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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Scientific Journal of Informatics JURNAL AGRILAND Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Abdimas Talenta : Jurnal Pengabdian Kepada Masyarakat Data Science: Journal of Computing and Applied Informatics CCIT (Creative Communication and Innovative Technology) Journal Journal of Information System, Applied, Management, Accounting and Research Jurnal Informatika Kaputama (JIK) Jurnal Pengabdian Al-Ikhlas Journal of Applied Engineering and Technological Science (JAETS) Indonesian Journal of Electrical Engineering and Computer Science Journal of Research in Mathematics Trends and Technology Narra J Jurnal EduHealth
Mahyuddin K. M Nasution
Faculty Of Computer Science And Information Technology, Universitas Sumatera Utara, Medan, Indonesia
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Public Health Social Sciences Veterinary

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Journal : Bulletin of Electrical Engineering and Informatics

 1 
Complexity prediction model: a model for multi-object complexity in consideration to business uncertainty problems Syah, Rahmad B. Y.; Satria, Habib; Elveny, Marischa; K. M. Nasution, Mahyuddin
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5380

Abstract

In a competitive environment, the ability to rapidly and successfully scale up new business models is critical. However, research shows that many new business models fail. This research looks at hybrid methods for minimizing constraints and maximizing opportunities in large data sets by examining the multivariable that arise in user behavior. E-metric data is being used as assessment material. The analytical hierarchy process (AHP) is used in the multi-criteria decision making (MCDM) approach to identify problems, compile references, evaluate alternatives, and determine the best alternative. The multi-objectives genetic algorithm (MOGA) role analyzes and predicts data. The method is being implemented to expand the information base of the strategic planning process. This research examines business sustainability along two critical dimensions. First, consider the importance of economic, environmental, and social evaluation metrics. Second, the difficulty of gathering information will be used as a predictor for making long-term business decisions. The results show that by incorporating the complexity features of input optimization, uncertainty optimization, and output value optimization, the complexity prediction model (MPK) achieves an accuracy of 89%. So that it can be used to forecast future business needs by taking into account aspects of change and adaptive behavior toward the economy, environment, and social factors.
A novel MPK optimization framework for financial data analysis incorporating complexity and uncertainty management Syah, Rahmad Bayu; Elveny, Marischa; Ananda, Rana Fathinah; Nasution, Mahyuddin Khairuddin Matyuso
Bulletin of Electrical Engineering and Informatics Vol 14, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i4.9358

Abstract

In a competitive environment, the ability to scale quickly and successfully is a critical need. This research proposes a new framework using multi-objective complexity prediction model (MPK) for financial data analysis, including complexity and uncertainty management. This model integrates input, uncertainty, and output optimization functions (OOFs) (input optimization function (IOF), uncertainty optimization function (UOF), and OOF) to predict complex output values under dynamic business conditions. Model evaluation is carried out using performance metrics, namely mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE), and R² score. The evaluation results show that this model has an MSE value of 20.112, an RMSE of 2.267, and an MAE of 2.351, reflecting a low prediction error rate and high accuracy. In addition, the R² value of 0.884259 indicates that this model is able to explain around 88.4% of the variability in the output data, indicating its ability to capture complex data patterns. Thus, the proposed MPK model is effective in predicting output values in complex business scenarios and can be applied for strategic decision-making under conditions of uncertainty.
Co-Authors Al Khowarizmi Albadri, Aldhi Alexander F.K. Sibero Amelia Oktarini Siregar Ananda, Rana Fathinah Aritonang, Evawany Y. Azmi, Zulfian - Betty Yel, Mesra Efendi, Syahril Elveny, Marischa Elviawaty Muisa Zamzami Erna Budhiarti Nababan Habib Satria Harahap, Latifah Hanum Herman Mawengkang Heru Santosa Imelda, Fatwa Ivan Jaya Ivan Jaya Lubis, Arif Ridho Lumbanraja, Sarma N. Marischa Elveny, Marischa Muhammad Ichwan Muhammad Zarlis Muhammad Zarlis, Muhammad Nainggolan, Pauzi Ibrahim Opim Salim Sitompul Rahmad Syah Rahman Aulia, Rahman Rambe, Basyit Mubarroq Sawaluddin Sawaluddin, Sawaluddin Siahaan, Andre MP. Sri Melvani Hardi Sutarman Sutarman Syah, Rahmad B. Y. Syah, Rahmad Bayu Syamsafitri Syamsafitri Tobing, Immanuel DL. Verdi Yasin Y. Syah, Rahmad B. Zarlis, M Zarlis, M Zulfian Azmi