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All Journal INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) Hexagon Majalah Teknik Industri
Mutmainnah
Politeknik ATI Makassar
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Optimizing Economic Dispatch through Web-based Applications using Lambda Iteration Algorithm for Efficient Power System Operation Muhammad Fadli Azis; Mutmainnah; Lutfi; Julianti Habibuddin
INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) Vol. 6 No. 1 (2023)
Publisher : Department of Electrical Engineering, Faculty of Engineering, Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/inajeee.v6n1.p1-8

Abstract

This research presents the development of an online economic dispatch web application using the lambda iteration method. The proposed method is implemented through a systematic process of problem formulation, optimization method selection, application design, and testing. The web application is created using MATLAB Web Apps and tested using generation data from the IEEE 30 bus system. The results demonstrate that the developed web application operates effectively and fulfills the desired specifications. Users can access the application via web browsers without the need for MATLAB installation on their devices. The study concludes that the developed economic dispatch web application can serve as a valuable tool for enhancing the efficiency and effectiveness of economic dispatch processes. The application can be further optimized by incorporating more comprehensive and user-friendly features.
Penggunaan Aplikasi SMS Gateway dan Solar Cell untuk Membasmi Hama pada Tanaman Bawang Sitti Wetenriajeng Sidehabi; Mutmainnah; Nirmalasari Rahman
Majalah Teknik Industri Vol 29 No 1 (2021): Majalah Teknik Industri Juni 2021
Publisher : Unit Penelitian dan Pengabdian Masyarakat (UPPM) Politeknik ATI Makassar

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Abstract

Bawang merah merupakan sayuran dengan kandungan gizi yang tinggi dan mempunyai nilai ekonomi yang tinggi. Bawang merah ini menpunyai arti yang tinggi bagi masyarakat karena digunakan sebagai pelengkap bumbu masak dan dikonsumsi sehari-hari. Tujuan penelitian ini adalah untuk merancang dan membuat sistem monitoring pembasmi hama menggunakan cahaya lampu pada kebun bawang berbasis sms gateway guna memudahkan petani dalam pengontrolan lampu penerangan pada kebun bawang. Penelitian ini adalah penelitian eksperimental dengan merancang dan membuat sebuah alat yang dapat membasmi hama pada kebun bawang berbasis SMS Gateway dengan penerangan lampu dengan sumber listrik solar cell. Adapun hasil penelitian ini adalah sistem ini dapat digunakan untuk menjebak hama yang aktif dimalam hari dengan cahaya lampu sebagai pemikat hama serta dapat memberikan informasi melalui pesan SMS. Pengujian pada hari pertama jumlah hama yang tertangkap 60 ekor, hari kedua 57 ekor, hari ketiga 48 ekor, hari keempat 40 ekor, dan hari kelima 35 ekor.
PENERAPAN ORANGE DATA MINING UNTUK PEMBELAJARAN SISTEM MANUFAKTUR DISKRIT PADA KASUS KLASIFIKASI DAN KLASTERISASI GAMBAR HEWAN BERBASIS MACHINE LEARNING Sukriyah Buwarda; Mutmainnah; Lutfi
Hexagon Vol 6 No 2 (2025): Vol. 6 No. 2 (2025): HEXAGON - Edisi 12
Publisher : Fakultas Teknologi Lingkungan dan Mineral - Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36761/hexagon.v6i2.5144

Abstract

Politeknik ATI Makassar has introduced technologies such as Artificial Intelligence, Internet of Things, and Big Data Analytics in the Discrete Manufacturing Systems course. This research focuses on the application of Data Science using the Orange Data Mining application for the classification and clustering of animals. The adopted experimental method involves controlling variables by following the CRISP-DM methodology. Evaluation results indicate that the logistic regression model is the best, with an AUC accuracy of 1 and a precision of 0.962. Clustering resulted in two clusters: C1 for cats and C2 for cows, with a silhouette score of 0.145. This research demonstrates the effectiveness of the Orange Data Mining application in teaching discrete manufacturing systems based on machine learning.
Co-Authors Julianti Habibuddin Lutfi Lutfi Muhammad Fadli Azis Nirmalasari Rahman Sitti Wetenriajeng Sidehabi Sukriyah Buwarda