Perancangan Sistem Sortasi Warna Sebagai Media Pembelajaran Otomasi Berbasis Internet of Things (IoT)

Revanza, Agum Surya and , Ir. Ratnanto Fitriadi, S.T., M.T.) (2026) Perancangan Sistem Sortasi Warna Sebagai Media Pembelajaran Otomasi Berbasis Internet of Things (IoT). Skripsi thesis, Universitas Muhammadiyah Surakarta.

	PDF (Naskah Publikasi) Naskah Publikasi_Perpus UMS_D600220213_Agum Surya Revanza.pdf Download (833kB)
	PDF (Surat Pernyataan Publikasi) SURAT PERNYATAAN PUBLIKASI_D600220213_Agum Surya Revanza.pdf Restricted to Repository staff only Download (364kB)

Abstract

Advances in industrial automation technology require the availability of learning materials capable of realistically representing industrial processes. One process widely used in industry is the sorting system in the quality control stage. This study aims to design and build an Internet of Things (IoT)-based automation learning medium using a color sorting system equipped with a conveyor, a TCS34725 color sensor, a 4-Degree-ofFreedom (DOF) robotic arm, and an ESP32 microcontroller. The research method used is reverse engineering to identify system requirements based on the learning tools already available at the Industrial Engineering Automation Laboratory of Muhammadiyah University Surakarta. The results of the identification were used as the basis for the design process, prototype creation, and system development. Testing was conducted on the sensor’s ability to identify object colors, the success of the sorting process, and an evaluation of the learning medium’s feasibility. Test results show that the TCS34725 sensor is capable of identifying object colors with a 100% success rate, and the sorting system as a whole also achieved a 100% success rate. Statistical analysis using the Shapiro-Wilk test and the Independent Samples t-test yielded a significance value of 0.000 (<0.05), indicating a significant difference in sensor response time between green objects and non-green objects. The evaluation results from a questionnaire administered to 7 respondents yielded a feasibility rating of 94.48%, classified as “highly feasible.” Based on these results, the developed education learning is deemed capable of representing the industrial sorting process and is suitable for use as a practical tool for IoT-based industrial automation.

Item Type:	Thesis (Skripsi)
Uncontrolled Keywords:	Internet of Things, Media Pembelajaran, Otomasi Industri, Reverse Engineering, Robot Arm, Sistem Sortasi Warna.
Subjects:	T Technology > TI Industrial Engineering T Technology > TI Industrial Engineering > Quality Control T Technology > TI Industrial Engineering > Otomasi, Robot, Mesin Pabrik
Divisions:	Fakultas Teknik > S1 Teknik Industri
Depositing User:	AGUM SURYA REVANZA
Date Deposited:	01 Aug 2026 04:31
Last Modified:	01 Aug 2026 04:31
URI:	http://eprints.ums.ac.id/id/eprint/146622

Actions (login required)

View Item