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Advanced Exergy Analysis on the Turbofan Engine Indriyati, Feni; Mahandari, Cokorda Prapti; Yamin, Mohamad
Journal of Novel Engineering Science and Technology Vol. 3 No. 03 (2024): Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v3i03.543

Abstract

Studies on energy utilization underscore the paramount importance of energy, as evidenced by numerous researchers. This research encompasses both conventional and advanced exergy analyses. Advanced exergy analysis aims to ascertain the extent of energy loss in each component, influenced by irreversibility, and to account for component interactions within the system. Furthermore, advanced exergy analysis seeks to enhance the operational efficiency of each engine component. The findings reveal that the combustion chamber exhibits the highest level of energy loss, amounting to 32.817 MW. This energy loss primarily stems from irreversibility triggered by chemical reactions leading to heat transfer. Overall, the study results indicate that the exergy influx from external sources surpasses that generated internally in each component system.
KONTRIBUSI PERENCANAAN SDM DAN DISIPLIN KERJA TERHADAP KINERJA PEGAWAI PT.LION AIRLINES DI BANDARA INTERNASIONAL Yamin, Mohamad
Jurnal Nusantara Madani Vol 3 No 1 (2024): Jurnal Nusantara Madani
Publisher : Jurnal Nusantara Mandani

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Masalah pokok dalam penelitian ini adalah apakah proses Kontribusi Perencanaan SDM dan disiplin kerja terhadap kinerja pegawai di PT Lion Air Bandara Internasional Soekarno Hatta, diantara proses kontribusi perencanaan SDM dan disiplin kerja yang manakah berpengaruh dominan terhadap kinerja pegawai di PT.Lion Air. Hasil penelitian menunjukan bahwa: proses kontribusi perencanaan SDM dan disiplin kerja berpengaruh positif dan signifikan terhadap kinerja pegawai PT Lion Air di Bandara Internasional Soekarno Hatta, dan juga untuk mengetahui manakah faktor yang berpengaruh lebih dominan terhadap kinerja pegawai pada PT. Lion Air di Bandara Internasional Soekarno Hatta. Untuk mengaplikasi tujuan tersebut maka digunakan metode deskriptif, Berdasarkan hasil analisis mengenai kontribusi perencanaan SDM dan disiplin kerja terhadap kinerja pegawai PT Lion Air, di Bandara Internasional Soekarno Hatta. Hasil penelitian menunjukan bahwa pengaruh Perencanaan SDM dan Disiplin Kerja Terhadap Kinerja Pegawai, dengan kontribusi determinasi (R²) sebesar 0,514 atau 51,4%. Dijelaskan oleh variabel lain diluar konsep penelitian dan persamaan regresi yang dihasilkan adalah Y= 7,643 + 0,286X1+ 0,512X2. Berdasarkan persamaan regresi diatas maka dapat dijelaskan, dengan nilai konstanta (b0) sebesar 7,643, menyatakan bahwa nilai Kinerja Pegawai akan tetap ada sebesar 7,643 walaupun variabel bebasnya Perencanaan SDM, dan Disiplin Kerja tidak ada (0). Nilai (b1) sebesar 0,286, ini berarti menunjukan ada pengaruh positif dan signifikan variabel Perencanaan SDM terhadap Kinerja Pegawai sebesar 0,286, jika nilainya positif berarti kalau ada peningkatan sebesar 0,286 maka Kinerja Pegawaipun akan meningkat sebesar 0,286. Nilai (b2) sebesar 0,512 ini menunjukan bahwa ada pengaruh positif dan signifikan Disiplin Kerja terhadap Kinerja Pegawai yaitu sebesar 0,512, jika Disiplin Kerja meningkat sebesar 0,512 maka Kinerja Pegawai juga akan meningkat sebesar yang sama yaitu 0,512 maka Kinerja Pegawai akan meningkat dengan julam yang sama.
Machine Learning untuk Prediksi Produksi Gula Nasional Jaelani, Toniyah; Yamin, Mohamad; Mahandari, Cokorda Prapti
JMPM (Jurnal Material dan Proses Manufaktur) Vol 6, No 1 (2022): Juni
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jmpm.v6i1.14897

Abstract

Gula merupakan salah satu bahan utama yang selalu dibutuhkan untuk membuat makanan atau minuman. Saat ini produksi gula belum mampu memenuhi kebutuhan gula nasional. Namun, pemerintah terus menambah jumlah pabrik dan meningkatkan produktivitas pabrik gula yang ada untuk memenuhi kebutuhan gula nasional. Di sisi lain, produksi gula juga berfluktuasi. Hal ini dapat mengakibatkan kelangkaan gula jika tidak diprediksi secara tepat dan akurat. Oleh karena itu, pada penelitian ini dilakukan perbandingan prediksi produksi gula Indonesia dengan menggunakan metode machine learning yaitu Long Short Term Memory (LSTM) dan juga dilakukan prediksi dengan menggunakan metode regresi linier. Penelitian ini dilakukan berdasarkan data sekunder yang bersumber dari hasil penelitian dan laporan dari instansi atau instansi terkait. Data yang digunakan adalah data nasional berupa time series selama 52 tahun yaitu dari tahun 1968 sampai dengan tahun 2020. Hasil penelitian ini menunjukkan bahwa error pada metode regresi linier adalah 8%. Hasil prediksi dengan machine learning menunjukkan error yang lebih kecil dibandingkan dengan metode regresi linier. Metode LSTM menghasilkan error data kereta sebesar 0,069% dan nilai error data pengujian sebesar 0,082%. Hasil peramalan dari regresi linier memiliki trend produksi yang meningkat namun pada metode LSTM hasilnya mengalami trend penurunan. Sugar is one of the main ingredients that are always needed to make food or drink. At this time sugar production has not been able to meet the national sugar demand. However, the government continues to increase the number of factories and increase the productivity of existing sugar factories to meet national sugar demand. On the other hand, sugar production also fluctuated. This can lead to a shortage of sugar if it is not predicted precisely and accurately. Therefore, in this study, a comparison of predictions of Indonesian sugar production was carried out using the machine learning method, namely Long Short Term Memory (LSTM) and predictions were also made using a linear regression method. This research was conducted based on secondary data sourced from research results and reports from related institutions or agencies. The data used is national data in the form of a time series for 52 years, namely from 1968 to 2020. The results of this study show that the error in the linear regression method is 8%. Prediction results with machine learning show a smaller error than the linear regression method. The LSTM method produces a train data error of 0.069% and a test data error value of 0.082%. Forecasting results from linear regression have an increasing trend in production but in the LSTM method the results experience a downward trend.
Support Vector Regression Approach for Wind Forecasting Yamin, Mohamad; Giyats, Ahmad Fakhri
International Journal of Advanced Science Computing and Engineering Vol. 4 No. 2 (2022)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (393.552 KB) | DOI: 10.62527/ijasce.4.2.84

Abstract

The government policies to fully support the G20 sustainability emphasize increased use of renewable energy. The high penetration of wind energy into power systems poses many challenges for energy system operators, primarily due to the unpredictability and variability of wind energy production. Wind power may not be provided, but accurate forecasting of wind speed and power generation helps grid operators reduce the risk of reduced electricity reliability. Accurately predicting wind speeds over 1 to 24 hours based on these conditions is important for predicting potential energy supply. These short-term forecasts are important to support wind power planning, so the required base load supply for the grid is always guaranteed (even if the wind power output fluctuates significantly). This task demonstrates that the relative forecasting performance of a support vector regression (SVR) wind forecasting system can be improved by systematically selecting and combining related input functions that affect wind speed. Shows the results of data collected in Sidrap, Indonesia, during the six months of 2019. This paper explained key methods of wind forecasting, based on the evaluation of wind speeds and wind speed prediction methods. The RMSE from the SVR shows an 8% - 9% improvement on the RMSE of the persistence forecast every 1 hour. Wind speed estimation using a support vector regression approach has the potential for further development, one of which is determining the potential location of wind-based renewable sources and Wind Energy Conversion System (WECS) can make more efficient.
Handling and Stability Analysis of an Autonomous Vehicle Using Model Predictive Control in a CarSim–Simulink Co-Simulation Environment Yamin, Mohamad; Mumtaz, Mega Maulida; Firmansyah, Riyan
International Journal of Innovation in Mechanical Engineering and Advanced Materials Vol 7, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/ijimeam.v7i2.31812

Abstract

Cars are a prevalent mode of transportation for both people and goods, with B-class hatchbacks being particularly popular in Indonesia. However, road traffic crashes remain a major concern, contributing millions of deaths annually, primarily due to human error. Autonomous vehicles offer a promising solution to mitigate these issues by reducing reliance on human control. In particular, Level 3 autonomous vehicles enhance road safety, enable independent mobility, reduce traffic congestion, and allow drivers to engage in non-driving tasks. This study proposes an autonomous vehicle model that employs a trajectory tracking approach using Model Predictive Control (MPC), a robust and widely adopted control strategy in autonomous systems. A three-degree-of-freedom (3-DOF) vehicle dynamic model was developed and analyzed through co-simulation using CarSim and Simulink to evaluate its performance during a double-lane change maneuver. The simulation results demonstrate that the vehicle accurately follows the reference trajectory and exhibits excellent dynamic performance. The roll angle remained consistently low, ranging between 0.024 and 0.026 radians—well below the rollover threshold of 0.14 radians—demonstrating strong roll stability. The slip angle varied between –0.013 and 0.0135 radians, nearly 12 times lower than the critical limit, indicating optimal traction and directional control. Lateral acceleration ranged from –3.59 m/s² to 3.41 m/s², and yaw rate remained within –7.78°/s to 7.25°/s, both well within safe operational bounds. These findings confirm that the proposed MPC-based control framework enables precise path tracking, robust stability, and reliable handling performance in dynamic driving scenarios.
Studi Numerik Pengaruh Flutter Pada Sirip Roket Berbahan Material Bio-Komposit Putranto , Muhammad Naufal; Yamin, Mohamad; Permana, Sulaksana
AME (Aplikasi Mekanika dan Energi): Jurnal Ilmiah Teknik Mesin Vol. 11 No. 1 (2025)
Publisher : Universitas Ibn Khaldun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32832/ame.v11i1.1405

Abstract

Sirip roket merupakan komponen penting untuk mendukung keberhasilan misi menerima beban earodinamis yang tinggi. Pada saat menjalankan misi, terdapat kemungkinan kegagalan struktur sirip roket akibat gaya aerodinamis yang biasa disebut sebagai efek flutter. Material sirip yang berbeda dapat memberikan perilaku terhadap efek flutter yang berbeda. Disamping itu, isu lingkungan mendorong penggunaan material ramah lingkungan, seperti material bio-komposit. Dalam paper ini dilakukan pengujian numerik dengan mengunakan metode Fluid Structure Interaction (FSI) untuk mengetahui pengaruh flutter yang terjadi pada sirip roket dengan memanfaatkan aplikasi ANSYS 2023 R1. Hasil studi menunjukkan bahwa nilai frekuensi natural pada sirip roket sebesar 21,854Hz, 45,655Hz, 89,106Hz, dan 121,59Hz. Selain itu, diketahui bahwa fenomena flutter untuk material bio-komposit terjadi pada kecepatan 149,81m/s. Analisis FSI dilakukan pada kecepatan flutter sirip roket dengan tekanan udara 9460,49 Pa dan didapatkan tekanan aerodinamik yang bekerja pada sirip roket menyebabkan sirip roket mengalami deformasi bersifat osilasi dengan nilai deformasi terbesar ada pada sumbu x yaitu sebesar 0,439 mm.
PRESTASI POMPA SENTRIFUGAL TIPE OVERHUNG UNTUK APLIKASI INDUSTRI DENGAN METODE REVERSE ENGINEERING DAN CFD Yamin, Mohamad; Irawan, Rudi; Mahandari, Cokorda Prapti; Ariandi, Rian Dwi; Firmansyah, Riyan; Alfasha, Muhammad Zidan; Suharto, Suharto
Machine : Jurnal Teknik Mesin Vol 11 No 1 (2025): Machine : Jurnal Teknik Mesin
Publisher : Jurusan Teknik Mesin Fakultas Sains dan Teknik Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33019/jm.v11i1.5623

Abstract

Indonesia faces various challenges in achieving net zero emissions, energy crises, and urgent agricultural irrigation needs. In this context, centrifugal pumps play a crucial role in various industrial applications and irrigation systems. However, performance curve data for pumps is often unavailable, particularly for older pumps or those with lost documentation. This study aims to develop new performance curves for centrifugal pumps using Reverse Engineering (RE) based on 3D scanning and Computational Fluid Dynamics (CFD) simulation. The process begins with geometric modeling of the pump using 3D scanning to obtain accurate data regarding the pump’s physical shape. The model is then used in CFD simulations with the k-epsilon (k-ε) turbulence model and SIMPLE method to analyze flow characteristics and pump performance. Simulation results show that the deviation in efficiency and power compared to existing experimental data is below 2%, with a mesh size of 0.00005 mm providing optimal results in terms of accuracy and computational efficiency. This research demonstrates that developing performance curves using RE and CFD methods can address issues of missing data and provide a solid foundation for design improvements and efficient operation of centrifugal pumps. The findings have the potential to enhance operational efficiency of pump systems and support environmental impact mitigation efforts through pump technology optimization.
UJI COBA SISTEM PENGGERAK ELEKTRIK DAN PENGUKURAN TEMPERATUR PADA PROTOTIPE KENDARAAN UG-HEV (HYBRID ELECTRIC VEHICLE) Khalis, Muhana; Yamin, Mohamad
AME (Aplikasi Mekanika dan Energi): Jurnal Ilmiah Teknik Mesin Vol. 7 No. 1 (2021)
Publisher : Universitas Ibn Khaldun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32832/ame.v7i1.4121

Abstract

Teknologi kendaraan hybrid merupakan bagian dari pengembangan prototipe kendaraan UG-HEV (Hybrid Electric Vehicle) yang dimodifikasi dari mobil Toyota Soluna. Kendaraan hybrid merupakan kendaraan yang bergerak menggunakan dua sumber daya yaitu sumber daya bahan bakar dan listrik.  Oleh karena itu, digunakan Brushless Motor DC untuk memenuhi kebutuhan pada putaran motor rendah dengan torsi yang relative besar dari kisaran 1200-3000 rpm. Pengendali utama pada modifikasi mobil hybrid ini adalah KLS BLDC Motor Brushless yang berfungsi untuk mengatur kecepatan putaran motor. Baterai yang digunakan adalah Lithium Ferro Phosphate 4. Dalam penelitian ini dikaji kondisi temperatur sistem penggerak elektrik dengan berbagai kecepatan motor dan sistem pendinginan. Hasil penelitian menunjukkan rotasi putaran motor berputar maksimal, sehingga suhu temperatur penggerak elektrik pada controller mencapai 300C, Baterai 300C dan motor 450C. Sehingga sistem pendinginan diukur menggunakan thermostat, jika suhu themperatur sudah mencapai suhu yang ditetapkan maka sistem pendingin akan menyala secara otomatis dan menurunkan temperatur dengan waktu yang sangat cepat hingga 20-50%.
PENGARUH GREEN INVESTMENT, DAN CARBON CREDIT TERHADAP SUSTAINABLE FIRM PERFOMANCE PADA BANK UMUM SYARIAH YANG TERDAFTAR DI BEI Ningsih, Tiara Setia; Yamin, Mohamad
Management Research and Business Journal Vol. 3 No. 2 (2025): Edisi : Agustus 2025
Publisher : Sekolah Tinggi Ilmu Ekonomi Bhakti Pembangunan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64237/mrb.v3i1.108

Abstract

This study was conducted to determine the Influence of Green Investment and Carbon Credit on Sustainable Firm Performance in Islamic General Banks Listed on the IDX. This study uses Purposive Sampling and uses 14 Islamic General Banks for the 2021-2024 period as research samples. The method used in this study is a quantitative method with data analysis using non-parametric regression tests, determination coefficient tests (R2), F tests, and multicollinearity tests processed using the SPSS program. The results of the study show that the non-parametric regression analysis of the Green Investment and Carbon Credit variables has a positive and significant effect on the three indicators of the Sustainable Firm Performance variable, namely ROA, Total Tree Planting, and Employee Turnover. The Green Investment variable has a significance value of 0.004 (ROA), 0.003 (Total Tree Planting), and 0.047 (Employee Turnover). Meanwhile, the Carbon Credit variable has a significance value of 0.003 (ROA), 0.003 (Total Tree Planting), and 0.011 (Employee Turnover). This finding also shows that green investment efforts and involvement in the carbon credit mechanism are able to support profitability, environmental sustainability, and also social aspects in Islamic Commercial Banks listed on the Indonesia Stock Exchange
PENGARUH GREEN ACCOUNTING, CORPORATE SOCIAL RESPONSIBILITY (CSR), UKURAN PERUSAHAAN TERHADAP KINERJA KEUANGAN PADA PERUSAHAAN PERBANKAN YANG TERDAFTAR DI BEI Berliana Nova, Chairunisa; Yamin, Mohamad
Accounting Research and Business Journal Vol. 3 No. 2 (2025): Edisi : Agustus 2025
Publisher : Sekolah Tinggi Ilmu Ekonomi Bhakti Pembangunan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64237/arbus.v3i1.112

Abstract

This study aims to analyze the effects of Green Accounting, Corporate Social Responsibility (CSR), and Firm Size on Financial Performance as measured by Return on Assets (ROA) among banking companies listed on the Indonesia Stock Exchange (IDX) during the 2020–2023 period. A quantitative approach was employed using secondary data from annual reports and sustainability reports. The sample consisted of 12 banking companies, yielding 48 observations over the four-year span.The data analysis included descriptive statistics, classical assumption testing, and multiple linear regression using SPSS 26. The results reveal that, individually, Green Accounting and Firm Size have a positive and significant impact on ROA, while CSR has a negative but significant effect. Collectively, the three independent variables significantly influence financial performance. The coefficient of determination (R²) is 39.8%, indicating that Green Accounting, CSR, and Firm Size explain 39.8% of the variance in financial performance, with the remainder influenced by factors outside the model.