IMPLEMENTATION OF EMPLOYEE DISCIPLINE CLUSTERING AT GOTTING SIDODADI VILLAGE OFFICE BANDAR PASIR MANDOGE USING K-MEANS ALGORITHM

  • Dewi Murni Sistem Informasi, Sekolah Tinggi Manajemen Informatika dan Komputer Royal Kisaran, Indonesia
  • Bachtiar Efendi Sistem Informasi, Sekolah Tinggi Manajemen Informatika dan Komputer Royal Kisaran, Indonesia
  • Nurul Rahmadani Sistem Komputer, Sekolah Tinggi Manajemen Informatika dan Komputer Royal Kisaran, Indonesia
Keywords: Attendance, Employee Discipline, K-Means Clustering

Abstract

Discipline is the key to the success of an organization in achieving its goals, because discipline is an operative function of human resource management which is very important and will create quality employees. Employee discipline can be seen through employee attendance. The importance of evaluating employee discipline levels to improve services to the community and make it easier for leaders to find out the level of discipline of Gotting Sidodadi Village office employees, Bandar Pasir Mandoge currently has not grouped the level of employee discipline because there is no system that can assist in the process. The grouping of employees' discipline levels is used the K-Means Clustering method in this study. The application of the K-means Clustering method is implemented in an application made with 3 clusters of 14 data samples, and not absent from home. The data used is attendance data for 14 employees from 2018 to 2021. The results of this study are that the k-means algorithm is able to classify the data with the highest level of discipline. medium and low with the existence of this application system, it is hoped that the leadership can easily find out the level of discipline of employees at the Gotting Sidodadi Village Office so that they can provide bonuses for employees with high levels of discipline, and sanctions for employees with low levels of discipline.

Downloads

Download data is not yet available.

References

I. Mardeli and Y. Yansahrita, “Pengaruh Kedisiplinan Terhadap Prestasi Kerja Pegawai Pada Kantor Kecamatan Belitang Madang Raya Oku Timur,” J. Aktual, vol. 17, no. 1, p. 41, 2019, doi: 10.47232/aktual.v17i1.32.

Suanda, “Sistem informasi absensi pegawai berbasis web pada kantor kelurahan sako palembang,” J. Sigmata, vol. 7, no. April, 2019.

E. Nopitasari and H. Krisnandy, “PENGARUH GAYA KEPEMIMPINAN DEMOKRATIS, MOTIVASI INTRINSIK DAN DISIPLIN KERJA TERHADAP KINERJA KARYAWAN PT PANGANSARI UTAMA FOOD INDUSTRY,” Oikonomia J. Manaj., vol. 14, no. 1, 2019, doi: 10.47313/oikonomia.v14i1.511.

D. M. C. Hermanto, “Analisis Algoritma Clustering,” J. Media Apl., vol. 9, no. 2, 2017.

S. Regina, E. Sutinah, and N. Agustina, “Clustering Kualitas Kinerja Karyawan Pada Perusahaan Bahan Kimia Menggunakan Algoritma K-Means,” vol. 5, no. April, pp. 573–582, 2021, doi: 10.30865/mib.v5i2.2909.

G. Gustientiedina, M. H. Adiya, and Y. Desnelita, “Penerapan Algoritma K-Means Untuk Clustering Data Obat-Obatan,” J. Nas. Teknol. dan Sist. Inf., vol. 5, no. 1, 2019, doi: 10.25077/teknosi.v5i1.2019.17-24.

I. Sumadikarta and E. Abeiza, “PENERAPAN ALGORITMA K-MEANS PADA DATA MINING UNTUK MEMILIH PRODUK DAN PELANGGAN POTENSIAL ( Studi Kasus : PT Mega Arvia Utama ),” pp. 12–23, 2014.

N. Rahmadani, E. Rahayu, and ..., “K-Means Clustering Areas Prone To Traffic Accidents in Asahan Regency,” JITK (Jurnal Ilmu Pengetah. dan Teknol. Komputer), vol. 6, no. 2, pp. 181–186, 2021, doi: 10.33480/jitk.v6i2.1519.K-MEANS.

P. Purwadi, P. S. Ramadhan, and N. Safitri, “Penerapan Data Mining Untuk Mengestimasi Laju Pertumbuhan Penduduk Menggunakan Metode Regresi Linier Berganda Pada BPS Deli Serdang,” J. SAINTIKOM (Jurnal Sains Manaj. Inform. dan Komputer), vol. 18, no. 1, 2019, doi: 10.53513/jis.v18i1.104.

A. W. Wijayanti, “Analisis Hasil Implementasi Data Mining Menggunakan Algoritma Apriori pada Apotek,” J. Edukasi dan Penelit. Inform., vol. 3, no. 1, 2017, doi: 10.26418/jp.v3i1.19534.

N. Rahmadani and E. Kurniawan, “Implementasi Metode K-Means Clustering Tunggakan Rekening Listrik pada PT. PLN (Persero) Gardu Induk Kisaran,” J-SISKO TECH (Jurnal Teknol. Sist. Inf. dan Sist. Komput. TGD), vol. 3, no. 1, p. 103, 2020, doi: 10.53513/jsk.v3i1.201.

K. Produk and P. Usaha, “MANAJEMEN INFORMATION SYSTEM OF HALAL CERTIFICATION FACILTIES , BRAND RIGHTS , PRODUK PACKAGING FOR BUSSINESS PEOPLE UMKM,” vol. 1, no. 1, 2020.

M. M. Gultom and U. M. Surakarta, “SISTEM INFORMASI PENJUALAN MATERIAL BANGUNAN PADA TOKO BANGUNAN BERKAH,” vol. 1, no. 2, pp. 79–86, 2020.

R. P. Mahardikawati and K. Boyolali, “INFORMATION SYSTEM OF SMALL AND MEDIUM ENTERPRISES GOVERNMENT OF BOYOLALI WEBISTE BASED,” vol. 1, no. 2, pp. 53–60, 2020.

A. Ahmad and Y. I. Kurniawan, “SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN PEGAWAI TERBAIK MENGGUNAKAN SIMPLE ADDITIVE WEIGHTING DECISION SUPPORT SYSTEM FOR BEST EMPLOYEE SELECTION USING,” vol. 1, no. 2, pp. 101–108, 2020.

Published
2022-04-25
How to Cite
[1]
D. Murni, B. Efendi, and N. Rahmadani, “IMPLEMENTATION OF EMPLOYEE DISCIPLINE CLUSTERING AT GOTTING SIDODADI VILLAGE OFFICE BANDAR PASIR MANDOGE USING K-MEANS ALGORITHM”, J. Tek. Inform. (JUTIF), vol. 3, no. 2, pp. 295-304, Apr. 2022.