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All Journal International Journal of Engineering, Technology and Natural Sciences (IJETS) Journal Innovations Computer Science
Rahman, Haidar
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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A A Wind Forecasting Model Using Regression and Genetic Algorithm to Solve Economic Dispatch for Evaluating a Hybrid Power System Rahman, Haidar; Budi Prasetyo, Ridwan
Jurnal Internasional Teknik, Teknologi dan Ilmu Pengetahuan Alam Vol 2 No 2 (2020): International Journal of Engineering, Technology and Natural Sciences
Publisher : University of Technology Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (339.158 KB) | DOI: 10.46923/ijets.v2i2.69

Abstract

In this research, the problem to find an evaluator to determine a location to build the standalone power system can be seen as problem which can be solved with Kernels Regression where, it will receive 2 inputs such as time and wind speed in order to predict the future wind speed. Afterward the obtained predicted wind speed will be converted into potential electrical energy with maximum and minimum energy and we will be using the Genetic Algorithm (GA) to solve the Economic Dispatch (EDC) to see the operational cost when dispatch into the grid. The data was taken from Baron Techno-Park and PLTH Pantai Baru, and will only be using data from the month of September - December since it is the rainy season. Therefore, since significant parameters such as energy per currency will show that operational cost of Baron Techno-Park have the least operational cost then PLTH Pantai Baru, hence the creation of renewable power plants in Baron Techno-Park are suitable and will have a good operational cost justification. Keywords: Economic Dispatch, Genetic Algorithm, Kernels Regression Standalone Power Plant.
AcaraKita: Integrated Digital Platform for Event Organizer Services in Indonesia Tegar Pangestu, Bukhori Debrillianda; Nurfattah, Fu’ad Na’im; Rahman, Haidar; Wido Prasojo, Nanda
Journal Innovations Computer Science Vol. 4 No. 2 (2025): November
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/jics.v4i2.306

Abstract

This study examines the development and implementation of AcaraKita, a web- and mobile-based digital platform designed to modernize event organizer (EO) services in Indonesia. The system integrates three primary actors—Admin, Admin EO, and Customer—each with distinct yet complementary roles involving vendor management, booking, verification, status tracking, and service reviews. The development process applied the Waterfall model, consisting of requirement analysis, design, implementation, testing, deployment, and maintenance, combined with IT governance evaluation using the COBIT 5 framework to ensure alignment with business objectives. Testing results indicated that all core features operated effectively, with an average response time of less than one second and a user satisfaction score of 4.139 on the Likert scale. The IT governance risk analysis highlighted the need for improvements in documentation, security, and business continuity planning. While the system demonstrates a solid foundation, further enhancements are necessary, including social media API integration, vendor recommendation systems, and analytics dashboards to support decision-making. Overall, AcaraKita strengthens EO digitalization, improves operational efficiency, and fosters service transparency in a sustainable manner.
AcaraKita: Integrated Digital Platform for Event Organizer Services in Indonesia Tegar Pangestu, Bukhori Debrillianda; Nurfattah, Fu’ad Na’im; Rahman, Haidar; Wido Prasojo, Nanda
Journal Innovations Computer Science Vol. 4 No. 2 (2025): November
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/jics.v4i2.306

Abstract

This study examines the development and implementation of AcaraKita, a web- and mobile-based digital platform designed to modernize event organizer (EO) services in Indonesia. The system integrates three primary actors—Admin, Admin EO, and Customer—each with distinct yet complementary roles involving vendor management, booking, verification, status tracking, and service reviews. The development process applied the Waterfall model, consisting of requirement analysis, design, implementation, testing, deployment, and maintenance, combined with IT governance evaluation using the COBIT 5 framework to ensure alignment with business objectives. Testing results indicated that all core features operated effectively, with an average response time of less than one second and a user satisfaction score of 4.139 on the Likert scale. The IT governance risk analysis highlighted the need for improvements in documentation, security, and business continuity planning. While the system demonstrates a solid foundation, further enhancements are necessary, including social media API integration, vendor recommendation systems, and analytics dashboards to support decision-making. Overall, AcaraKita strengthens EO digitalization, improves operational efficiency, and fosters service transparency in a sustainable manner.
Artificial Neural Network Based Evaluation of Wind Energy Potential for Small-Scale Renewable Power Generation in Wufeng, Taiwan Rahman, Haidar; Akbar, Ahzami Fadilah
Jurnal Internasional Teknik, Teknologi dan Ilmu Pengetahuan Alam Vol 7 No 2 (2025): International Journal of Engineering, Technology and Natural Sciences
Publisher : Universitas Teknologi Yogyakarta, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46923/ijets.v7i2.581

Abstract

This study investigates the wind energy potential in the Wufeng area of Taichung, Taiwan, with the aim of supporting the development of small-scale renewable wind power generators. Specifically, it seeks to evaluate wind patterns and meteorological parameters over a three-year period and to identify the most accurate predictive model for wind speed and energy output. A quantitative research methodology was employed, analyzing weather data using multiple regression algorithms, including Linear Regression, Lasso Regression, Ridge Regression, Support Vector Regression (SVR), Dynamic Thermal Rating (DTR), and Artificial Neural Network (ANN). The performance of these models was compared through data training and testing, with the ANN demonstrating the highest predictive accuracy. Using this model, the maximum expected wind speed was determined to be 5.56 m/s, corresponding to a potential energy output of 992.57 watts over a one-week period, indicating that the region is suitable for small-scale wind power development. However, the study is limited by its reliance on short-term data, which may not capture seasonal variations, economic feasibility, or operational constraints of wind power systems. Therefore, future research should incorporate long-term wind monitoring, feasibility assessments, and pilot projects to evaluate the practical performance and reliability of small-scale wind turbines in the Wufeng region.
Co-Authors Akbar, Ahzami Fadilah Nurfattah, Fu’ad Na’im Ridwan Budi Prasetyo Tegar Pangestu, Bukhori Debrillianda Wido Prasojo, Nanda