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All Journal International Journal of Electrical and Computer Engineering Jurnal Keteknikan Pertanian Perfecting a Video Game with Game Metrics JURNAL PENGABDIAN KEPADA MASYARAKAT Journal of Computer, Electronic, and Telecommunication (COMPLETE)
Nanda, Muhammad Achirul
Universitas Padjadjaran
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Social Sciences

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Journal : International Journal of Electrical and Computer Engineering

 1 
The susceptible-infected-recovered-dead model for long-term identification of key epidemiological parameters of COVID-19 in Indonesia Muhammad Achirul Nanda; Anifatul Faricha; Siti Maghfirotul Ulyah; Ni'matut Tamimah; Enny Indasyah; Muhammad Falahudin Malich Salaz; Qurrotun 'Ayun Mawadatur Rohmah; Ulfah Abqari
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2900-2910

Abstract

The COVID-19 epidemic has spread massively to almost all countries including Indonesia, in just a few months. An important step to overcoming the spread of the COVID-19 is understanding its epidemiology through mathematical modeling intervention. Knowledge of epidemic dynamics patterns is an important part of making timely decisions and preparing hospitals for the outbreak peak. In this study, we developed the susceptible-infected-recovered-dead (SIRD) model, which incorporates the key epidemiological parameters to model and estimate the long-term spread of the COVID-19. The proposed model formulation is data-based analysis using public COVID-19 data from March 2, 2020 to May 15, 2021. Based on numerical analysis, the spread of the pandemic will begin to fade out after November 5, 2021. As a consequence of this virus attack, the cumulative number of infected, recovered, and dead people were estimated at ≈ 3,200,000, ≈ 3,437,000 and ≈ 63,000 people, respectively. Besides, the key epidemiological parameter indicates that the average reproduction number value of COVID-19 in Indonesia is 7.32. The long-term prediction of COVID-19 in Indonesia and its epidemiology can be well described using the SIRD model. The model can be applied in specific regions or cities in understanding the epidemic pattern of COVID-19.
Comparison study of transfer function and artificial neural network for cash flow analysis at Bank Rakyat Indonesia Anifatul Faricha; Siti Maghfirotul Ulyah; Rika Susanti; Hawwin Mardhiana; Muhammad Achirul Nanda; Ilma Amira Rahmayanti; Christopher Andreas
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i6.pp6635-6644

Abstract

The cash flow analysis is essential to examine the economic flows in the financial system. In this paper, the financial dataset at Bank Rakyat Indonesia was used, it recorded the sources of cash inflow and outflow during a particular period. The univariate time series model like the autoregressive and integrated moving average is the common approach to build the prediction based on the historical dataset. However, it is not suitable to estimate the multivariate dataset and to predict the extreme cases consisting of nonlinear pairs between independent-dependent variables. In this study, the comparison of using two types of models i.e., transfer function and artificial neural network (ANN) were investigated. The transfer function model includes the coefficient of moving average (MA) and autoregressive (AR), which allows the multivariate analysis. Furthermore, the artificial neural network allows the learning paradigm to achieve optimal prediction. The financial dataset was divided into training (70%) and testing (30%) for two types of models. According to the result, the artificial neural network model provided better prediction with achieved root mean square error (RMSE) of 0.264897 and 0.2951116 for training and testing respectively.
Shannon entropy on near-infrared spectroscopy for nondestructively determining water content in oil palm Inna Novianty; Walidatush Sholihah; Gema Parasti Mindara; Muhammad Iqbal Nurulhaq; Anifatul Faricha; Rismen Sinambela; Pradeka Brilyan Purwandoko; Muhammad Achirul Nanda
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i5.pp5397-5405

Abstract

Indonesia is the world’s largest producer of palm oil. To preserve its competitive advantages, the Indonesian oil palm sector must expand high-quality palm oil output. In oil palm quality control, the water content is a crucial parameter as it can be used as a reference to determine the right harvest time. Thus, this study proposed a near-infrared (NIR) spectroscopy as a fast and non-destructive analysis to assess oil palm water content. NIR spectra were processed using Shannon entropy to describe the characteristics at each wavelength. In this study, oil palm fruit samples at various maturity levels were collected with eight different maturity fractions. Based on the analysis, the Shannon entropy value is closely related to any changes in the water content of palm oil. The entropy value has a decreasing trend as the water content increases. The proposed technique can predict the water content of an oil palm with satisfactory performance with values of 0.9746 of coefficient of determination (R2) and 2,487 of root mean square error (RMSE). Application of this model will lead to a fast and accurate prediction system related to oil palm water content.
Co-Authors Anifatul Faricha Anifatul Faricha anifatul faricha Christopher Andreas Djoko Purwanto Dodi Nandika Gema Parasti Mindara Ilma Amira Rahmayanti Indasyah, Enny Inna Novianty Kharistya Amaru Kudang Boro Seminar M. Rivai Mardhiana, Hawwin Muhammad Falahudin Malich Salaz Muhammad Iqbal Nurulhaq Ni'matut Tamimah Ni'matut Tamimah Pradeka Brilyan Purwandoko Qurrotun 'Ayun Mawadatur Rohmah Rika Susanti Rismen Sinambela Rizki Anhar R.P. Robin Addwiyansyah Alvaro Samrat Sholihah, Walidatush Siti Maghfirotul Ulyah Siti Maghfirotul Ulyah Sophia Dwiratna Nur Perwitasari Suwito Suwito Ulfah Abqari