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All Journal Jurnal Elektronika Telekomunikasi & Computer Hexagon Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Sukriyah Buwarda
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Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Development of DCS SCADA Teaching Module on A Pid-Based Water Level Control Case Using Labview and Factory I/O Lutfi; Sukriyah Buwarda
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol. 12 No. 2 (2022): Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Pusat Penelitian dan Pengabdian Pada Masyarakat Sekolah Tinggi Manajemen Informatika dan Komputer AKBA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (492.285 KB) | DOI: 10.35585/inspir.v12i2.28

Abstract

The DCS SCADA course is one of the latest courses for the 2022 curriculum at Politeknik ATI Makassar. This course has case study-based learning from the industrial world and involves very expensive instrumentation devices for Real Plant, so a Teaching Module with factory i/o was created. This research aims to develop a DCS SCADA Teaching Module based on the Water Level Control case using Labview and Factory I/O. The virtual plant uses a water tank with instruments consisting of two control valves, namely the fill valve and the discharge valve, and two transducers, namely the level meter and the flow meter. To connect the factory I/O to NI Labview, the open protocol Modbus Ethernet is used. Based on the testing results, the calibration for the level measurement has an accuracy of 99.59% and a precision of 0.69 % with the interpolation y = 0.301x -0.536 for a 100 % correlation. For the system response with SP = 150 without disturbance, the PID parameters should be set to Kp = 25, Ti = 0.1, and Td = 0 with a system response consisting of Rise Time = 396 seconds, no Overshoot, Settling Time = 430 seconds, and Steady state error = 0.566 cm. For the system response with SP = 150 with a DV = 50 percent disturbance, the PID parameters should be set to Kp = 25, Ti = 0.1, and Td = 0 with a system response consisting of Rise Time = 382 seconds, no Overshoot, Settling Time = 462 seconds, and Steady state error = 1.469 cm.
PROTOTIPE RUMAH CERDAS BERBASIS IOT Sukriyah Buwarda; Asmawaty Azis; Andita Dani Achmad; Jatur Andrian kristiyanto
Jurnal Elektronika Telekomunikasi & Computer Vol 6, No 1 (2021): April
Publisher : Jurnal Elektronika Telekomunikasi & Computer

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

Abstract

Pemanfaatan teknologi kendali otomatis jarak jauh berbasis internet banyak digunakan sebagai cara memudahkan pengontrolan. Penelitian ini memanfaatkan teknologi smartphone sebagai sistem kendali jarak jauh memanfaatkan jaringan internet sebagai penghubung antara sistem kontrol smartphone dan mikrokontroler wemos D1 ESP 8266 sebagai sistem output dari kendali smartphone, penelitian ini juga memakai sistem input tambahan yaitu sensor cahaya dan RFID. Komponen yang digunakan dalam dalam penelitian ini meliputi : mikrokontroler wemos D1 ESP 8266 sebagai perangkat wifi, relay 8 pin sebagai saklar, solenoid untuk mengunci pintu, motor DC untuk mengoperasikan pagar, modul RFID, modul LDR, rangkaian power supply, dan perngkat smartphone yang digunakan sebagai alat pengontrol melalui aplikasi. Pada penelitian ini dibuat sebuah prototype rumah cerdas yang dapat dikontrol dengan smartphone. Hasil dari percobaan prototype tersebut ditampilkan pada serial monitor mikrokontroler, dan juga dapat dilihat langsung pada perangkat elektronik yang terdapat pada prototype. Dalam percobaan ini tingkat keberhasilan pengiriman 100%  namun terdapat delay yang mengganggu pengiriman data disebabkan oleh kondisi sekitar prototype, delay yang terjadi dalam percobaan antara 0,93 – 3,04 detik.
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 Andita Dani Achmad Asmawaty Azis Jatur Andrian kristiyanto Lutfi Lutfi Mutmainnah