PERAN PEJABAT PEMBUAT KOMITMEN SEBAGAI PENGENDALI FUNGSI DALAM PEMBANGUNAN LANJUTAN LABORATORIUM B2P2TOOT TAWANGMANGU

Yola Vegita, Cahyo Prianto, Syafrial Fachri Pane

Abstract


This study investigates the general form of the determinant of negative integer powers of a special class of centrosymmetric matrices of even order. For an even positive integer and a positive integer , let denote such a matrix, and consider the matrix obtained by raising to the power . To determine , we first conjecture the general form of the inverse matrix by observing the patterns in the explicit inverses , and . The conjectured form is then verified by showing that and . The resulting inverse is used to construct the matrices , and ; from these cases we infer the general structure of . The validity of this general form is established using mathematical induction. Once the matrix has been obtained, an explicit closed-form expression for is derived via the cofactor expansion method. Finally, a numerical example is presented to illustrate the application of the determinant formula.


Keywords


literacy; local wisdom; natural and social science; wordwall

Full Text:

PDF

References


T. Tania, D. Haryadi, W. W. Mirza, and A. M. Khairusy, “Improving employe performance with structural empowerment and transformational leadership through job satisfaction , organizational citizenship behavior and interpersonal trust (study at PT . BPRS Cilegon Mandiri),†Am. J. Humanit. Soc. Sci. Res., vol. 5, no. 11, pp. 91–102, 2021.

M. T. Lesmana, “Pengaruh Kompetensi Dan Disiplin Kerja Terhadap Kinerja Pegawai,†vol. 6681, pp. 665–670, 2017.

Kepala Badan kepegawaian Negara, “Peraturan Kepala Badan Kepegawaian Negara Nomor 1 Tahun 2013 Tentang Ketentuan Pelaksanaan Peraturan Pemerintah Nomor 45 Tahun 2011 Tentang Penilaian Prestasi Kerja Pegawai Negeri Sipil,†pp. 1–135, 2013, [Online]. Available: https://www.bkn.go.id/wp-content/uploads/2015/02/Perka-Bkn-Nomor-1-Tahun-2013-Ketentuan-Pelaksanaan-Pp-Nomor-46-Tahun-2011-Tentang-Penilaian-Prestasi-Kerja-Pns.pdf

P. W. Kastawan, D. M. Wiharta, and M. Sudarma, “Implementasi Algoritma C5.0 pada Penilaian Kinerja Pegawai Negeri Sipil,†Maj. Ilm. Teknol. Elektro, vol. 17, no. 3, p. 371, 2018, doi: 10.24843/mite.2018.v17i03.p11.

D. Suer, “Analisa Penentuan Karyawan Terbaik Menggunakan Data Mining Dengan Metode Algoritma C4.5 Di Pt.Shei Tai Industrial,†World Dev., vol. 1, no. 1, pp. 1–15, 2018, [Online]. Available: http://www.fao.org/3/I8739EN/i8739en.pdf%0Ahttp://dx.doi.org/10.1016/j.adolescence.2017.01.003%0Ahttp://dx.doi.org/10.1016/j.childyouth.2011.10.007%0Ahttps://www.tandfonline.com/doi/full/10.1080/23288604.2016.1224023%0Ahttp://pjx.sagepub.com/lookup/doi/10

P. Mishra, A. Biancolillo, J. M. Roger, F. Marini, and N. Rutledge, “New data preprocessing trends based on ensemble of multiple preprocessing techniques,†Trends Anal. Chem., p. 116045, 2020, doi: 10.1016/j.trac.2020.116045.

M. K. Dahouda and I. Joe, “A Deep-Learned Embedding Technique for Categorical Features Encoding,†IEEE Access, vol. 9, pp. 114381–114391, 2021, doi: 10.1109/Access.2021.3104357.

A. Elhassan, S. M. Abu-soud, F. Alghanim, and W. Salameh, “ILA4 : Overcoming missing values in machine learning datasets – An inductive learning approach,†J. King Saud Univ. - Comput. Inf. Sci., vol. 34, no. 7, pp. 4284–4295, 2022, doi: 10.1016/j.jksuci.2021.02.011.

K. Surabaya et al., “Antara Kejadian Demam Berdarah Dengue Dengan Kepadatan Penduduk Di Kota Surabaya Pada Tahun 2012 - 2014 Pearson Correlation Analysis to Determine The Relationship Between City Population Density with Incident Dengue Fever of Surabaya in The Year 2012-2014 Widayanti Ratna Safitri Program Studi S1 Ilmu Kesehatan Masyarakat Universitas Airlangga Surabaya,†2014.

H. Kaur, H. S. Pannu, and A. K. Malhi, “A Systematic Review on Imbalanced Data Challenges in Machine Learning : Applications and Solutions,†vol. 52, no. 4, 2019.

S. Widaningsih, “Perbandingan Metode Data Mining Untuk Prediksi Nilai Dan Waktu Kelulusan Mahasiswa Prodi Teknik Informatika Dengan Algoritma C4,5, Naïve Bayes, Knn Dan Svm,†J. Tekno Insentif, vol. 13, no. 1, pp. 16–25, 2019, doi: 10.36787/jti.v13i1.78.

A. Y. Simanjuntak, I. S. E. S. Simatupang, and A. Anita, “Implementasi Data Mining Menggunakan Metode NaãÂVe Bayes Classifier Untuk Data Kenaikan Pangkat Dinas Ketenagakerjaan Kota Medan,†J. Sci. Soc. Res., vol. 5, no. 1, p. 85, 2022, doi: 10.54314/jssr.v5i1.804.

Afdhaluzzikri, “Analisa Kinerja Metode Naïve Bayes Dengan Pembobotan Data,†2021.

F. Elfaladonna and A. Rahmadani, “Analisa Metode Classification-Decission Tree Dan Algoritma C.45 Untuk Memprediksi Penyakit Diabetes Dengan Menggunakan Aplikasi Rapid Miner,†SINTECH (Science Inf. Technol. J., vol. 2, no. 1, pp. 10–17, 2019, doi: 10.31598/sintechjournal.v2i1.293.

F. Marisa, A. L. Maukar, I. Khalim, and M. R. Putra, “Jurnal Teknologi dan Manajemen Informatika Analisa Prediksi Varietas Buah Salak yang Sesuai dengan Lahan Daerah,†vol. 8, no. 1, pp. 20–25, 2022.

Binus, “Clustering.†[Online]. Available: https://socs.binus.ac.id/2017/03/09/clustering/

M. Azhari, Z. Situmorang, and R. Rosnelly, “Perbandingan Akurasi, Recall, dan Presisi Klasifikasi pada Algoritma C4.5, Random Forest, SVM dan Naive Bayes,†J. Media Inform. Budidarma, vol. 5, no. 2, p. 640, 2021, doi: 10.30865/mib.v5i2.2937.

Presiden Republik Indonesia, “Peraturan Pemerintah Republik Indonesia Nomor 30 Tahun 2019 Tentang Penilaian Kinerja Pegawai Negeri Sipil,†Kementeri. Sekr. Negara Republik Indones., pp. 1–52, 2019.

D. Alita, A. D. Putra, and D. Darwis, “Analysis of Classic assumption test and multiple linear regression coefficient test for employee structural office recommendation,†vol. 15, no. 3, pp. 295–306, 2021.

S. J. Kamatkar, A. Tayade, A. Viloria, and A. Hernández-Chacín, “Application of classification technique of data mining for employee management system,†Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 10943 LNCS, pp. 434–444, 2018, doi: 10.1007/978-3-319-93803-5_41.

C. Elfira, A. Pah, and I. Journal, “Decision Support Model for Employee Recruitment Using Data Mining Classificationâ€.




DOI: https://doi.org/10.26877/jiu.v8i2.13205

Refbacks

  • There are currently no refbacks.


Copyright (c) 2023 Cahyo Prianto