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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Rekayasa Teknologi dan Sains Terapan Jurnal Teknik Mesin Mechanical Xplore Proceeding of the International Conference on Family Business and Entrepreneurship (ICFBF) Jurnal Pemberdayaan Umat Applied Quantitative Analysis (AQA) Journal of Actuarial, Finance, and Risk Managment
Hamzah, Dadang Amir
President University
Agriculture, Biological Sciences & Forestry Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation

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ANALISIS GAYA PADA SILINDER UNTUK ALAT ANGKUT TIPE HYDRAULIC SCISSOR LIFT KAPASITAS 1.000 KG Ana Fitriani; Muchammad Chusnan Aprianto; Mochamad Abdul Muftinur; Dadang Amir Hamzah
Jurnal Teknik Mesin Mechanical Xplore Vol 1 No 2 (2021): Jurnal Teknik Mesin Mechanical Xplore
Publisher : Mechanical Engineering Department Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (694.605 KB) | DOI: 10.36805/jtmmx.v1i2.1390

Abstract

Penelitian ini bertujuan untuk menganalisis gaya yang bekerja pada bagian silider pada perancangan alat angkut dengan tipe scissor lift yang saat ini banyak digunakan di dunia industri. Alat yang dirancang mampu mengangkat beban 1000 kg berdasarkan perhitungan menggunakan standar ANSI MH29.1-2012. Selain dirancang secara perhitungan manual, simulasi model juga digunakan untuk mengkonfirmasi hasil perhitungan secara manual. Berdasarkan hasil perhitungan diperoleh gaya silider pada posisi terendah sebesar 23.641,74 N. Selain itu, beban gaya silider pada posisi tertinggi sebesar 74.473,03 N. Berdasarkan hasil perhitungan tegangan manual yang didapat dapat disimpulkan bahwa tegangan yang dihitung tidak melebihi tegangan normal yang diijinkan sehingga desain scissor lift kapasitas 1.000 kg berdasarkan standar ANSI MH29.1-2012 dinyatakan bisa dibuat untuk difabrikasi.
On The Decay Energy of Lotka-Volterra Reaction-Diffusion Competition Model Dadang Amir Hamzah
Jurnal Rekayasa Teknologi dan Sains Terapan Vol 1 No 2 (2018): Jurnal Rekayasa Teknologi dan Sains Terapan
Publisher : LPPM, Sekolah Tinggi Teknologi DR. KHEZ Muttaqien

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Abstract

In this paper we consider Lotka-Volterra system. It describes competition of two species. We explore conditions which guarantee the coexistence of two populations in the system. Energy method is employed to derive the conditions. Numerical example is presented to support the theory.
Numerical Properties of Explicit and Semi-implicit Finite Difference Scheme for Fisher's Equation Dadang Amir Hamzah; Bayu Robiyana
Jurnal Rekayasa Teknologi dan Sains Terapan Vol 2 No 1 (2019): Jurnal Rekayasa Teknologi dan Sains Terapan
Publisher : LPPM, Sekolah Tinggi Teknologi DR. KHEZ Muttaqien

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Abstract

This paper is devoted to analize the numerical finite difference scheme for Fisher’s equations. Fisher’s equation is a parabolic type of partial differential equations for modelling the population growth in mathematical ecology. An explicit and semi-implicit finite difference schemes are constructed with the analysis of their numerical properties such as accuracy, stability and convergency respect to energy norm. An efficient algorithm is contructed to simulate the Fisher’s equation. Some numerical tests are shown in a good agreement with the numerical properties (i.e the stability scheme)
On explicit finite difference scheme for Korteweg de Vries equation Dadang Amir Hamzah
Jurnal Rekayasa Teknologi dan Sains Terapan Vol 2 No 2 (2019): Jurnal Rekayasa Teknologi dan Sains Terapan
Publisher : LPPM, Sekolah Tinggi Teknologi DR. KHEZ Muttaqien

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Abstract

In this paper we apply a finite difference method to approximate the solution of KdV equation. We implement the scheme to the benchmark problem and compare with the exact solution. The results shows that the numerical solution are agree with the exact solution.
On Energy Bound of Burgers Fisher Equation Under Dirichlet Boundary Condition Dadang Amir Hamzah
Jurnal Rekayasa Teknologi dan Sains Terapan Vol 3 No 2 (2021): Jurnal Rekayasa Teknologi dan Sains Terapan
Publisher : LPPM, Sekolah Tinggi Teknologi DR. KHEZ Muttaqien

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Abstract

.In this paper the energy bound for the Burgers-Fisher equation under Dirichlet Boundary condition is determined. The boundedness of the reaction term plays a significant role in determining the energy bound. A number of inequalities are employed in deriving of the bound.
Predicting Bank Loan Application Approval using Logistic Regression Method Dadang Amir Hamzah; Akbar Jabbarudin; Haura Nizar Nabila; Muhammad Alfarisi; Salwa Fayza Alkatraz; Zievan Ananta Pahlevi
Jurnal Rekayasa Teknologi dan Sains Terapan Vol 4 No 1 (2022): Jurnal Rekayasa Teknologi dan Sains Terapan
Publisher : LPPM, Sekolah Tinggi Teknologi DR. KHEZ Muttaqien

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Abstract

This paper provides an overview of the analysis that affects a bank based on existing data records. By using logistic regression, the dependent variable is a defining feature that determines whether there is an investment or not investment. On the other hand, the independent variables are analyzed by using exploratory data analysis to identify which characteristic has the highest correlation with the dependent variable. Based on selected features, the logistic regression model is created and used to generate the prediction data. The predicted data will provide an excellent approximation for the actual data.
Solvability Conditions of Integro-Differential Equation on Classical Risk Models with Exponential Claims via Laplace Transform Dadang Amir Hamzah; Ranny Febrianti
Jurnal Rekayasa Teknologi dan Sains Terapan Vol 4 No 2 (2023): Jurnal Rekayasa Teknologi dan Sains Terapan Vol. 4 No. 2
Publisher : LPPM, Sekolah Tinggi Teknologi DR. KHEZ Muttaqien

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Abstract

In the classical risk models, ruin probability can be determined by solving the initial value problem of the integro-differential equation. This equation is determined by considering the process that arises from the amount of the first claim in a classical risk model. The Laplace transform is applied to solve the integro-differential equation. The parameters that appear in the model such as loading factor, claim amount distribution, and number of claim parameters can influence the successful application of this method, that is for some value of parameters in the model, the Laplace transform can return the analytical solution of the integro differential equation. In this paper, the lower bound of the loading factor is determined. The claims amount distribution is divided into three different forms of exponential functions. The bound will guarantee the successful application of Laplace transforms in solving the integro-differential equation.
Identifying Fraud in Automobile Insurance Using Naïve Bayes Classifier Dadang Amir Hamzah; Annisa Sentya Hermawan; Shintya Jasmine Pertiwi; Syarifah Intan Nabilah
Journal of Actuarial, Finance, and Risk Management Vol 1, No 2 (2022)
Publisher : Journal of Actuarial, Finance, and Risk Management

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33021/jafrm.v1i2.3971

Abstract

In this article, the Naïve Bayes Classifier is employed to detect fraud in automobile insurance. The Naïve Bayes classier is a simple probabilistic method based on the Bayes theorem. The data used in this article is determined from databricks.com which consists of 40 attributes and 1000 entries. The target attribute that will be predicted consists of two categories,” yes" or "no", which inform whether there is a fraud or not. The Data is split into training and testing with suitable proportions. Based on training data, the Naïve Bayes Classifier is applied to the testing data and returns the predictions data. Then, the prediction data is compared with the actual data to see the performance of the method. The result shows that the Naïve Bayes Classifier gives a good result to predict the insurance fraud with 78% accuracy, 67% precision, 3% of recall,  and  6% of F1 score  for “Yes”
Pemberdayaan Ibu Rumah Tangga: Pelatihan Minyak Jelantah Jadi Sabun Ramah Lingkungan Fernando, Agus; Hakim, Dani Lukman; Hamzah, Dadang Amir
Jurnal Pemberdayaan Umat Vol. 3 No. 2 (2024): Agustus
Publisher : Penerbit Goodwood

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/jpu.v3i2.4067

Abstract

Purpose: The management of used cooking oil waste poses a significant environmental challenge, as it is often not properly managed, resulting in negative impacts on human health and the environment. This training aimed to increase housewives’ knowledge about the dangers of used cooking oil waste, provide skills in making soap as an eco-friendly solution, and support family economies. Research methodology: This activity involved three stages: preparation, implementation, and monitoring evaluation. During the implementation stage, participants received materials on the impact of used cooking oil, a demonstration of soap-making, training in basic bookkeeping, and marketing techniques. Results: The evaluation results showed that 86.7% of the participants intended to apply training at home. The activity had a positive impact by raising environmental awareness and opening new business opportunities for participants. Limitations: This community service is limited to the scope of RW 016, Simpangan Village, and involves only 14 participants; therefore, generalizing the results to a broader community requires further evaluation. Contribution: This research is useful in the fields of community empowerment, environmentally-based waste management, and social entrepreneurship, particularly in densely populated areas with middle-to-low economic levels.
PREDICTING BANK LOAN APPROVAL USING LOGISTIC REGRESSION AND FEATURE SELECTION METHOD Hamzah, Dadang Amir; sigalingging, fika lestauli
Proceeding of the International Conference on Family Business and Entrepreneurship 2024: PROCEEDING OF 8TH INTERNATIONAL CONFERENCE ON FAMILY BUSINESS AND ENTREPRENEURSHIP
Publisher : President University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33021/icfbe.v0i0.5691

Abstract

Examining bank loan application is a long process that requires a detail check in every stages. This process is important in the banking industry, as it directly impacts the bank's risk management and profitability. However, due to a long process in making decision the customer wait a long time to get the decision which results to the customers dissatisfaction. Therefore, to improve the examination process and provide a quick decision result, the more effective tools is required. Logistic regression is a machine learning method that able to predict the binary output based on the probability value. This method takes the value from the multiple regression method and convert it into probability value using the activation function called sigmoid function. This paper applies the logistic regression method to predict bank loan approvals based on several features considered as independent variables. This research uses the secondary data taken from www.kaggle.com. The model performance is measured using the confusion matrix that consist of accuracy, precision, recall, and F1 score. This research construct three models based on data type. The first model is constructed using numerical data only, the second model is constructed using categorical data only, and the third model is constructed by combining numerical data type and categorical data type. It is determined that the first model return 87.8% accuracy, 95.94% precision, 87.57% recall, and 91.56% F1 score. The second model return accuracy 69%, precision 96.81%, recall 69.87%, and F1 score 81.17%. Moreover, the return 86.6% accuracy, 96.81% precision, 85.64% recall, and 90.88% F1 score. Based on these results, it is concluded that the best method in processing loan bank application data is to use the third model that is the model that includes both categorical and numerical data type. 
Co-Authors Akbar Jabbarudin Alika, Zalfani Alkhayyat, Naufal G Ana Fitriani Annisa Sentya Hermawan Bayu Robiyana Fernando, Agus Goklas, Lucky S Haura Nizar Nabila Kalambe, Averia A Mochamad Abdul Muftinur Muchammad Chusnan Aprianto Muhammad Alfarisi Nugraha, Edwin Setiawan Pranata, Vania Chrestella Ranny Febrianti Salwa Fayza Alkatraz Shintya Jasmine Pertiwi Siahaan, Theresia Stefany Anawa sigalingging, fika lestauli Singgih, Gabriella Maria Syarifah Intan Nabilah Zievan Ananta Pahlevi