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All Journal INTEK: Jurnal Penelitian Jurnal Teknologi Elekterika Hexagon Inspiration: Jurnal Teknologi Informasi dan Komunikasi JEAT : Journal of Electrical and Automation Technology Majalah Teknik Industri
Sitti Wetenriajeng Sidehabi
Politeknik ATI Makassar
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Assessment of wind power plant performance using turbine performance and power curves: a case study of PLTB TOLO I Jeneponto Sofyan, Sofyan; Idris, Ahmad Rosyid; Latif, Muh. Ardiansyah; Thaha, Sarma; Asri, Andarini; Thahir, Muhammad; Sidehabi, Sitti Wetenriajeng
Jurnal Teknologi Elekterika Vol. 21 No. 2 (2024)
Publisher : Jurusan Teknik Elektro Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/elekterika.v21i2.5116

Abstract

Jeneponto Regency in South Sulawesi possesses significant wind potential, making it an ideal location for the development of Wind Power Plants (WPP). However, these WPPs are intermittent due to the inconsistent nature of wind energy, presenting challenges that affect the performance and efficiency of turbines in generating electricity. Therefore, this study aims to evaluate the performance of the SWT-3.6-130 wind turbines at the Tolo 1 WPP in Jeneponto to determine their capability in converting wind energy into electrical energy at specific wind speeds. The evaluation results indicate that the performance of the SWT-3.6-130 wind turbines at the Tolo WPP in February 2022 was not optimal. The maximum output power generated by these turbines approached the maximum capacity of 3.6 MW, with Turbine 06 producing 3.57 MW at a wind speed of 13.07 m/s, Turbine 09 producing 3.57 MW at a wind speed of 12.27 m/s, and Turbine 013 producing 3.58 MW at a wind speed of 12.11 m/s. Although the power generated was close to the maximum capacity, the performance variation among turbines indicates the need for further evaluation to address factors reducing efficiency. Power coefficient analysis shows that Turbine T13 exhibited the best performance, with the fewest instances of power coefficient values not meeting standards. This study provides crucial insights for improving performance and preventing failures at the Tolo WPP in the future.
Development of a Color-Based Image Recognition System for Robotic Sorting and Picking Sidehabi, Sitti Wetenriajeng; Azis, Muhammad Fadli; Asbar, Muhammad
INTEK: Jurnal Penelitian Vol 11 No 2 (2024): October 2024
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/intek.v11i2.5009

Abstract

This research presents the development of an automated object sorting and picking system using a robotic arm controlled by colour-based image recognition. The system is designed to enhance efficiency and accuracy in manufacturing processes by eliminating the need for manual sorting. A Dobot Magician robotic arm, an Arduino microcontroller, a conveyor belt, a photoelectric sensor, and a camera are integrated to achieve this goal. Colour segmentation is implemented using the HSV colour space, enabling the system to accurately classify objects based on colour. Experimental results demonstrate the system's ability to successfully sort objects of three colours in a random sequence with 100% accuracy over ten trials.
PENERAPAN CHATGPT DAN DRAW.IO UNTUK OTOMATISASI FLOWCHART MENGGUNAKAN MERMAID CODE Sidehabi, Sitti Wetenriajeng; Gani, Hamdan; Lutfi
Hexagon Vol 6 No 1 (2025): HEXAGON - Edisi 11
Publisher : Fakultas Teknologi Lingkungan dan Mineral - Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36761/hexagon.v6i1.5153

Abstract

This research examines the potential of automating flowchart creation by combining ChatGPT, an advanced language model, and Draw.io, an intuitive diagramming tool. The process begins with inputting a workflow description into ChatGPT, which generates Mermaid code to be converted into a visual flowchart in Draw.io. This approach was tested in discrete manufacturing systems courses, where students often struggle to design flowcharts for complex processes. The study is categorized as development research and involves needs analysis, system design, implementation, testing, and evaluation. Results indicate that this method significantly reduces the time and effort needed to create flowcharts, particularly for students without an IT background. Although manual adjustments are still required to meet certain standards, the offered automation provides a solid foundation for further development. The integration of ChatGPT and Draw.io has the potential to enhance understanding of complex systems across various fields, allowing students to focus on analysis and problem-solving rather than time-consuming diagram creation.
Co-Authors Ahmad Rosyid Akbar, Zainal Asbar, Muhammad asri, andarini Asyraful Insan Asry Aulani, Tiara Hamdan Gani Irfan, Alfius Latif, Muh. Ardiansyah Lutfi M. Hamka Kadir Muammar Muhammad Fadli Azis Muhammad Thahir Mutmainnah Mutmainnah Nirmalasari Rahman Rachma Rachma Rizal, Muh Rizman Saiful Ashar Sofyan Sofyan St. Nurhayati Djabir Thaha, Sarma Wahidah Yuriadi