Determination Potential Experts by Application The Apriori Algorithm and the K-Means Algorithm

(1) * Rini Sovia Mail (Department Informatics Engineering , Faculty of Computer Science, University Putra Indonesia "YPTK" Padang, Indonesia, Indonesia)
(2) Sarjon Defit Mail (Department Informatics Engineering , Faculty of Computer Science, University Putra Indonesia "YPTK" Padang, Indonesia, Indonesia)
(3) Noor Fatimah Mail (Universiti Teknikal Malaysia Melaka, Malaysia)
*corresponding author

Abstract


Experts are people who have special expertise who provide services based on their expertise. The company has experts in handling projects that will be carried out for the progress of the company. The importance of the quality of experts in the company can improve the quality of human resources. The Apriori algorithm is a data mining method that has the aim of looking for association patterns based on the project being carried out so that they can be identified by experts who are often used in handling projects. Furthermore, a data mining approach is needed to classify experts with the K-means algorithm used. This study combines the Apriori and K-means algorithms, by grouping experts based on the handling of the project they are working on.


Keywords


Prediction, Experts, Projects, Apriori, K-Means

   

DOI

https://doi.org/10.29099/ijair.v6i1.219
      

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References


L. Muflikhah, WL Yunita, and MT Furqon, "Prediction of Student Course Values Using the K-Apriori Algorithm," Sisfo, vol. 06, no. 02, pp. 157–172, 2017, DOI: 10.24089 / j.sisfo.2017.01.001.

S. Setiawan, "Cluster Analysis Using the K-Means Algorithm to Determine the Ability of Employees in It at Cv. Roxed Ltd, †J. Pelita Inform. , vol. 18, pp. 80–86, 2019.

J. Han and M. Kamber, Data Mining Concepts And Techniques.

R. Sovia, E. Praja, W. Mandala, and S. Mardhiah, "K-Means Algorithm in Selection of Outstanding Students and SAW Method for Prediction," vol. 6, no. 2, pp. 181–187, 2020.

Aprilla Dennis, "Learning Data Mining with Rapid Miner," Innov. Knowl. Manag. Bus. Glob. Theory Pract. Vols 1 2, vol. 5, no. 4, pp. 1–5, 2013, DOI: 10.1007 / s13398-014-0173-7.2.

A. Salam, J. Zeniarja, W. Wicaksono, and L. Kharisma, "Search for Association Patterns for Organizing Goods Using Comparison of Apriori Algorithms and Fp-Growth (Case Study of Pemalang Epo Store Distro)," Dinamik, vol. 23, no. 2, pp. 57–65, 2019, DOI: 10.35315 / dynamic.v23i2.7178.

I. Vhallah, S. Sumijan, and J. Santony, "Grouping Potential Students to Drop Out Using the K-Means Clustering Method," J. RESTI (System Engineering and Information Technology), vol. 2, no. 2, pp. 572–577, 2018, DOI: 10.29207 / rest.v2i2.308.

D. Sepri and M. Afdal, "Analysis and Comparison of Apriori and Fp-Growth Algorithm Methods for Finding Strategic Regional Patterns Introduction to Case Study Campuses at Stkip Adzkia Padang," J. Sist. Inf. Kaputama, vol. 1, no. 1, 2017.

E. Elisa, "Market Basket Analysis at Ayu Mini Market with Apriori Algorithm," J. RESTI (Engineering Systems and Information Technology), vol. 2, no. 2, pp. 472–478, 2018, DOI: 10.29207 / resti.v2i2.280.

C. With and M. Algorithms, "Development of Profit Rate Determination Applications in E-," vol. 2016, no. Sentika, pp. 18–19, 2016.

RK Dinata, H. Novriando, N. Hasdyna, and S. Retno, "Attribute Reduction Using Information Gain for Optimization of K-Means Algorithm Clusters," J. Education and Researchers. Inform. , vol. 6, no. 1, p. 48, 2020, DOI: 10.26418 / jp.v6i1.37606.

M. Mardalius, "Utilization of Rapid Miner Studio 8.2 for Grouping Accessories Sales Data Using the K-Means Algorithm," Jurteksi, vol. 4, no. 2, pp. 123–132, 2018, DOI: 10.33330 / jurteksi.v4i2.36.

H. Priyatman, F. Sajid, and D. Haldivany, "Clustering Using the K-Means Clustering Algorithm to Predict Student Graduation Time," J. Education and Researchers. Inform. , vol. 5, no. 1, p. 62, 2019, DOI: 10.26418 / jp.v5i1.29611.

AZY Ridho Ananda, "JOURNAL OF RESTI Determination of K-means Initial Centroids in the Evaluation Data Clustering Process," J. RESTI (Engineering Systems and Information Technology), vol. 1, no. 10, pp. 544–550, 2021.

L. Hakim and H. Seruni, "Indications of Irregularities in XYZ University Academic Financial Statements Using the Greedy and K-Means Algorithm," J. RESTI (System Engineering and Information Technology), vol. 2, no. 1, pp. 301–306, 2018, doi: 10.29207 / resti.v2i1.261.




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