Penerapan Metode PIPRECIA dan Multi-Attribute Utility Theory dalam Pemilihan Reporter Terbaik

Temi Ardiansah; Ade Dwi Putra

doi:10.58602/jima-ilkom.v3i2.31

Temi Ardiansah Universitas Teknokrat Indonesia
Ade Dwi Putra Universitas Teknokrat Indonesia

DOI: https://doi.org/10.58602/jima-ilkom.v3i2.31

Keywords: MAUT, Election, PIPRECIA, Reporter, Best

Abstract

In the media industry, reporters play an important role in conveying accurate, fast, and credible information to the public. One of the main problems is subjectivity in evaluation, where personal preferences or the evaluator's bias can affect the final result. In addition, the scoring criteria used are sometimes not uniform or clear, resulting in a difference in perception of what actually constitutes the best reporter's measure. The purpose of applying the PIPRECIA and MAUT methods in selecting the best reporter is to provide an objective and measurable assessment of the reporter's performance based on several relevant criteria. The results of Ferdi's ranking won 1st place with a final score of 0.4358, indicating that he has the best performance in the assessment based on the set criteria, namely the quality of coverage, communication skills, speed of news delivery, and excellent integrity. The results of this ranking provide a clear insight into the performance of each reporter based on the PIPRECIA and MAUT methods. These results can be used as a reference for further decision-making regarding recognition or awards to reporters.

Downloads

Download data is not yet available.

References

D. Pramana, “Pola Komunikasi Reporter Berita Dalam Proses Produksi Liputan Televisi (Studi Kualitatif Reporter TVRI Jawa Timur).” Universitas 17 Agustus 1945 Surabaya, 2024.

M. W. Arshad and S. Setiawansyah, “Combination of Rank Sum and Multi Attribute Utility Theory in Determining the Best Receptionist Performance,” KLIK Kaji. Ilm. Inform. dan Komput., vol. 4, no. 5, pp. 2549–2558, 2024, doi: 10.30865/klik.v4i5.1791.

I. Oktaria, “Kombinasi Metode Multi-Attribute Utility Theory ( MAUT ) dan Rank Order Centroid ( ROC ) dalam Pemilihan Kegiatan Ekstrakulikuler,” J. Ilm. Inform. dan Ilmu Komput., vol. 2, no. 1, pp. 1–11, 2023.

V. R. Campos and D. J. S. Moreira, “Risk assessment with multi-attribute utility theory for building projects,” J. Build. Pathol. Rehabil., vol. 7, no. 1, p. 98, 2022.

F. El Khair, S. Defit, and Y. Yuhandri, “Sistem Keputusan dengan Metode Multi Attribute Utility Theory dalam Penilaian Kinerja Pegawai,” J. Inf. dan Teknol., pp. 215–220, 2021.

M. I. Fikri, E. Haerani, I. Afrianty, and S. Ramadhani, “Sistem Pendukung Keputusan Penilaian Kinerja Guru Menggunakan Metode Multi Attribute Utility Theory (MAUT),” JURIKOM (Jurnal Ris. Komputer), vol. 9, no. 5, pp. 1271–1280, 2022.

J. Rueda-Benavides, M. Khalafalla, M. Miller, and D. Gransberg, “Cross-asset prioritization model for transportation projects using multi-attribute utility theory: a case study,” Int. J. Constr. Manag., vol. 23, no. 16, pp. 2746–2755, 2023.

U. Akpan and R. Morimoto, “An application of Multi-Attribute Utility Theory (MAUT) to the prioritization of rural roads to improve rural accessibility in Nigeria,” Socioecon. Plann. Sci., vol. 82, p. 101256, 2022.

A. D. Wahyudi, “Penentuan Lokasi Gudang Baru Menggunakan TOPSIS dan Pembobotan PIPRECIA,” J. Inf. Technol. Softw. Eng. Comput. Sci., vol. 2, no. 1, pp. 22–30, 2024.

S. Sudha and N. Martin, “Comparative analysis of Plithogenic neutrosophic PIPRECIA over neutrosophic AHP in criteria ordering of logistics selection,” in AIP Conference Proceedings, 2023, vol. 2649, no. 1, p. 030014. doi: 10.1063/5.0147363.

S. Setiawansyah, “Kombinasi Pembobotan PIPRECIA-S dan Metode SAW dalam Pemilihan Ketua Organisasi Sekolah,” J. Ilm. Inform. dan Ilmu Komput., vol. 2, no. 1, pp. 32–40, 2023.

H. Sulistiani, Setiawansyah, P. Palupiningsih, F. Hamidy, P. L. Sari, and Y. Khairunnisa, “Employee Performance Evaluation Using Multi-Attribute Utility Theory (MAUT) with PIPRECIA-S Weighting: A Case Study in Education Institution,” in 2023 International Conference on Informatics, Multimedia, Cyber and Informations System (ICIMCIS), 2023, pp. 369–373. doi: 10.1109/ICIMCIS60089.2023.10349017.

S. Setiawansyah, S. H. Hadad, A. A. Aldino, P. Palupiningsih, G. Fitri Laxmi, and D. A. Megawaty, “Employing PIPRECIA-S weighting with MABAC: a strategy for identifying organizational leadership elections,” Bull. Electr. Eng. Informatics, vol. 13, no. 6, pp. 4273–4284, Dec. 2024, doi: 10.11591/eei.v13i6.7713.

N. T. L. Toruan, “Sistem Pendukung Keputusan Pemilihan Pembawa Acara Berita Terbaik Menerapkan Metode OCRA,” Bull. Comput. Sci. Res., vol. 1, no. 3, pp. 71–78, 2021.

P. Adytia, M. Fahmi, and R. Andrea, “Analisis Dalam Pendukung Keputusan Seleksi Reporter dengan Menerapkan Metode EDAS dan Pembobotan ROC,” J. MEDIA Inform. BUDIDARMA, vol. 7, no. 2, pp. 809–818, 2023.

R. Y. Lubis, M. Syahril, and S. Sobirin, “Pemilihan Editor Berita Terbaik Menggunakan Metode Complex Proportional Assessment (COPRAS),” J. Cyber Tech, vol. 3, no. 4, pp. 738–747, 2020.