Pengaruh Penerapan Sistem Digitalisasi, Efektivitas Pengendalian Internal, dan Pengungkapan Pengendalian Internal terhadap Nilai Perusahaan
Abstract
Variables that affect company valuation can be seen from the probability level (ROA/Return on Assets), the amount of earnings per share (EPS/Earnings Per Share), and the ratio of liabilities to equity (DER/Debt Equity Ratio). Based on the explanation of the theory and several previous studies, which explain that major changes in the era where digital technology is developing very widely, with the presence of technology creating opportunities in the economic sector that can affect the value of the company. This study aims to confirm that this statement is true that this variable is able to affect the value of the company's infrastructure or not. Processing data from the study used the SPSS version 25 application, with sampling using the purposive sampling method. The number of company samples taken consisted of 22 companies over a 3-year period, namely 2020-2022, and produced 66 samples. The results of this study indicate that the digitalization system, the effectiveness of internal control, and internal control do not have a significant impact on the value of infrastructure partially. The findings of this study state that these variables do not directly affect the value of the company in the context of the sample and time period studied.
References
A. Desiani and M. Arhami, Konsep Kecerdasan Buatan, 1 ed., D. Hardjono, Ed., Yogyakarta: Penerbit ANDI, 2006.
Kusrini, Sistem Pakar Teori dan Aplikasi, 1 ed., f. Suyantoro, Ed., Yogyakarta: Penerbit ANDI, 2006.
A. Desiani and M. Arhami, Konsep Kecerdasan Buatan, 1 ed., D. Hardjono, Ed., Yogyakarta: Penerbit ANDI, 2006.
I. A. Adriana, Penalaran Komputer Berbasis Kasus (Case Based Reasoning), Yogyakarta: Ardana Media, 2007.
R. D. R. e. all, Telinga Hidung Tenggorok Kepala dan Leher edisi ketujuh, Jakarta: FK UI, 2012.
E. M. V. S. T.Sutojo, Kecerdasan Buatan, Yogyakarta: Andi, 2011.
S. W. Faza Akmal, "SISTEM PPAKAR UNTUK MENDIAGNOSA PENYAKIT LAMBUNG DENGAN IMPLEMENTASI METODE CBR (CASE BASED REASONING) BERBASIS WEB," Jurnal Sarjana Teknik Informatika, vol. 2 , no. 1, Februari 2014.
A. M. M. M. N. W. a. N. F. Adiwijaya, "A comparative study of MFCC-KNN and LPC-KNN for hijaiyyah letters pronounciation classification system," Information and Communication Technology (ICoIC7), pp. (pp. 1-5), 2017.
M. N. Al-Kabi, G. Kanaan, R. Al-Shalabi, S. Al-Sinjilawi and R. S. Al-Mustafa, "Al-Hadith Text Classifier," Journal of Applied Sciences 5, pp. 584-587, 2005.
F. Harrag and E. El-Qawasmah, "Neural Network for Arabic Text Classification," 2009 Second International Conference on the Applications of Digital Information and Web Technologies, pp. 778-783, 2009.
E. R. R. J. S. A.-F. and A. , "Klasifikasi Anjuran, Larangan dan Informasi pada Hadis Sahih Al-Bukhari," e-Proceeding of Engineering, p. 4683, 2017.
A. K. S. A.-F. and A. , "Klasifikasi Informasi, Anjuran dan Larangan pada Hadits Shahih Bukhari menggunakan Metode Support Vector Machine," e-Proceeding of Engineering, p. 5014, 2017.
A. I. P. and Adiwijaya, "On the Feature Selection and Classification Based on Information Gain for Document Sentiment Analysis," Applied Computational Intelligence and Soft Computing, vol. 2018, p. 5, 2018.
M. Z. and Z. H. Z. , "Multilabel neural networks with applications to functional genomics and text," IEEE transactions on Knowledge and Data Engineering, pp. 1338-1351, 2006.
M. S. M. N. S. H. A. Reynaldi Ananda Pane, "A Multi-lable Classification on Topics of Quranic Verses in English Translation using Multinomial Naive Bayes," 6th International Conference on Information and Communication Technology (ICoICT), 2018.
S. a. N. F. Nurcahyo, "Rainfall Prediction in Kemayoran Jakarta Using Hybrid Genetic Algorithm (GA) and Partially Connected Feedforward Neural Network (PCFNN)," Information and Communication Technology (ICoICT), pp. (pp. 166-171), 2014.
J. S. D. Raharjo, "Model Artificial Neural Network berbasis Particle Swarm Optimization untuk Prediksi Laju Inflasi," Sistem Komputer, 2013.
H. N. A. H. S. M. S. and N. S. , "Particle Swarm Optimization For Neural Network Learning Enchancement," Jurnal Teknologi, pp. 13-26, 2008.
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