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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Informatik : Jurnal Ilmu Komputer Jurnal Teknologi Terapan JTRM (Jurnal Teknologi dan Rekayasa Manufaktur) Journal of Energy and Electrical Engineering (JEEE) Madaniya Jurnal Puan Indonesia Tedc SEMNASTERA (Seminar Nasional Teknologi dan Riset Terapan) Jurnal Polimesin
Sandy Bhawana Mulia
Politeknik Manufaktur Bandung
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Rancang Bangun Prototipe Automated Guided Vehicle Berbasis Mikrokontroler Sandy Bhawana Mulia; Wahyu Adhie Candra; Mohammad Faisal
Jurnal TEDC Vol 17 No 1 (2023): JURNAL TEDC
Publisher : UPPM Politeknik TEDC Bandung

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

Abstract

Autonomatic guided vehicle (AGV) merupakan salah satu jenis robot pengangkut barang yang memiliki roda dan dapat berpindah tempat dengan panduan sensor (Abdurrahman et al., 2020). Beragam bentuk lintasan yang akan dilalui oleh robot akan mempengaruhi kecepatannya. Dalam penelitian ini menggunakan mikrokontroler robotdyn dan mengunakan sistem kendali PID untuk mengatur kecepatan dua buah motor dc yang berdampak pada posisi robot agar selalu mengikuti jalur dimana umpan balik yang digunakan yaitu sensor IR 5 channel sebagai pembaca jalur. Digunakan juga RFID untuk mengidentifikasi sektor a dan sektor b. Dari hasil pengujian AGV ini dapat mengikuti jalur yang telah ditentukan, dapat berhenti di tiap stasiun untuk proses pemindahan material dan juga dapat memenuhi faktor keamanan seperti berhenti ketika terdapat halangan di depannya.
Production monitoring system using SCADA-IIOT for improving efficiency and productivity on stamping machines Gun Gun Maulana; Sandy Bhawana Mulia; wahyudi Purnomo; Hadi Supriyanto
Jurnal Polimesin Vol 24, No 2 (2026): April
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v24i2.8713

Abstract

The manufacturing industry plays a crucial role in the global economy, requiring continuous improvements in efficiency and productivity. Digital transformation through Supervisory Control and Data Acquisition (SCADA) systems has enabled better monitoring and control of production processes. However, recent industrial challenges demand more advanced solutions, particularly through the integration of Industrial Internet of Things (IIoT) technologies. This research proposes a web-based SCADA–IIoT production monitoring system for stamping machines that supports real-time machine monitoring, reliable communication, and automated abnormal event notifications. The system architecture integrates sensors for monitoring critical production parameters, SCADA software for visualization and control, and a web-based interface for remote monitoring. System security and communication reliability are ensured through appropriate protocol implementation. A case study conducted in a manufacturing environment evaluates the performance of the proposed system. Experimental results show that the system achieves a data integrity level of 98.99% during monitoring operations. The system is also capable of storing machine condition history and operational activities with a storage capacity of 604,800 data points and an average storage delay of 45.50 ms. Additionally, an error notification feature integrated with the Telegram messaging platform provides automated alerts with an average message latency of 445.99 ms. The proposed system demonstrates the potential of SCADA–IIoT integration to enhance production monitoring, improve decision-making accuracy, and increase operational efficiency in manufacturing environments.
Perancangan Mesin Pemilah Sampah Rumah Tangga Organik dan Anorganik Setyawan Ajie Sukarno; Sandy Bhawana Mulia; Abyanuddin Salam; Yuliadi Erdani; Kamsudin
JTRM (Jurnal Teknologi dan Rekayasa Manufaktur) Vol 5 No 2 (2023): Volume: 5 | Nomor: 2 | Oktober 2023
Publisher : Pusat Penelitian dan Pengabdian kepada Masyarakat (P3M) Politeknik Manufaktur Bandung (Polman Bandung)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.48182/jtrm.v5i1.124

Abstract

Waste is a real problem and will continue to increase as the human population grows. The increase in waste will have a negative impact on the environment and health if not managed properly. The process of handling household waste is still limited to collection and disposal carried out by the local Sanitation Service. In this case, recycling household waste is needed to reduce environmental impacts and improve economic and social welfare in the community. However, the problem that is often faced for this recycling process is the initial processing which includes sorting and crushing waste. This research aims to produce an efficient and appropriate household waste sorting machine design, this waste sorting machine design is useful for separating household waste that is organic and inorganic.
Implementation Of Kalman Filter at IoT Animal Weighing Nuryanti; Danu Jaya Saputro; Ismail Rokhim; Hendy Rudiansyah; Sandy Bhawana Mulia; Wahyu Adhie Candra; M Wahyu Firmansyah
Informatik : Jurnal Ilmu Komputer Vol 22 No 2 (2026): August 2026
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v22i2.13604

Abstract

Animal weighing is an important aspect of livestock farming, as it plays a role in feed determination, growth monitoring, and economic evaluation. However, accuracy is often compromised by animal movement, which causes fluctuations in sensor data and unstable readings, making it difficult to determine the actual weight. To address this, this study proposes an IoT-based animal weighing system equipped with a Kalman Filter algorithm to reduce noise and improve measurement stability. The system utilizes four 200 kg load cells, connected via HX711 and controlled by an ESP32 microcontroller, which is supported by an RFID module for automatic animal identification, an RTC for time logging, and Firebase as a cloud storage platform with real-time visualization capabilities through Node-RED. Experimental for moving object weighing results show that the Kalman Filter reduces measurement errors to less than 2% and maintains the coefficient of variation below 2%, demonstrating high precision and stability. Therefore, this system is proven effective for automatic, accurate, and remote-accessible animal weight monitoring, with strong potential for implementation in modern livestock industries.
Co-Authors Abdur Rohman Harits Martawireja Abyanuddin Salam Achmad Ibnu Rosid Ade Gafar Abdullah, Ade Gafar Adhitya Sumardi Sunarya Aris Budiyarto Danu Jaya Saputro Dede Sujana Fitria Suryatini Gun Gun Maulana Hadi Supriyanto Hasbullah Hasbullah Hendy Rudiansyah Ilham Rafif Mochamad Ismail Rokhim Kamsudin M Wahyu Firmansyah Mindit Eriyadi Mochammad Rizky Febrian Mohammad Faisal Muhammad Hanif Robbani Muhammad Yugi Wibowo Nedy Arif Cahyadi Nur Wisma Nugraha Nuryanti Nuryanti Nuryanti Permata, Nia Nuryanti Reffi Fachrushidieq Alfian Ridwan Ridwan Rifa'i, Afaf Fadhil Rizky Akbar Suryana Sarosa Castrena Abadi Setyawan Ajie Sukarno Siti Aminah Wahyu Adhie Candra Wahyudi Purnomo Yuliadi Erdani, Yuliadi