KONSUMSI RUMAH TANGGA TERHADAP INDEKS PEMBANGUNAN MANUSIA DI INDONESIA (Doctoral dissertation, UNIVERSITAS SULTAN AGENG TIRTAYASA).
Maya S., Abi W., Sudarwanto, 2021, Pemodelan Jumlah Kasus Malaria di Indonesia Menggunakan Generalized Linear Model, Jurnal Statistika dan Aplikasinya, No. 1, Vol. 5: https://doi.org/10.21009/JSA.05111.
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Copyright (c) 2022 Ikhsan Romli, M Edi Kurniawan
This work is licensed under a Creative Commons Attribution 4.0 International License.
