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An Implementation of Internet of Things for Digitalization of Kanban Production System Purba, Victor Chris Samuel; Lalujan, Virginia; Phangnesia, Calvin
Jurnal Sistem Cerdas Vol. 7 No. 1 (2024)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v7i1.383

Abstract

Just-In-Time production system in the form of kanban has been implemented in many production processes in order to optimize the production output. Internet of Things (IoT) has been integrated into production system in digitalizing production processes as well as obtaining and gathering real-time information in the factory floor through sensors, actuators, and network. In this study, an application of IoT into kanban and production system was proposed. The proposed electronic kanban system composed of Radio Frequency Identification (RFID) cards and readers, QR code and reader, microcontrollers, digital displays, and server. In this system, the kanban card is replaced by an RFID card. All workstations in the production process are equipped by RFID readers, microcontrollers, and displays to show relevant instructions to the operator. The microcontrollers are connected to a server to send information of the RFID card scanned by them and the time when the card was scanned. The latter information is used for tracing each of the products produced in each of the workstations. The proposed electronic Kanban system was implemented to an assembling process consisting of 7 workstations. The system was able to replace the conventional kanban card with RFID and electronic displays and performing the unit tracing capability.
Prototipe Powered Emergency Resuscitator Berbasis Bag Valve Mask Ghandy, Ghandy; Panggabean, Jayandi; Lalujan, Virginia; Naulid, Maria Anindita; Lawalata, Sanga
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 6 No 4 (2024): Oktober 2024
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v6i4.1587

Abstract

The COVID-19 pandemic proves that healthcare capacity and equipment are not sufficient to handle a pandemic, especially the availability of ventilators. Composed of more than 17.500 islands, 6.000 of which are inhabited, Indonesia’s demographic varies widely from one area to another. Health infrastructure in many areas is minimal, with many having no hospitals but clinics with limited resources/funds and minimally-trained healthcare professionals. The need for domestically produced ventilators is clear. But not only that, there is a need to produce simpler/more economical ventilators that are affordable and simpler to operate. This paper will discuss the basic ventilator (resuscitator), built upon MIT Open Design (used by clinics/smaller hospitals) and was in the last development phase before product testing at Balai Pengamanan Fasilitas Kesehatan (BPFK) Jakarta.
Rancang Bangun Sistem Pemantauan Kebisingan Berbasis IoT pada Jam Tenang di Asrama Mahasiswa Lalujan, Virginia; Prathama, Aditya Heru; Irawan, Jo'el Evander Nathanael; Christopher, Pixel Ariel; Silpinus, Davin Edbert
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 13 No 2: April 2026
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.132

Abstract

  Kesempatan tinggal di asrama selama masa studi membawa banyak manfaat bagi mahasiswa, seperti akses cepat ke fasilitas kampus, pengalaman hidup mandiri dalam komunitas, dan lingkungan yang tenteram untuk mendukung produktivitas akademik. Manfaat tersebut hanya dapat terwujud apabila ketenangan lingkungan asrama terjaga secara konsisten, khususnya pada periode jam tenang (quiet hour) yang diperuntukkan bagi belajar dan istirahat. Namun, pengelolaan kebisingan masih menjadi tantangan yang sering dikeluhkan oleh pamong asrama. Penelitian ini menyajikan rancang bangun sistem pemantauan kebisingan berbasis IoT untuk lingkungan asrama mahasiswa selama jam tenang. Sistem dirancang untuk pemantauan pada tingkat kamar dengan penempatan satu Noise Detection Kit (NDK) per kamar pada skenario target implementasi. NDK merupakan perangkat ringkas dan portabel sehingga memungkinkan implementasi simultan pada banyak titik. Pada tahap realisasi, sistem diimplementasikan secara terbatas pada sepuluh kamar terpilih sebagai sampel untuk memvalidasi kinerja dan fungsionalitas. Sistem mengintegrasikan sound sensor, NodeMCU, serta komunikasi MQTT dan Node-RED untuk visualisasi data melalui web dashboard dan mobile notifications via Telegram. Pada kondisi bising (>55 dB), indikator LED pada dashboard berubah menjadi merah disertai informasi kebisingan, log aktivitas, serta opsi aktivasi buzzer oleh pamong. Kebisingan kontinu lebih dari 5 detik memicu notifikasi otomatis ke ponsel pamong. Sensor dikalibrasi menggunakan Sound Level Meter (SLM) dengan MAE 1,02 dan RMSE 1,44, menunjukkan kinerja deteksi yang handal. Sistem ini memungkinkan pengelolaan kebisingan secara otomatis, objektif, real time, dan kontinu. Dibandingkan perangkat komersial sejenis atau SLM, sistem yang dikembangkan menawarkan solusi yang lebih ekonomis dengan skalabilitas yang lebih tinggi, serta peningkatan efisiensi seiring bertambahnya luas asrama yang dikelola.   Abstract Living in student dormitory during study period provides many benefits, including quick access to campus facilities, independent living experience within communities, and calm environment that supports academic productivity. These benefits can only be realized if dormitory environment remains consistently quiet, particularly during quiet hours intended for studying and resting. However, noise management remains a challenge frequently reported by dormitory supervisors. This study presents design and development of an IoT-based noise monitoring system for student dormitories during quiet hours. It is designed for room-level monitoring by deploying one Noise Detection Kit (NDK) per room in the target scenario. The NDK is compact and portable, enabling simultaneous deployment at multiple monitoring points. During implementation phase, the system was deployed on a limited scale in ten selected rooms as samples to validate system performance and functionality. The system integrates sound sensor, NodeMCU, MQTT, and Node-RED to enable data visualization through web-based dashboard and mobile notifications via Telegram. When noise levels exceed 55 dB, the dashboard LED indicator turns red and displays noise information, activity logs, and an option for supervisors to activate a buzzer. Continuous noise lasting more than 5 seconds triggers automatic notifications to the supervisor’s phone. The sensor was calibrated using a Sound Level Meter (SLM), achieving MAE of 1.02 and RMSE of 1.44, indicating reliable noise detection performance. The system enables automatic, objective, real-time, and continuous noise management. Compared to commercial devices or standalone SLMs, the proposed system is more economical and scalable, with increasing efficiency as dormitory area expands.