METODE BAYES DALAM EVALUASI KINERJA PENYULUH PERTANIAN

Dewi Suranti, Hari Aspriyono

Abstract


Performance is a very important factor in determining success in assessing work quality. Good performance is the hope of all parties in an institution, including agricultural institutions. The Sukaraja Agricultural Extension Service Technical Unit (UPT BPP) always supports to improve the performance of extension workers in order to improve the quality of extension workers. Evaluation of broadcasting performance is carried out from the beginning of the activities carried out, starting from the preparation, implementation, evaluation and reporting. Evaluation of instructor performance at UPT BPP Sukaraja is carried out every three months and six months. So far, the evaluation is done manually, so it does not need to be done in a timely manner because of constrained inadequate labor. The method used in the evaluation study is the use of agricultural instructors using the Bayes method. The Bayes method is first performed by calculating the value of each criterion, total weighting, probability perriterian, calculating the total probability, calculating the threshold of each criterion and calculating the threshold value then comparing the total value with the threshold value of each criterion. The results of this method produce a good agriculture instructor ranking ranking, namely with initial Sdn with a total value of probability 31.38 and those requiring guidance are extension agents with Sjn and Dsm with a total probability of 24.13, and a total probability of 24.


Keywords


Bayes, Performance evaluation, Agricultural extensionist

Full Text:

PDF

References


Sapar, & Butami, L. (2017). Faktor-Faktor yang Mempengaruhi Kinerja Penyuluh Pertanian dalam Peningkatan Produktivitas Kakao Di Kota Palopo. Jurnal Ekonomi Pembangunan Vol. 03 No. 01 Februari 2017 ISSN 2339-1529 , 35-42.

Mustafa, M. S., Ramadhan, M. R., & Thenata, A. P. (2017). Implementasi Data Mining untuk Evaluasi Kinerja Akademik Mahasiswa Menggunakan Algoritma Naive Bayes Classifier. Citec Journal, Vol. 4, No. 2, Februari 2017 – April 2017 ISSN: 2460-4259 , 151-162.

Ari Jayanti, N. K. (2013). Implementasi Metode Bayes Pada Penilaian Kinerja Dosen. Eksplora Informatika Vol. 2, No. 2, Maret 2013 , 101-108.

Astiti, N. M. (2107). Sistem Pendukung Keputusan Pemberian Kredit Pada Lembaga Perkreditan desa Pejeng dengan Menggunakan Metode Bayes. Konferensi Nasional Sistem & Informatika (pp. 730-736). Bali: STMIK STIKOM.

Muliadi, Syarif, S., & Salim, A. (2019). Penerapan Algoritma Naive Bayes pada Penilaian Kinerja Pemerintah Desa dalam Pengelolaan Dana Desa. Jurnal Riset Informatika Vol. 1, No. 2 Maret 2019 , 71-80.

Herman, M. (2014, 7 13). A Multi-Criteria Decision Making Approach to Problem Solving. Brussel, Belgia.

Brans, J.-P., & Mareschal, B. (2016). PROMETHEE METHODS. In S. Greco, M. Ehrgott, & J. R. Figueira, Multiple Criteria Decision Analysis: State of the Art Surveys (pp. 163-195). New York: Springer.

Gunawan, & Astuti, S. (2013). Sistem Pendukung Keputusan pemilihan gadget Android menggunakan metode Promethee. Techno.Com , 12 (2), 104-116.

Pertanian, K. (2013, September 24). Peraturan Menteri Pertanian Nomor 91/Permentan/OT.140/9/2013 tentang Pedoman Evaluasi Kinerja Penyuluh Pertanian. Jakarta, DKI Jakarta, Indonesia. Retrieved from http://perundangan.pertanian.go.id/admin/file/Permentan%2091-2013%20Evaluasi%20Kinerja%20Penyuluh%20Pertanian.pdf




DOI: https://doi.org/10.30873/ji.v20i1.2027


 Jurnal Informatika is abstracting and indexing in the following databases:

 


JURNAL INFORMATIKA

 

Dikelola Oleh: Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM)

Diterbitkan Oleh: Institut Informatika dan Bisnis Darmajaya
Alamat: Jl. Z.A. Pagar Alam No. 93 Gedong Meneng, Bandar Lampung Lampung
Website: jurnal.darmajaya.ac.id

Email: lp4mjurin@gmail.com


View Jurnal Informatika StatCounter

Creative Commons License

Jurnal Informatika is licensed under a Creative Commons Attribution 4.0 International License.