Revolutionizing Education through Artificial Intelligence: Fuzzy Multiple Attribute Decision Making Approach for Determining the Best Vocational High School

Article Preview

Abstract:

Vocational High School has its own charm for prospective students. Graduates have ready-to-work capability based on the skills needed in the workplace. Decision Making System using Fuzzy Multiple Attribute Decision Making with Weighted Product method as the best vocational high school determinant method is an interactive computer-based system that can help decision makers to find the best alternative based on predetermined criteria. In this case the intended alternative is to determine the best vocational high school based on the criteria by finding the weight value for each attribute. The criteria needed in decision making namely facility, accreditation, quality, student (non-academic achievement), cost, human resources teacher.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

234-239

Citation:

Online since:

June 2019

Export:

Price:

* - Corresponding Author

[1] S. A. K. Sukadari, Suyata, Penelitian Etnografi Tentang Budaya Sekolah Dalam Pendidikan Karakter Di Sekolah Dasar., p.1–11, (2015).

DOI: 10.21831/jppfa.v3i1.7812

Google Scholar

[2] I. T. Dinar Mahdalena, Mungin Eddy Wibowo, Pengembangan Modul Bimbingan Karir Berbasis Multimedia Interaktif Untuk Meningkatkan Kematangan Karir Siswa,, J. Bimbing. Konseling, vol. 2, no. 1, p.1–9, (2013).

DOI: 10.30736/akademika.v9i2.69

Google Scholar

[3] A. D. W. KIisworo, Model Sistem Pendukung Keputusan Menggunakan Metode Fmadm Untuk Seleksi Beasiswa A-PPA Dan Bbp-Ppa Pada Perguruan Tinggi,, p.1–6, (2017).

DOI: 10.25077/teknosi.v2i3.2016.175-188

Google Scholar

[4] Basri, Metode Weightd Product ( WP ) Dalam Sistem Pendukung Keputusan Penerimaan Beasiswa Prestasi,, Insypro, vol. 2, no. 1, p.1–6, (2017).

DOI: 10.22202/ei.2019.v6i1.3669

Google Scholar

[5] Fauzi, Nungsiyati, T. Noviarti, M. Muslihudin, R. Irviani, and A. Maseleno, Optimal Dengue Endemic Region Prediction using Fuzzy Simple Additive Weighting based Algorithm,, Int. J. Pure Appl. Math., vol. 118, no. 7, p.473–478, (2018).

Google Scholar

[6] R. Irviani, I. Dinulhaq, D. Irawan, R. Renaldo, and A. Maseleno, Areas Prone of the Bad Nutrition based Multi Attribute Decision Making with Fuzzy Simple Additive Weighting for Optimal Analysis,, Int. J. Pure Appl. Math., vol. 118, no. 7, p.589–596, (2018).

Google Scholar

[7] E. Turban, J. E. Aronson, and T.-P. Liang, Decision Support Systems and Intelligent Systems,, Decis. Support Syst. Intell. Syst., vol. 7, p.867, (2007).

Google Scholar

[8] K. A. Henry Wibowo, Riska Amalia, Andi Fadlun M, Sistem Pendukung Keputusan Untuk Menentukan Penerima Beasiswa Bank BRI Menggunakan FMADM (Studi Kasus: Mahasiswa Fakultas Teknologi Industri Universitas Islam Indonesia),, Semin. Nas. Apl. Teknol. Inf. 2009, no. Snati, p.1–6, (2009).

DOI: 10.35457/antivirus.v11i1.195

Google Scholar

[9] W. Waziana, R. Irviani, I. Oktaviani, F. Satria, D. Kurniawan, and A. Maseleno, Fuzzy Simple Additive Weighting for Determination of Recipients Breeding Farm Program,, Int. J. Pure Appl. Math., vol. 118, no. 7, p.93–100, (2018).

Google Scholar

[10] S. Mukodimah, M. Muslihudin, A. Andoyo, S. Hartati, and A. Maseleno, Fuzzy Simple Additive Weighting and its Application to Toddler Healthy Food,, Int. J. Pure Appl. Math., vol. 118, no. 7, p.1–7, (2018).

Google Scholar

[11] S. Kusumadewi, S. Hartati, A. Harjoko, and Retanto Wardoyo, Fuzzy Multi-Attribute Decision Making (Fuzzy MADM). Yogyakarta: Graha Ilmu, (2013).

Google Scholar

[12] M. Muslihudin and M. Gumanti, A System To Support Decision Makings In Selection Of Aid Receivers For Classroom Rehabilitation For Senior High Schools By Education Office Of Pringsewu District By,, IJISCS, vol. 1, no. 2, p.1–9, (2017).

DOI: 10.56327/ijiscs.v1i2.495

Google Scholar

[13] M. Muslihudin, Fauzi, T. S. Susanti, Sucipto, and A. Maseleno, The Priority of Rural Road Development using Fuzzy Logic based Simple Additive Weighting,, Int. J. Pure Appl. Math., vol. 118, no. 8, p.9–16, (2018).

Google Scholar

[14] A. Alinezhad, A. Amini, and A. Alinezhad, Sensitivity analysis of simple additive weighting method (SAW): the results of change in the weight of one attribute on the final ranking of alternatives,, J. Ind. Eng., (2009).

Google Scholar

[15] M. M. Febri Ariyanto, Sistem Pendukung Keputusan Menentukan Sekolah Menengah Kejuruan (SMK) Unggulan Di Wilayah Lampung Tengah Menggunakan Metode Topsis,, J. TAM ( Technol. Accept. Model ), vol. 5, no. 2, p.1–8, (2015).

DOI: 10.36448/jmsit.v7i2.964

Google Scholar

[16] I. S. Sianturi, Sistem Pendukung Keputusan Untuk Menentkan Pemilihan Jurusan Siswa Dengan Menggunakan Metode Weighted Product (Studi Kasus : SMA Swasta HKBP Doloksanggul),, Inf. dan Teknol. Ilm., vol. 1, no. Sistem Pendukung Keputusan, p.19–22, (2013).

DOI: 10.30587/indexia.v1i2.2541

Google Scholar

[17] J. R. S. C. Mateo, Weighted sum method and weighted product method,, in Green Energy and Technology, 2012, vol. 83, p.19–22.

DOI: 10.1007/978-1-4471-2346-0_4

Google Scholar

[18] A. Maseleno, M. M. Hasan, M. Muslihudin, and T. Susilowati, Finding Kicking Range of Sepak Takraw Game: Fuzzy Logic and Dempster-Shafer Theory Approach,, Indones. J. Electr. Eng. Comput. Sci., vol. 2, no. 1, p.187, (2016).

DOI: 10.11591/ijeecs.v2.i1.pp187-193

Google Scholar

[19] A. Maseleno, N. Tuah, and C. R. Tabbu, Fuzzy Logic and Dempster-Shafer Theory to Predict the Risk of Highly Pathogenic Avian Influenza H5N1 Spreading,, World Appl. Sci. J., vol. 34, no. 8, p.995–1003, (2016).

DOI: 10.1016/j.procs.2015.07.349

Google Scholar

[20] A. Maseleno, M.M. Hasan. (2011). Fuzzy Logic Based Analysis of the Sepak takraw Games Ball Kicking with the Respect of Player Arrangement. World Applied Programming Journal, 2(5), 285-293.

Google Scholar

[21] A. Maseleno, M.M. Hasan. (2015). Finding Kicking Range of Sepak Takraw Game: A Fuzzy Logic Approach. Indonesian Journal of Electrical Engineering and Computer Science, 14(3), 557-564.

DOI: 10.11591/telkomnika.v14i3.7833

Google Scholar

[22] A. Maseleno, M.M. Hasan. (2013). Fuzzy logic and dempster-shafer theory to find kicking range of sepak takraw game. Proceedings of 5th International Conference on Computer Science and Information Technology (CSIT). Amman, Jordan, 8-12.

DOI: 10.1109/csit.2013.6588750

Google Scholar

[23] A. Maseleno, M.M. Hasan. (2013). Dempster-shafer theory for move prediction in start kicking of the bicycle kick of sepak takraw game. Middle-East Journal of Scientific Research, 16(7), 896-903.

DOI: 10.1109/acsat.2012.8

Google Scholar

[24] A. Maseleno, M.M. Hasan. (2012). Move prediction in start kicking of sepak takraw game using Dempster-Shafer theory. Proceedings of International Conference on Advanced Computer Science Applications and Technologies (ACSAT). Kuala Lumpur, Malaysia, 376-381.

DOI: 10.1109/acsat.2012.8

Google Scholar

[25] A. Maseleno, M.M. Hasan, N. Tuah, M. Muslihudin. (2015). Fuzzy Logic and Dempster-Shafer belief theory to detect the risk of disease spreading of African Trypanosomiasis. Proceedings of Fifth International Conference on Digital Information Processing and Communications (ICDIPC). University of Applied Sciences and Arts Western Switzerland (HES-SEO Valais Wallis), Switzerland, 153-158.

DOI: 10.1109/icdipc.2015.7323022

Google Scholar

[26] A. Maseleno, M.M. Hasan, N. Tuah, C.R. Tabbu. (2015). Fuzzy Logic and Mathematical Theory of Evidence to Detect the Risk of Disease Spreading of Highly Pathogenic Avian Influenza H5N1. Procedia Computer Science, 57, 348-357.

DOI: 10.1016/j.procs.2015.07.349

Google Scholar

[27] A. Maseleno, G. Hardaker. (2016). Malaria detection using mathematical theory of evidence. Songklanakarin Journal of Science & Technology, 38(3), 257-263.

Google Scholar

[28] A. Maseleno, M.M. Hasan. (2013). The Dempster-Shafer theory algorithm and its application to insect diseases detection. International Journal of Advanced Science and Technology, 50(1), 111-119.

Google Scholar

[29] A. Maseleno, M.M. Hasan. (2012). Poultry diseases warning system using dempster-shafer theory and web mapping. International Journal of Advanced Research in Artificial Intelligence, 1(3), 44-48.

DOI: 10.14569/ijarai.2012.010308

Google Scholar

[30] A. Maseleno, M.M. Hasan. (2012). Skin diseases expert system using Dempster-Shafer theory. International Journal of Intelligent Systems and Applications, 4(5), 38-44.

DOI: 10.5815/ijisa.2012.05.06

Google Scholar

[31] A. Maseleno, M.M. Hasan. (2012). African Trypanosomiasis Detection using Dempster-Shafer Theory. Journal of Emerging Trends in Computing and Information Sciences, 3(4), 480-487.

Google Scholar

[32] A. Maseleno, M.M. Hasan. (2012). Avian influenza (H5N1) expert system using Dempster-Shafer theory. International Journal of Information and Communication Technology, 4(2), 227-241.

DOI: 10.1504/ijict.2012.048766

Google Scholar

[33] A. Maseleno, M. Muslihudin. (2015). Ebola virus disease detection using Dempster-Shafer evidence theory. Proceedings of IEEE International Conference on Progress in Informatics and Computing (PIC). Nanjing, China, 579-582.

DOI: 10.1109/pic.2015.7489914

Google Scholar

[34] A. Maseleno, M.M. Hasan. (2012). Skin infection detection using Dempster-Shafer theory. Proceedings of International Conference on  Informatics, Electronics & Vision (ICIEV). Dhaka, Bangladesh, 1147-1151.

DOI: 10.1109/iciev.2012.6317330

Google Scholar

[35] A. Maseleno, R.Z. Hidayati. (2017). Hepatitis disease detection using Bayesian theory. In AIP Conference Proceedings. East Kalimantan, Indonesia, 050001-1 – 050001-10.

DOI: 10.1063/1.4975973

Google Scholar

[36] A. Maseleno, M. Huda, M. Siregar, R. Ahmad, A. Hehsan, Z. Haroon, M.N. Ripin, S.S. Ikhwani, K.A. Jasmi. (2017). Combining the Previous Measure of Evidence to Educational Entrance Examination. Journal of Artificial Intelligence, 10 (3), 85-90.

DOI: 10.3923/jai.2017.85.90

Google Scholar

[37] T. Susilowati, E.Y. Anggraeni, Fauzi, W. Andewi, Y. Handayani, A. Maseleno, Using Profile Matching Method to Employee Position Movement,, International Journal of Pure and Applied Mathematics, vol. 118, no. 7, pp.415-423, (2018).

Google Scholar

[38] M. Muslihudin, Trisnawati, A. Latif, S. Ipnuwati, R. Wati, A. Maseleno, A Solution to Competency Test Expertise of Engineering Motorcycles using Simple Additive Weighting Approach,, International Journal of Pure and Applied Mathematics, vol. 118, no. 7, pp.261-267, (2018).

Google Scholar

[39] Oktafianto, M.R. Al Akbar, Y. Fitrian, Zulkifli, Sodikin, Wulandari, A. Maseleno, Dismissal Working Relationship using Analytic Hierarchy Process Method,, International Journal of Pure and Applied Mathematics, vol. 118, no. 7, pp.177-184, (2018).

Google Scholar

[40] A. Maseleno, M. Huda, K.A. Jasmi, B. Basiron, I. Mustari, A.G. Don, R. Ahmad, Hau-Kashyap Approach for Student's Level of Expertises,, Egyptian Informatics Journal, (2018).

DOI: 10.1016/j.eij.2018.04.001

Google Scholar