SISTEM PENDUKUNG KEPUTUSAN PEMBERHENTIAN HUBUNGAN KERJA DENGAN METODE AHP
(1) STMIK Pringsewu, Lampung
(2) STMIK Pringsewu, Lampung
Corresponding Author
Abstract
Perusahaan atau lembaga pendidikan harus memiliki manajemen yang efektif dan profesional. Manajemen yang efektif dan profesional, tidak lepas dari dukungan dari semua karyawan profesional. Banyak perusahaan atau lembaga pendidikan salah memutuskan di bidang Pemberhentian Hubungan Kerja yang berakibat menurunnya produk atau kinerja perusahaan. Untuk menentukan pemberhentian hubungan kerja banyak kriteria yang dijadikan penilaian pemilihan. Salah satu metode sistem rekomendasi dalam menentukan persoalan yang melibatkan multi kriteria adalah dengan metode Analytical Hierarchy Process (AHP) dipilih karena metode ini memberikan kepentingan yang lebih dominan. Pada penelitian ini dibangun sistem aplikasi yang menggunakan metode Analytical Hierarchy Process (AHP). Aplikasi ini digunakan untuk membantu melakukan penilaian dan dapat dijadikan masukan bagi perusahaan dalam mengambil keputusan pemberhentian hubungan kerja.
Keywords
References
. McLeod, R. 1998. Sistem Pendukung Keputusan pada Penerimaan Karyawan PT. Tapioka. Jakarta.
. Suryadi, K. 2002. Sistem Pendukung Keputusan dalam Penerimaan Beasiswa pada SMA Negeri 1 Garut.
. Huda, M., Maseleno, A., Shahrill, M., Jasmi, K. A., Mustari, I., and Basiron, B. (2017). Exploring Adaptive Teaching Competencies in Big Data Era. International Journal of Emerging Technologies in Learning, 12(3), 68-83.
. Huda, M., Maseleno, A., Atmotiyoso, P., Siregar, M., Ahmad, R., Jasmi, K.A., Muhamad, N.H.N., Mustari, I.M., and Basiron, B. (2017). Emerging Big Data Technologies. Insights into Innovative Environment for Online Learning Resources. International Journal of Emerging Technologies in Learning. (In press).
. Maseleno, A.; and Hasan, M.M. (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.
. Maseleno, A; and Hasan, M.M. (2015). Finding Kicking Range of Sepak Takraw Game: A Fuzzy Logic Approach. Indonesian Journal of Electrical Engineering and Computer Science, 14(3), 557-564.
. Maseleno, A.; and Hasan, M.M. (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.
. Maseleno, A.; Hasan, M.M.; Muslihudin, M.; and Susilowati, T. (2016). Finding Kicking Range of Sepak Takraw Game: Fuzzy Logic and Dempster-Shafer Theory Approach. Indonesian Journal of Electrical Engineering and Computer Science, 2(1), 187-193.
. Maseleno, A.; and Hasan, M.M. (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.
. Maseleno, A.; and Hasan, M.M. (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.
. Maseleno, A.; Hasan, M.M.; Tuah, N.; and Muslihudin, M. (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.
. Maseleno, A.; Hasan, M.M.; Tuah, N.; and Tabbu, C.R. (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.
. Maseleno, A.; and Hardaker, G. (2016). Malaria detection using mathematical theory of evidence. Songklanakarin Journal of Science & Technology, 38(3), 257-263.
. Maseleno, A.; and Hasan, M.M. (2013). The Dempster-Shafer theory algorithm and its application to insect diseases detection. International Journal of Advanced Science and Technology, 50(1), 111-119.
. Maseleno, A.; and Hasan, M.M. (2012). Poultry diseases warning system using dempster-shafer theory and web mapping. International Journal of Advanced Research in Artificial Intelligence, 1(3), 44-48.
. Maseleno, A.; and Hasan, M.M. (2012). Skin diseases expert system using Dempster-Shafer theory. International Journal of Intelligent Systems and Applications, 4(5), 38-44.
. Maseleno, A.; and Hasan, M.M. (2012). African Trypanosomiasis Detection using Dempster-Shafer Theory. Journal of Emerging Trends in Computing and Information Sciences, 3(4), 480-487.
. Maseleno, A.; and Hasan, M.M. (2012). Avian influenza (H5N1) expert system using Dempster-Shafer theory. International Journal of Information and Communication Technology, 4(2), 227-241.
. Maseleno, A.; and Muslihudin, M. (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.
. Maseleno, A.; and Hasan, M.M. (2012). Skin infection detection using Dempster-Shafer theory. Proceedings of International Conference on Informatics, Electronics & Vision (ICIEV). Dhaka, Bangladesh, 1147-1151.
. Maseleno, A.; and Hidayati, R.Z. (2017). Hepatitis disease detection using Bayesian theory. In AIP Conference Proceedings. East Kalimantan, Indonesia, 050001-1 – 050001-10.
. Maseleno, A.; Huda, M.; Siregar, M.; (2017). Combining the Previous Measure of Evidence to Educational Entrance Examination. Journal of Artificial Intelligence, 10 (3), 85-90.
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