CPU and eGPU Support System Based on Naive Bayes Classification

https://doi.org/10.22146/ijccs.63689

Mursyid Ardiansyah(1*), Wahyu Hidayat(2), Ema Utami(3), Suwanto Raharjo(4)

(1) AMIKOM University Yogyakarta
(2) AMIKOM University Yogyakarta
(3) AMIKOM University Yogyakarta
(4) IST AKPRIND Yogyakarta
(*) Corresponding Author

Abstract


Central Processing Unit (CPU) and External Graphics Processing Unit (eGPU) technology are known as overclocks which aim to make the device exceed the benchmarks set by the device maker. Until now there is no determination to rank the two hardware within certain limits such as hardware price range and year-by-year. Therefore, it is necessary to process the ranking of the hardware using Simple Additive Weighting (SAW) to obtain a ranking range and determine the weight per type of hardware analyzed. It can be classified using Naïve Bayes to determine results of criteria combination between two hardware to determine possible criteria into "not good" and "good". This classification used to determine probability criteria of choosing a combination of CPU and eGPU hardware. The results of this study are getting the best CPU and eGPU every year using SAW and then classifying it for pricing. In testing conducted on application of Naïve Bayes using 80% of training data has 2776 data and 20% of testing data has 695 data that will be tested for accuracy, precision, recall, and F1-score. For results of tests that have been carried out get 0.78 accuracy results, precision 1, Recall 0.764, and F1-Score 0.866.

Keywords


Simple Additive Weighting; Naïve Bayes; Classification

Full Text:

PDF


References

[1] F. Wu, J. Chen, Y. Dong, W. Zheng, and X. Pan, “A Holistic Energy-Efficient Approach fora Processor-Memory System,” vol. 24, pp. 468–483, 2019. Available: https://ieeexplore.ieee.org/abstract/document/8660532. [Accessed: 27-Jan-2021]

[2] S. S. Hegna, “Design of efficient parallel algorithms for the TSP on multicore processors with shared memory,” no. February, 2019. Available: http://urn.nb.no/URN:NBN:no-71102. [Accessed: 27-Jan-2021]

[3] R. N. Perwiro Atmojo, Y. Lie, H. H. Muljo, U. M. Saputra, D. Christianto, and D. Trisaputra, “The ‘Voice of Customer’ Web Application at State-Owned Telecommunication Company,” Proc. 2018 Int. Conf. Inf. Manag. Technol. ICIMTech 2018, no. September, pp. 333–338, 2018. Available: https://ieeexplore.ieee.org/abstract/document/8528097/. [Accessed: 27-Jan-2021]

[4] J. D. Santoso, T. Komputer, F. I. Komputer, and C. Catur, “Analisis password crackcing mneggunakan gpu process,” vol. 3, no. 1, pp. 143–150, 2019. Available: http://e-jurnal.pelitanusantara.ac.id/index.php/mantik/article/view/602. [Accessed: 29-Apr-2021]

[5] N. Krisnaryatko and K. Ika, “Analisis Kinerja Keuangan Perusahaan dengan Du Pont System ( Studi Pada Nvidia Corporation dan Advanced Micro Devices , Inc,” J. Akuntansui Keuang. dan Bisnis Vol. 12, No. 2, Novemb. 2019, vol. 12, no. 2, pp. 77–86, 2019. Available: https://jurnal.pcr.ac.id/index.php/jakb/article/view/2547. [Accessed: 29-Apr-2021]

[6] D. T. Alamanda, A. Ramdhani, I. Kania, W. Susilawati, and E. S. Hadi, “Sentiment Analysis Using Text Mining of Indonesia Tourism Reviews via Social Media,” Int. J. Humanit. Arts Soc. Sci., vol. 5, no. 2, pp. 72–82, 2019. Available: http://kkgpublications.com/wp-content/uploads/2019/11/ijhss.5.10004-2.pdf. [Accessed: 27-Jan-2021]

[7] T. Retnasari, T. Prihatin, and M. Fikri, “A Determination of The Best Employees using Simple Additive Weighting (SAW) Method,” SinkrOn, vol. 4, no. 1, p. 106, 2019. Available: http://jurnal.polgan.ac.id/index.php/sinkron/article/view/10169. [Accessed: 27-Jan-2021]

[8] D. Krisbiantoro and W. M. Baihaqi, “the Implementation of Simple Additive Weighting Method in the Selection of Rehabilitation Fund Recipients for Uninhabitable Home,” Simetris J. Tek. Mesin, Elektro dan Ilmu Komput., vol. 10, no. 1, pp. 309–318, 2019. Available: https://jurnal.umk.ac.id/index.php/simet/article/view/3023. [Accessed: 27-Jan-2021]

[9] Artan C. and T. Kaya, “Analysis of E-Government Strategies with Hesitant Fuzzy Linguistic Multi-Criteria Decision Making Techniques,” Intell. Fuzzy Tech. Big Data Anal. Decis. Mak., vol. 1029, pp. 313–321, 2019. Available: https://link.springer.com/chapter/10.1007/978-3-030-23756-1_126. [Accessed: 27-Jan-2021]

[10] A. Pataropura, R. Riki, and J. G. Manu, “Decision Support System for Selection of Assembly Using Profile Matching Method and Simple Additive Weighting Method (Case Study: GKIN Diaspora Church),” bit-Tech, vol. 2, no. 1, pp. 43–52, 2019. Available: http://jurnal.kdi.or.id/index.php/bt/article/view/100. [Accessed: 27-Jan-2021]

[11] J. Jahja, R. A. Hartono, and K. M. Suryaningrum, “Pemilihan Graphics Processing Unit Nvidia dan AMD Menggunakan Algoritma Simple Additive Weighting,” CogITo Smart J., vol. 6, no. 1, p. 25, 2020. Available: http://cogito.unklab.ac.id/index.php/cogito/article/view/197. [Accessed: 29-Apr-2021]

[12] A. Hikmat and A. Abdullah, “The Impact of Overclocking the CPU to the Genetic Algorithm,” Ijcsns, vol. 9, no. 5, p. 175, 2009. Available: http://eprints.utp.edu.my/793. [Accessed: 27-Jan-2021]

[13] F. Haswan, “Application of Simple Additive Weighting Method to Determine Outstanding School Principals,” SinkrOn, vol. 3, no. 2, p. 186, 2019. Available: http://jurnal.polgan.ac.id/index.php/sinkron/article/view/10082. [Accessed: 27-Jan-2021]

[14] L. Y. Bai et al., “Prediction of effective drug combinations by an improved naïve bayesian algorithm,” Int. J. Mol. Sci., vol. 19, no. 2, 2018. Available: https://www.mdpi.com/1422-0067/19/2/467. [Accessed: 27-Jan-2021]

[15] F. Tempola, M. Muhammad, and A. Khairan, “Perbandingan Klasifikasi Antara KNN dan Naive Bayes pada Penentuan Status Gunung Berapi dengan K-Fold Cross Validation,” J. Teknol. Inf. dan Ilmu Komput., vol. 5, no. 5, p. 577, 2018. https://jtiik.ub.ac.id/index.php/jtiik/article/view/983

[16] W. Gata et al., “Algorithm Implementations Naïve Bayes, Random Forest. C4.5 on Online Gaming for Learning Achievement Predictions,” vol. 258, no. Icream 2018, 2019. Available: https://www.atlantis-press.com/proceedings/icream-18/55914201. [Accessed: 27-Jan-2021]

[17] Y. Gultepe, “The Use of Data Mining Techniques in Heart Disease Prediction,” vol. 8, no. 4, pp. 136–141, 2019. Available: https://ieeexplore.ieee.org/document/7873142. [Accessed: 27-Jan-2021]

[18] Y. I. Kurniawan, “Perbandingan Algoritma Naive Bayes dan C.45 dalam Klasifikasi Data Mining,” J. Teknol. Inf. dan Ilmu Komput., vol. 5, no. 4, p. 455, 2018. Available: https://jtiik.ub.ac.id/index.php/jtiik/article/view/803. [Accessed: 29-Apr-2021]

[19] S. Kusumadewi, Fuzzy Multi-Attribute Decision Making (FUZZY MADM). Yogyakarta: Graha Ilmu, 2006. Available: http://journals.usm.ac.id/index.php/transformatika/article/view/441. [Accessed: 27-Jan-2021]

[20] M. K. K and K. P. Sankaranarayanan Seena, “Prediction of Different Dermatological Conditions Using Naïve Bayesian Classification,” Int. J. Adv. Res. Comput. Sci. Softw. Eng., vol. 4, no. 1, pp. 2277–128, 2014. Available: https://doi.org/10.1016/j.imu.2019.100202. [Accessed: 27-Jan-2021]

[21] M. Bramer, Principles of Data Mining. London: Springer, 2007.

[22] J. Han, M. Kamber, and J. Pei, Introduction. 2012.

[23] J. Sepúlveda and S. A. Velastín, “F1 score assesment of Gaussian mixture background subtraction algorithms using the MuHAVi dataset,” IET Semin. Dig., vol. 2015, no. 5, pp. 1–6, 2015. Available: https://digital-library.theiet.org/content/conferences/10.1049/ic.2015.0106. [Accessed: 27-Jan-2021]



DOI: https://doi.org/10.22146/ijccs.63689

Article Metrics

Abstract views : 1344 | views : 892

Refbacks

  • There are currently no refbacks.




Copyright (c) 2021 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.



Copyright of :
IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
ISSN 1978-1520 (print); ISSN 2460-7258 (online)
is a scientific journal the results of Computing
and Cybernetics Systems
A publication of IndoCEISS.
Gedung S1 Ruang 416 FMIPA UGM, Sekip Utara, Yogyakarta 55281
Fax: +62274 555133
email:ijccs.mipa@ugm.ac.id | http://jurnal.ugm.ac.id/ijccs



View My Stats1
View My Stats2