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All Journal Jurnal Informatika dan Teknik Elektro Terapan Jurnal Teknik Elektro dan Komputer TRIAC Infotekmesin Jurnal Elkolind : Jurnal Elektronika dan Otomasi Industri Journal of Computer, Electronic, and Telecommunication (COMPLETE) Jurnal Rekayasa elektrika
Zindhu Maulana Ahmad Putra
Politeknik Perkapalan Negeri Surabaya
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Mechanical Engineering

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Journal : Infotekmesin

 1 
Kontrol Kestabilan Kapal Autonomous Submarine Surface Vehicle Dengan Metode Fuzzy logic Abdul Hafizh Abyan Faruq; Joko Endrasmono; Isa Rachman; Agus Khumaidi; Ryan Yudha Adhitya; Zindhu Maulana Ahmad Putra
Infotekmesin Vol 14 No 2 (2023): Infotekmesin: Juli, 2023
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v14i2.1920

Abstract

The Autonomous Submarine Surface Vehicle is a type of unmanned underwater vehicle. When the ship performs maneuvers, there are large Pitch and Roll motions. This research aims to control the stability of the Autonomous Submarine Surface Vehicle with Fuzzy. The first process is taking Pitch and Roll data followed by the Fuzzification process to change input data with firm values into Fuzzy values. The next stage is Inference by using the rules (if – then) and the Deffuzification process to change the results of the inference stage into output values. The last is the process of stabilizing the ship with a Thruster dc motor. When the system is activated, it has a time of 0.518 seconds faster to steady state than the deactivated system with a roll tilt of (plus) 11°. On the roll tilt of (plus) 20° the highest PWM rotation is 1600µs with a time of 9,342 seconds to steady state and the roll tilt is (plus) 11° with the highest PWM of 1500µs with a time of 4,335 seconds. Based on this research, the Fuzzy Method can control the stability of the Autonomous Submarine Surface Vehicle ship.
Alat Deteksi Suara Gergaji Sebagai Indikasi Awal Terjadinya Penebangan Menggunakan Metode Convolutional Neural Network Ana Surya Ningrum; Adianto; Rini Indarti; Edy Setiawan; Afif Zuhri Arfianto; Zindhu Maulana Ahmad Putra
Infotekmesin Vol 15 No 2 (2024): Infotekmesin, Juli 2024
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v15i2.2304

Abstract

Illegal logging in Indonesia is no small problem, with illegal logging causing damage to forest resources in terms of quantity, quality and ecosystem. Many efforts have been taken by the Indonesian government, but it has not been effective in dealing with this problem, due to limited supervision. From this problem, a chainsaw sound detection system was designed as an early indication of logging activity. This system is equipped with four MAX4466 sound sensors using the Convolutional Neural Network method. This system also uses data processing so that the chainsaw sound can be recognized by the system specifically and can communicate remotely with the use of LoRa RFM95. Thus, the system can identify the sound of the chainsaw with a maximum distance of 50 m, the success accuracy of the CNN model created reaches 97.5%, and can be integrated with WhatsApp in realtime.
Kontrol Kestabilan Kapal Autonomous Submarine Surface Vehicle Dengan Metode Fuzzy logic Abyan Faruq, Abdul Hafizh; Endrasmono, Joko; Rachman, Isa; Khumaidi, Agus; Yudha Adhitya, Ryan; Ahmad Putra, Zindhu Maulana
Infotekmesin Vol 14 No 2 (2023): Infotekmesin: Juli, 2023
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v14i2.1920

Abstract

The Autonomous Submarine Surface Vehicle is a type of unmanned underwater vehicle. When the ship performs maneuvers, there are large Pitch and Roll motions. This research aims to control the stability of the Autonomous Submarine Surface Vehicle with Fuzzy. The first process is taking Pitch and Roll data followed by the Fuzzification process to change input data with firm values into Fuzzy values. The next stage is Inference by using the rules (if – then) and the Deffuzification process to change the results of the inference stage into output values. The last is the process of stabilizing the ship with a Thruster dc motor. When the system is activated, it has a time of 0.518 seconds faster to steady state than the deactivated system with a roll tilt of (plus) 11°. On the roll tilt of (plus) 20° the highest PWM rotation is 1600µs with a time of 9,342 seconds to steady state and the roll tilt is (plus) 11° with the highest PWM of 1500µs with a time of 4,335 seconds. Based on this research, the Fuzzy Method can control the stability of the Autonomous Submarine Surface Vehicle ship.
Alat Deteksi Suara Gergaji Sebagai Indikasi Awal Terjadinya Penebangan Menggunakan Metode Convolutional Neural Network Surya Ningrum, Ana; Adianto; Indarti, Rini; Setiawan, Edy; Arfianto, Afif Zuhri; Ahmad Putra, Zindhu Maulana
Infotekmesin Vol 15 No 2 (2024): Infotekmesin, Juli 2024
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v15i2.2304

Abstract

Illegal logging in Indonesia is no small problem, with illegal logging causing damage to forest resources in terms of quantity, quality and ecosystem. Many efforts have been taken by the Indonesian government, but it has not been effective in dealing with this problem, due to limited supervision. From this problem, a chainsaw sound detection system was designed as an early indication of logging activity. This system is equipped with four MAX4466 sound sensors using the Convolutional Neural Network method. This system also uses data processing so that the chainsaw sound can be recognized by the system specifically and can communicate remotely with the use of LoRa RFM95. Thus, the system can identify the sound of the chainsaw with a maximum distance of 50 m, the success accuracy of the CNN model created reaches 97.5%, and can be integrated with WhatsApp in realtime.
Co-Authors Abdul Hafizh Abyan Faruq Abu Jami’in, Mohammad Abu Jami’in, Mohammad Abu Jami’in Abyan Faruq, Abdul Hafizh Adhitya, Ryan Yudha Adianto Adianto Adiatmoko, Mohammad Fajar Agus Khumaidi Aisyah, Erika Nur Alfitra, Muhammad Dhifa Almunawar, Deni Alrijadjis Alrijadjis Ana Surya Ningrum Anggara Trisna Nugraha Anto, Dwi Rizky Arfianto, Afif Zuhri Asri, Purwidi Bambang Sumantri C. I. Sutrisno Edy Setiawan Endrasmono, Joko Erika Nur Aisyah Faiz Romadloni Gusti Audryadmaja, Anugerah Ekha Hendro Agus Widodo Hendro Agus Widodo, Hendro Agus Ii Munadhif, Ii Ilhan Shanjaya, Mohammad Irfan Joko Endrasmono Khumaid, Agus Lilik Subiyanto Munadhif, Ii’ Nugraha, Anggara Trsina Raimundus Risa Arnestanta Riananda, Dimas Pristovani Rinanto, Noorman Rini Indarti Rini Indarti Ryan Yudha Adhitya Surya Ningrum, Ana Syaiin, Mat Washfil Hasin, Muhammad Dzi Yudha Adhitya, Ryan