Penerapan Case Based Reasoning Dalam Memprediksi Masa Tunggu Kerja Calon Alumni
DOI:
https://doi.org/10.30865/klik.v3i6.849Keywords:
Case Base Reasoning; K-Neareast Neigbor; AlumniAbstract
Alumni are assets for an educational institution, can illustrate how the vision and mission of the alumni home institution are achieved. Educational institutions need to track their graduates, this is done as a source of information and to find out the absorption, process, and position of graduates in the world of work and assist government programs in mapping the needs of the world of work with competencies obtained from universities. In addition, to increase the accreditation of a university, college or department. So important is alumni data in the world of work, there is a need for a system to predict the waiting points for alumni to work. The purpose of this study is to apply the Case Based Reasoning in predicting the waiting period of prospective alumni at Baturaja University using the K-Neareast Neigbor algorithm. Reasoning is based on 14 attributes with 10 rule bases. Based on the representation of the new case, the similarity value of the old case with the new case is 0.64
Downloads
References
R. Akbar dan M. Mukhtar, “Perancangan E-Tracer Study berbasis Sistem Cerdas,” J. Sisfokom (Sistem Inf. dan Komputer), vol. 9, no. 1, hal. 8–12, 2020, doi: 10.32736/sisfokom.v9i1.631.
M. I. Juwita, S. A. Wicaksono, dan N. Y. Setiawan, “Pengembangan Sistem Informasi Tracer Study Alumni Berbasis Web Menggunakan Metode RUP ( Studi Kasus?: SMA Suluh Jakarta Selatan ),” J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 3, no. 6, hal. 5703–5710, 2019.
J. Antares, Z. Gustiana, dan I. Rusydi, “Rancangan Sistem Informasi Dalam Pengembangan Model Tracer Study Di Universitas Dharmawangsa,” JURTEKSI (Jurnal Teknol. dan Sist. Informasi), vol. 7, no. 2, hal. 151–158, 2021, doi: 10.33330/jurteksi.v7i2.1002.
H. Haerudin, A. Syaripudin, D. A. Punkastyo, F. Nurlaila, dan J. Riyanto, “Sistem Tracer Study dan Monitoring Alumni Universitas Pamulang,” J. Inform. Univ. Pamulang, vol. 5, no. 4, hal. 498–505, 2020.
R. Rachmadiansyah, N. D. Rumlaklak, dan A. Y. Mauko, “Prediksi Masa Tunggu Kerja Alumni Menggunakan Naïve Bayes Classifier Pada Program Studi Ilmu Komputer Universitas Nusa Cendana,” J. Komput. dan Inform., vol. 10, no. 2, hal. 143–150, 2022, doi: 10.35508/jicon.v10i2.7426.
R. Jhordi, I. Bagus, G. Dwidasmara, dan I. W. Supriana, “Case Based Reasoning Untuk Diagnosa Kecanduan Terhadap Game Berbasis Web,” vol. 1, no. November, 2022.
N. P. P. Wardhana dan I. W. Supriana, “Pemanfaatan Case Based Reasoning sebagai Rekomendasi Produk Kamera,” JNATIA, vol. 1, no. November, hal. 569–574, 2022.
Abdul Rahman, Destiarini, dan J. Kuswanto, “Fuzzy Logic Recommended Student Learning Levels,” J. Inform. Polinema, vol. 7, no. 2, hal. 51–56, 2021, doi: 10.33795/jip.v7i2.531.
M. Ikhsan, Armansyah, dan R. S. Habibi, “Penerapan sistem cerdas berbasis case base based reasoning (cbr) dan metode k-nearest neighbor untuk identifikasi masalah data center,” vol. 6, no. 1, hal. 47–55, 2023.
Maukar, E. Sutanty, dan D. K. Astuti, “Kombinasi Case-Based Reasoning dan Rule-Based Reasoning Pada Sistem Pakar Deteksi Awal Covid-19,” Decod. J. Pendidik. Teknol. Inf., vol. 3, no. 1, hal. 94–105, 2023.
J. Kuswanto, A. F. Wulandari, I. Yani, S. Rizky, N. Samudra, dan J. Dapiokta, “Penerapan Metode Weighted Product ( WP ) untuk Menentukan Penerimaan BLT di Desa Rawasari,” vol. 3, no. 5, hal. 503–508, 2023.
Y. V. Via, F. T. Anggraeny, dan R. A. Jorgie, “Penerapan Algoritma Case Based Reasoning Dan K-Nearest Neighbor Untuk Diagnosa Penyakit Ayam,” Pros. Semin. Nas. Inform. Bela Negara, vol. 2, hal. 192–195, 2021, doi: 10.33005/santika.v2i0.140.
M. W. N. Fajar, “Sistem Pakar Diagnosa Penyakit Anemia Pada Ibu Hamil Dengan Metode Case Based Reasoning,” 2020.
L. Try Pangestu, H. Mubarok, dan N. Ika Kurniati, “Case-Based Reasoning Diagnosa Penyakit Jantung Korespondensi,” Sci. Artic. Informatics Students, vol. 1, no. 2, hal. 159–166, 2018.
Amriana, D. W. Nugraha, dan Rahmatanti, “Sistem Pakar Diagnosa Penyakit Lambung Menggunakan Metode Case Based Reasoning Berbasis Web,” CESS (Journal Comput. Eng. Syst. Sci., vol. 5, no. 1, hal. 114–123, 2020.
T. H. Pudjiantoro, U. Jenderal, dan A. Yani, “Penentuan Penanganan Kasus Terhadap Penyakit Berdasarkan Gejala Menggunakan Case Base Reasoning dan Algoritma Nearest Neighbor (Studi kasus?: Klinik Citra Medika Cianjur),” no. February, hal. 162–167, 2018.
H. Sulistiani, I. Darwanto, dan I. Ahmad, “Penerapan Metode Case Based Reasoning dan K-Nearest Neighbor untuk Diagnosa Penyakit dan Hama pada Tanaman Karet,” J. Edukasi dan Penelit. Inform., vol. 6, no. 1, hal. 23, 2020, doi: 10.26418/jp.v6i1.37256.
A. Rahman and U. Budiyanto, “Case based reasoning adaptive e-learning system based on visual-auditory-kinesthetic learning styles,” in International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), 2019, pp. 177–182. doi: 10.23919/EECSI48112.2019.8976921.
A. Rahman, R. A. Mutiarawan, A. Darmawan, Y. Rianto, and M. Syafrullah, “Prediction of students academic success using case based reasoning,” in International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), 2019, pp. 171–176. doi: 10.23919/EECSI48112.2019.8977104.
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Penerapan Case Based Reasoning Dalam Memprediksi Masa Tunggu Kerja Calon Alumni
ARTICLE HISTORY
Issue
Section
Copyright (c) 2023 Abdul Rahman, Pujianto, Joko Kuswanto

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- 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 (Refer to The Effect of Open Access).