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All Journal REKAYASA Jurnal Abdi: Media Pengabdian Kepada Masyarakat International Journal of Marine Engineering Innovation and Research
Ii Munadhif
Politeknik Perkapalan Negeri Surabaya
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Physics Social Sciences Transportation Other

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Pengenalan PLC untuk Meningkatkan Kemampuan Logika Asesmen Kompetensi Minimal (AKM) Siswa SMAN 1 Jogorogo Isa Rachman; Muhammad Basuki Rahmat; Adianto Adianto; Ii Munadhif; Ryan Yudha Adistira
Jurnal ABDI: Media Pengabdian Kepada Masyarakat Vol. 7 No. 1 (2021)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/ja.v7n1.p147-151

Abstract

Asesmen Kompetensi Minimal (AKM) merupakan salah satu asesmen nasional yang akan digunakan pada tahun 2021 oleh Kementerian Pendidikan dan Kebudayaan untuk menggantikan ujian nasional tingkat SMA. AKM fokus mengukur kemampuan literasi dan numerikal melalui kemampuan logika dan pemahaman baca siswa. Berdasarkan laporan hasil tes PISA pada tahun 2019, kedua aspek kompetensi ini menjadi masalah mendasar siswa di Indonesia. Untuk memicu peningkatan kemampuan logika siswa SMAN 1 Jogorogo, maka diberikan pengetahuan tambahan yang tidak tercantum dalam kurikulum. Salah satunya melalui kegiatan pengenalan PLC yang merupakan perangkat pemrograman berbasis logika. Kegiatan ini juga mampu meningkatkan kompetensi siswa dalam literasi digital, teknologi dan manusia pada era revolusi industri 4.0 karena PLC banyak digunakan dibidang otomasi industri. Kegiatan dilaksanakan secara daring melalui media interaktif karena pada kondisi pandemi COVID-19. Dari pelaksanaan kegiatan ini, didapatkan hasil quiz peserta pada setiap pokok materi menunjukkan hasil yang cukup memuaskan dengan nilai rata-rata 74 dan hasil test peserta pada akhir kegiatan juga menunjukkan hasil yang cukup memuaskan dengan nilai rata-rata 76. Selain itu, dari hasil kuisioner peserta sebagai bentuk umpan balik pelaksanaan kegiatan menunjukkan hasil yang baik. Dengan adanya kegiatan ini, PLC dapat dijadikan sebagai salah satu kegiatan ekstrakurikuler untuk meningkatkan kompetensi siswa SMAN 1 Jogorogo.
Kontrol Proportional Integral Derivative (PID) Sebagai Penstabil Tegangan pada Pembangkit Listrik Tenaga Hybrid Muhammad Arif Al Aziz; Edy Prasetyo Hidayat; Ii Munadhif
Rekayasa Vol 15, No 3: Desember 2022
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v15i3.16384

Abstract

Around 66% of power plants in Indonesia are still sourced from coal and oil. On the other hand, Indonesia is rich in renewable energy potential but still has minimal utilization. Furthermore, the voltage at power plants that are small and less stable is also often a nuisance. Thus, an innovative hybrid, solar and hydroelectric power plant with a PID (Proportional Integral Derivative) based voltage stabilizer was created. PID-based voltage stabilizer control is generated in the form of PWM (Pulse Width Modulation). The results obtained in this study are PID control can produce the lowest voltage of 12.78 V and the highest voltage of 13.96 V with a setpoint of 13.4 V. The power generated from solar, hydro, and hybrid power plants is 11.8 Watts, 9.4 Watts, and 14.85 Watts. As for Charging the Battery, an increase of 2.72 V was obtained in 24 hours. As for the storage side, the Battery can supply a 15 watt incandescent lamp for 8 hours 55 minutes while leaving 20% of the total capacity.
The Integration of Supervisory Control and Data Acquisition (SCADA) on the Crushing and Barge Loading Conveyor Systems Imam Sutrisno; Ihza Anfasa Dua Nurhidta; Ii Munadhif; Edy Prasetyo Hidayat; Joko Endrasmono; Projek Priyonggo; Tri Mulyatno Budhi Hartanto
International Journal of Marine Engineering Innovation and Research Vol 8, No 1 (2023)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v8i1.15472

Abstract

The utilization of the Crushing and Barge Loading Conveyor (BLC) systems is important in coal processing. A crushing system is required as a tool for the process of crushing coal into smaller sizes and then transferring it to the stockpile. While a BLC system is needed to transport coal from the stockpile to the barge. In general, the control and supervision systems for crushing and BLC systems are carried out separately by two operators. However, the distance between two operators causes a time lag information. In this research, we create a Supervisory Control and Data Acquisition (SCADA) system with the type of Multiple Programmable Logic Controller (PLC) on the Crushing and BLC systems using Profinet communication integrated by two PLCs with one Human Machine Interface (HMI) and WinCC. The system is equipped with real-time data, automatic control, and online surveillance with smartphones via the S7APP application. The error resulting from the reading of each component by the HMI and smartphone reaches 0%, while for automatic control, the system works very well, having a success rate of 100%.
Klasifikasi Gelombang Otot Lengan Pada Robot Manipulator Menggunakan Support Vector Machine Muhammad Ja'far Ubaidillah; Ii Munadhif; Noorman Rinanto
Rekayasa Vol 12, No 2: Oktober 2019
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (547.996 KB) | DOI: 10.21107/rekayasa.v12i2.5406

Abstract

Teknologi robotika semakin berkembang. Banyak orang berinovasi untuk membantu aktivitas mereka, diantaranya membuat robot manipulator untuk mengambil barang di tempat berbahaya atau memindah barang dengan presisi yang sangat tinggi. Pada penelitian ini telah dirancang robot manipulator untuk membantu pasien yang diamputasi pergelangan tangannya agar dapat memegang dan tidak memegang. Sensor Electromyography (EMG) dapat merekam aktivitas listrik yang dihasilkan oleh otot rangka dalam bentuk sinyal yang mempresentasikan gerakan otot. Pada penelitian ini, elektromiogram diekstraksi untuk mendapatkan fitur Root Mean Square (RMS) dan Mean Absolute Value (MAV) kemudian diklasifikasi menggunakan Support Vector Machine (SVM). Metode SVM dipilih karena mampu menemukan hyperplane terbaik sebagai pemisah. Pengendali yang digunakan adalah Arduino yang memerintahkan motor servo untuk menggerakkan robot manipulator sesuai dengan hasil klasifikasi. Penerapan metode Support Vector Machine (SVM) yang bertipe linier memiliki akurasi yang cukup baik dengan keberhasilan 80% pada pengujian dengan subjek yang telah diambil data sampel dan keberhasilan 60% pada pengujian dengan subjek yang tidak diambil data sampel.Classification of Muscle Wave Arm on Manipulator Robot Using Support Vector Machine ABSTRACTRobotics technology is growing. Many people innovate to help their activities, including making manipulator robots to take items in dangerous places or move items with very high precision. In this study a manipulator robot was designed to help patients who amputated their wrists to grip and un-grip. Electromyography (EMG) sensors can record electrical activity produced by skeletal muscles in the form of signals that present muscle movements. In this study, the electromyogram was extracted to get the Root Mean Square (RMS) and Mean Absolute Value (MAV) features then classified using Support Vector Machine (SVM). The SVM method was chosen because it was able to find the best hyperplane as a separator. The controller used is Arduino which instructs the servo motor to move the manipulator robot according to the classification results. The application of the Support Vector Machine (SVM) method which has a linear type has a fairly good accuracy with 80% success in testing with subjects who have taken sample data and 60% success in testing with subjects who are not taken sample data.Keywords: EMG Sensor, Arm Muscle, MAV, RMS, SVM, Classification.
Klasifikasi Gerakan Tangan Menjadi Suara Menggunakan Neural Network Muhammad Arifan Lizamanihi; Ii Munadhif; Mohammad Abu Jami'in
Rekayasa Vol 13, No 3: December 2020
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v13i3.6614

Abstract

Co-Authors Adianto Adianto Edy Prasetyo Hidayat Ihza Anfasa Dua Nurhidta Imam Sutrisno Joko Endrasmono Mohammad Abu Jami'in Muhammad Arif Al Aziz Muhammad Arifan Lizamanihi Muhammad Basuki Rahmat Muhammad Ja'far Ubaidillah Noorman Rinanto Projek Priyonggo Ryan Yudha Adistira Tri Mulyatno Budhi Hartanto