Aplikasi Penjadwalan Berbasis Heuristik untuk Peserta Pelatihan dengan Waktu dan Materi yang Berbeda-Beda (Heuristic-based Scheduling Application for Trainees with Different Timetables and Courses Material)

Main Article Content

Yustina Sri Suharini

Abstract

Abstrak

 

Sebagian besar lembaga pelatihan atau balai latihan kerja menggunakan penjadwalan dengan model batch, yang artinya sebuah jadwal digunakan bersama-sama untuk sekelompok orang, tanpa melihat karakteristik masing-masing peserta pelatihan atau ketersediaan waktu mereka. Namun penjadwalan model batch seperti itu belum tentu efektif untuk setiap orang dan belum sesuai dengan prinsip student center learning. Tulisan ini menawarkan alternatif solusi bagi lembaga pelatihan atau balai latihan kerja yang memerlukan penjadwalan dengan keragaman materi pelatihan dan ketersediaan waktu setiap peserta yang berbeda-beda. Solusi berupa pembuatan perangkat lunak aplikasi penjadwalan dengan arsitektur model-view-controller. Perangkat lunak yang dibuat mampu menjadwalkan lebih dari 300 peserta pelatihan dengan jumlah instruktur lebih dari 14 orang dan materi pelatihan berjumlah lebih dari 18 macam dengan tingkat kedalaman yang beragam.

Kata Kunci : penjadwalan pelatihan, slot waktu dan materi berbeda-beda 

 

Abstract

 

It is common for training institutions or vocational training centers using batch scheduling model, which means that a timetable be used together for a group of people, regardless of their individual needs or their time availabilities. Scheduling in batch model like that was not necessarily effective for every class member and not in accordance with the principle of student center learning. This paper offers an alternative scheduling solution for training institutions or vocational training centers that each participant has special needs in timetable, course interest, and course level. Our solution was implemented by model-view-controller architecture. The software could be used to schedule of more than 300 trainees with more than 14 instructors and more than 18 kinds of training materials.    

Keyword : training scheduling, different timetables and course material 

 

Article Details

Section
Articles

References

[ 1 ] BaykasoÄŸlu, Adil; Hamzadayi, Alper; Köse, Simge Yelkenci, 2014, “Testing the performance of teaching-learning based optimization (TLBO) algorithm on combinatorial problemsâ€, Journal Information Sciences Volume 276 Issue C, Pages 204-218.

[ 2 ] Lin, Tsung-Lieh; Horng, Shi-Jinn; Kao, Tzong-Wann; Chen, Yuan-Hsin; Run, Ray-Shine; Lai, Jui-Lin; Kuo, I-Hong; 2010, “An Efficient Job-Shop Scheduling Algorithm Based On Particle Swarm Optimizationâ€, Journal Expert Systems with Applications, Volume 37 Issue 3, March, 2010 Pages 2629-2636.

[ 3 ] Kader, Rehab F. Abdel; “Particle Swarm Optimization for Constrained Instruction Schedulingâ€, Hindawi Publishing Corporation, VLSI Design Volume 2008.

[ 4 ] Tavares, R.F.; Filho, M. Godinho; 2013, “Literature Review Regarding Ant Colony Optimization Applied To Scheduling Problems: Guidelines For Implementation And Directions For Future Researchâ€, Journal Engineering Applications of Artificial Intelligence, Volume 26 Issue 1, Pages 150-161.

[ 5 ] Rossi, Andrea; Lanzetta, Michele; 2014, “Native Metaheuristics for Non-Permutation Flowshop Schedulingâ€, Journal of Intelligent Manufacturing, Springer-Verlag Volume 25 Issue 6, Pages 1221-1233.

[ 6 ] Banharnsakun, Anan; Sirinaovakul, Booncharoen; Achalakul, Tiranee; 2012, “Job Shop Scheduling with the Best-so-far ABCâ€, Journal Engineering Applications of Artificial Intelligence, Volume 25 Issue 3, April, 2012, Pages 583-593.

[ 7 ] Prakash, Shiv; Vidyarthi, Deo Prakash; 2014, “A Hybrid GABFO Scheduling for Optimal Makespan in Computational Gridâ€, Journal International Journal of Applied Evolutionary Computation IGI Publishing Hershey Volume 5 Issue 3, July 2014, Pages 57-83.

[ 8 ] Chen, Chun-Lung; Huang, Shin-Ying; Tzeng, Yeu-Ruey; Chen, Chuen-Lung; 2014, “A Revised Discrete Particle Swarm Optimization Algorithm for Permutation Flow-Shop Scheduling Problemâ€, Journal Soft Computing - A Fusion of Foundations, Methodologies and Applications, Springer Volume 18 Issue 11, November 2014, Pages 2271-2282.

[ 9 ] Ergen, Sinem Coleri; Varaiya, Pravin; 2010, “TDMA Scheduling Algorithms for Wireless Sensor Networkâ€, Springer Wireless Network 16 page 985-997.

[ 10 ] Liu, Ke; Chen, jinjun; Jin, Hai; Yang, Yun; “A Min-Min Average Algorithm for Scheduling Transaction-Intensive Grid Workflowsâ€, Proc. 7th Australasian Symposium on Grid Computing and e-Research (AusGrid 2009), Wellington, New Zealand, 2009.

[ 11 ] Park, Taeju; Kim, Soontae; “Dynamic Scheduling Algorithm and Its Schedulability Analysis for Certifiable Dual-Criticality Systemsâ€, EMSOFT’11, October 9–14, 2011, Taipei, Taiwan, 2011.

[ 12 ] Huang, Po-Kai; Lin, Xiaojun; Chun, Chih; 2013, “A Low-Complexity Congestion Control And Scheduling Algorithm For Multihop Wireless Networks With Order-Optimal Per-Flow Delayâ€, IEEE / ACM Transactions on Networking, Vol. 21, No. 2, Page 1846-1859.

[ 13 ] Gupta, Abhinav; Lin, Xiaojun; Srikant, R.; 2009, “Low Complexity Distributed Scheduling Algorithms for Wireless Networksâ€, IEEE / ACM Transaction on Networking Vol 17 No. 6.

[ 14 ] Lerma, Miguel A., 2005, Mathematical Foundation of Computer Science, Set Theory, Chapter 2: “Set, Function, Relationâ€, (Online), (http://www.math.northwestern.edu/~mlerma/courses/cs310-05s/notes/dm-sets.pdf diakses Desember 2016)

[ 15 ] Partee, Barbara H., Meulen, Alice Ter, and Wall, Robert. 1990. Mathematical Methods in Linguistics, Dordrecht: Kluwer

[ 16 ] Ling 310, adapted from UMass Ling 409, Partee lecture notes March 1, 2006, page 1-10 (online) http://people.umass.edu/partee/NZ_2006/Set%20Theory%20Basics.pdf (diakses Desember 2016)