Prototipe Penilaian Kinerja Tenaga Ahli PT. Inacon Luhur Pertiwi Dengan Pendekatan Adaptive Neuro Fuzzy Inference System (ANFIS)
Abstract
Inacon Luhur pertiwi PT. as a
management consulting firm in carrying out
its work on the project PNPM Urban with
contract number HK.02.03 / NMC / IBRD /
SATKER-PK / 007/2012 dated 10 May 2012.
By carrying out quantitative research
methods, using primary and secondary data
as samples. Primary data retrieved by
conducting an observation as an
observation instrument of experts
performance assessment. Secondary data
was collected by observing the data,
reading, studying and quoting from the book
of literature, as well as the resources that
are closely related to this study. The data
obtained will be used for purposes of
descriptive data analysis process by using
Adaptive Neuro Fuzzy Inference System
(ANFIS). ANFIS method is a method that
uses neural networks to implement fuzzy
inference system. Fuzzy inference system
used is the fuzzy inference system models
Tagaki-Sugeno-Kang (TSK) with
consideration of simplicity and easy
computation. The result of this research is
the prototipe of expert performance
evaluation which can be implemented at
Inacon Luhur Pertiwi PT.
Full Text:
PDFReferences
Dick Grote, (2002) Dick Grote, The Performance
Appraisal Question and Answer Book: A
Survival Guide for Managers.
http://www.slideshare.
net/ngbaodien/business-management-dickgrote-
the-performance-apprais (diakses 6 juni
pukul 15.00 wib)
Changjun Zhu, L. (2009) Changjun Zhu, L,
.PSO-base RBF neural Network Model for
Teaching Quality Evaluation. International
Conference on Control, Automation and
System Engineering, 47. 2009
Changjun Zhu, L. (2009) Changjun Zhu, L,
.PSO-base RBF neural Network Model for
Teaching Quality Evaluation. International
Conference on Control, Automation and
System Engineering, 47. 2009
Kusumadewi (2004) Kusumadewi, Sri. Purnomo,
Hari, Aplikasi Logika Fuzzy untuk pendukung
keputusan: graha Ilmu, Yogyakarta, 2004.
Marimin, (2010) Marimin, Nurul, Aplikasi
Pengambilan Keputusan Fuzzy Dalam
Manajemen Rantai Pasok : IPB Press, Bogor,
Peng Dong, F. D. (2009) Peng Dong, F. D,
.Evaluation for Teaching Quality Based on
Fuzzy Neural network. International
Workshop on Eucation Technology and
Computer Science, 112. 2009
Kusumadewi (2002) Kusumadewi, Sri, Analisis
dan Desain Sistem Fuzzy Menggunakan
Fuzzy Toolbox Matlab. Yogyakarta: Graha
Ilmu, 2002.
Kusumadewi (2010) Kusumadewi, Sri. Purnomo,
Hari., Aplikasi Logika Fuzzy untuk
pendukung keputusan, Edisi 2: graha Ilmu,
Yogyakarta, 2010.
Kusumadewi (2010) Kusumadewi, Sri. Hartati, S.,
Neuro - Fuzzy : Integrasi sistem fuzzy dan
jaringan syaraf: graha Ilmu, Yogyakarta,
Prabowo, (2009) Prabowo, Rahmadya Penerapan
soft computing dengan matlab: Rekayasa
Sains, Bandung, 2009.
Alvino, (2012) Alvino, Penerapan Adaptive Neuro
Fuzzy Inference System Untuk Evaluasi Nilai
Ujian Nasional Calon Siswa Baru SMK :
Studi Kasus SMK Negeri 2 Kota Tangerang
Selatan, 2012
DOI: https://doi.org/10.37012/jtik.v5i1.225
Refbacks
- There are currently no refbacks.
Copyright (c) 2020 Handa Gustiawan
This work is licensed under a Creative Commons Attribution 4.0 International License.
Address:
Universitas Mohammad Husni Thamrin
Jl. Raya Pd. Gede No.23-25, RT.2/RW.1, Dukuh, Kec. Kramat jati, Kota Jakarta Timur, Daerah Khusus Ibukota Jakarta 13550
Jurnal Teknologi Informatika & Komputer Mohammad Husni Thamrin is licensed under a Creative Commons Attribution 4.0 International License.