MODEL PENDUKUNG KEPUTUSAN SELEKSI PENERIMAAN ASISTEN LABORATORIUM MENGGUNAKAN PERPADUAN METODE ROC DAN WASPAS
DOI:
https://doi.org/10.31000/jika.v6i1.5516Abstract
Pentingnya proses pengambilan keputusan yang tidak hanya cepat, namun juga tepat dan akurat telah menjadi suatu kewajiban bagi setiap institusi, tidak terkecuali dalam institusi perguruan tinggi. Permasalahan dalam penelitian ini adalah terkait proses pengambilan keputusan dalam seleksi penerimaan asisten laboratorium. Penelitian ini mengusulkan sebuah model pendukung keputusan melalui perpaduan antara metode Rank Order Centroid (ROC) dan Weighted Aggregated Sum Product Assesment (WASPAS). Hasil penelitian ini menunjukkan bahwa model yang diusulkan dapat digunakan dengan baik dalam melakukan proses seleksi penerimaan asisten laboratorium. Dalam Penelitian ini, penggunaan ROC mampu memberikan bobot kriteria yang sesuai berdasarkan tingkat kepentingan kriteria dari pengambil keputusan. Sedangkan, penggunaan metode WASPAS mampu menghasilkan keputusan berupa alternatif terbaik yang dapat digunakan untuk membantu pihak pengambil keputusan.References
Al-Hafiz, N. W., Mesran, & Suginam. (2017). Sistem Pendukung Keputusan Penentukan Kredit Pemilikan Rumah Menerapkan Multi-Objective Optimization on the Basis of Ratio Analysis ( Moora ). KOMIK (Konferensi Nasional Teknologi Informasi Dan Komputer), I(1), 306–309. http://www.stmik-budidarma.ac.id/ejurnal/index.php/komik/article/viewFile/513/455
Angeline, M., & Astuti, F. (2018). Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik Menggunakan Metode Profile Matching. Jurnal Ilmiah SMART, II(2), 45–51.
Barus, S., Sitorus, V. M., Napitupulu, D., Mesran, M., & Supiyandi, S. (2018). Sistem Pendukung Keputusan Pengangkatan Guru Tetap Menerapkan Metode Weight Aggregated Sum Product Assesment (WASPAS). Jurnal Media Informatika Budidarma, 2(2), 10–15. https://doi.org/10.30865/mib.v2i2.594
Chandra, K. A., & Hansun, S. (2019). Sistem Rekomendasi Pemilihan Laptop Dengan Metode Waspas. Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering), 6(2), 76–81. https://doi.org/10.33019/ecotipe.v6i2.1019
Fadlan, M., Muhammad, & Hadriansa. (2017). Terapan Kombinasi Metode Topsis dan Analytical Hierarchy Process Pada Perekomendasian Penerima Beasiswa Peningkatan Prestasi Akademik (studi kasus pada STMIK PPKIA Tarakanita Rahmawati). Jurnal SIMETRIS, 8(2), 663–670. https://doi.org/10.24176/simet.v8i2.1565
Faiz, A. (2020). Pengembangan Sistem Pendukung Keputusan Untuk Seleksi Penerimaan Beasiswa Dengan Metode Saw Dan Topsis : Studi Kasus Universitas Muhammadiyah Tangerang. JIKA (Jurnal Informatika), 4(1), 49. https://doi.org/10.31000/jika.v4i1.2424
Ickhsan, M., Anggraini, D., Haryono, R., Sahir, S. H., & Rohminatin. (2018). Sistem Pendukung Keputusan Pemberian Kredit Usaha Rakyat ( KUR ) Menggunakan Metode Weighted Product. JURIKOM (Jurnal Riset Komputer), 5(2), 97–102.
Laurentinus, L., & Rinaldi, S. (2019). Implementasi Metode Analytical Hierarchy Process dan Simple Additive Weighting untuk Pemilihan Dosen Terbaik Studi Kasus STMIK Atma Luhur. Jurnal Teknologi Informasi Dan Ilmu Komputer, 6(6), 655. https://doi.org/10.25126/jtiik.2019661636
Ruskan, E. L. (2017). Kolaborasi Metode Saw Dan Ahp Untuk Sistem Pendukung Keputusan Penilaian Kinerja Asisten Laboratorium. JSI: Jurnal Sistem Informasi (E-Journal), 9(1), 1204–1215. https://doi.org/10.36706/jsi.v9i1.4204
Simanjorang, R. M. (2018). Sistem Pendukung Keputusan Penentuan Mahasiswa Lulusan Terbaik Menggunakan Metode Analitycal Hierarchy Process Pada Perguruan Tinggi. Jurnal Mantik Penusa, 2(1), 1–10.
Situmorang, E., & Rindari, F. (2019). Decision Support System For Selection Of The Best Doctors In Sari Mutiara Hospital Using Fuzzy Tsukamoto Method. Jurnal Teknik Informatika C.I.T, 11(2), 45–50. www.medikom.iocspublisher.org/index.php/JTI
Stojić, G., Stević, Ž., AntucheviÄiene, J., PamuÄar, D., & Vasiljević, M. (2018). A novel rough WASPAS approach for supplier selection in a company manufacturing PVC carpentry products. Information (Switzerland), 9(5). https://doi.org/10.3390/info9050121
Sugiarti, S., Nahulae, D. K., Panggabean, T. E., & Sianturi, M. (2018). Sistem Pendukung Keputusan Penentuan Kebijakan Strategi Promosi Kampus Dengan Metode Weighted Aggregated Sum Product Assesment (WASPAS). JURIKOM (Jurnal Riset Komputer), 5(2), 103–108. http://ejurnal.stmik-budidarma.ac.id/index.php/jurikom%7CPage%7C103
Sugiyarti, E., Jasmi, K. A., Basiron, B., Huda, M., Shankar, K., & Maseleno, A. (2018). Decision support system of scholarship grantee selection using data mining. International Journal of Pure and Applied Mathematics, 119(15), 2239–2249. https://doi.org/10.5772/47788
Wanto, A., & Kurniawan, E. (2018). Seleksi Penerimaan Asisten Laboratorium Menggunakan Algoritma Ahp Pada Amik-Stikom Tunas Bangsa Pematangsiantar. JIKO (Jurnal Informatika Dan Komputer), 3(1), 11. https://doi.org/10.26798/jiko.2018.v3i1.106
Yunaldi, A. (2019). Sistem Pendukung Keputusan Seleksi Bantuan Siswa Miskin Menerapkan Kombinasi Metode SAW dan ROC. Jurnal Media Informatika Budidarma, 3(4), 376. https://doi.org/10.30865/mib.v3i4.1511
Downloads
Published
Issue
Section
License
License and Copyright Agreement
In submitting the manuscript to the journal, the authors certify that:
- They are authorized by their co-authors to enter into these arrangements.
- That it is not under consideration for publication elsewhere,
- That its publication has been approved by all the author(s) and by the responsible authorities – tacitly or explicitly – of the institutes where the work has been carried out.
- They secure the right to reproduce any material that has already been published or copyrighted elsewhere.
- They agree to the following license and copyright agreement.
Copyright
Authors who publish with International Journal of Advances in Intelligent Informatics agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.Â
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
Licensing for Data Publication
International Journal of Advances in Intelligent Informatics use a variety of waivers and licenses, that are specifically designed for and appropriate for the treatment of data:
Open Data Commons Attribution License, http://www.opendatacommons.org/licenses/by/1.0/ (default)
Creative Commons CC-Zero Waiver, http://creativecommons.org/publicdomain/zero/1.0/
Open Data Commons Public Domain Dedication and Licence, http://www.opendatacommons.org/licenses/pddl/1-0/
Other data publishing licenses may be allowed as exceptions (subject to approval by the editor on a case-by-case basis) and should be justified with a written statement from the author, which will be published with the article.
Open Data and Software Publishing and Sharing
The journal strives to maximize the replicability of the research published in it. Authors are thus required to share all data, code or protocols underlying the research reported in their articles. Exceptions are permitted but have to be justified in a written public statement accompanying the article.
Datasets and software should be deposited and permanently archived inappropriate, trusted, general, or domain-specific repositories (please consult http://service.re3data.org and/or software repositories such as GitHub, GitLab, Bioinformatics.org, or equivalent). The associated persistent identifiers (e.g. DOI, or others) of the dataset(s) must be included in the data or software resources section of the article. Reference(s) to datasets and software should also be included in the reference list of the article with DOIs (where available). Where no domain-specific data repository exists, authors should deposit their datasets in a general repository such as ZENODO, Dryad, Dataverse, or others.
Small data may also be published as data files or packages supplementary to a research article, however, the authors should prefer in all cases a deposition in data repositories.