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JTIM : Jurnal Teknologi Informasi dan Multimedia
Published by Puslitbang Sekawan Institute Nusa Tenggara
ISSN : 27152529     EISSN : 26849151     DOI : https://doi.org/10.35746/jtim.v2i1
Core Subject : Science,
Computer Science & IT
Cakupan dan ruang lingkup JTIM terdiri dari Databases System, Data Mining/Web Mining, Datawarehouse, Artificial Integelence, Business Integelence, Cloud & Grid Computing, Decision Support System, Human Computer & Interaction, Mobile Computing & Application, E-System, Machine Learning, Deep Learning, Information Retrievel (IR), Computer Network & Security, Multimedia System, Sistem Informasi, Sistem Informasi Geografis (GIS), Sistem Informasi Akuntansi, Database Security, Network Security, Fuzzy Logic, Expert System, Image Processing, Computer Graphic, Computer Vision, Semantic Web, Animation dan lainnya yang serumpun dengan Teknologi Informasi dan Multimedia.
Arjuna Subject : -
Articles 152 Documents
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Media Pengenalan Peti Kemas Logistik Menggunakan Augmented Reality Berbasis Android Vio Kartiko; Puteri Noraisya Primandari
JTIM : Jurnal Teknologi Informasi dan Multimedia Vol 5 No 2 (2023): August
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v5i2.369

Abstract

Containers are the most important part in the world of logistics, where the container is a medium for sending cargo or goods from the sender to the recipient. A container is a square-shaped box that is specially carved with a certain size made of iron or aluminum with a door on one side, the box has an important role in the export and import of goods. The study developed the Augmented Reality app using the Markerless and Markerbased methods to visualize Android-based 3D Logistics Box objects. The method used in this application development is the Software Development Life Cycle model Waterfall. Logistic container identification materials that will be used as 3D objects on applications are: dry container, isotank container, open top container, open side container, reefer container and flatrack container. The result of the development of this app is a container recognition media that runs on the Android smartphone using Augmented Reality technology. Based on the results of functionality testing / blackbox testing, it can be concluded that the application runs according to its function and the input/output process successfully produces a valid output. The marker accuracy test obtained a total percentage level of precision of 66.6%, and the markerless accurate test obtains a total level of accuration of 100%. Usability testing by conducting a questionnaire on 30 respondents could conclude all aspects of usability, functionality, efficiency and portability obtain a percentage score of Likert’s scale of 91%.
Implementasi Sistem Monitoring Tanaman Hidroponik Menggunakan Metode Fuzzy Sugeno Tegar Palyus Fiqar; Fitriani Fitriani; Riska Kurniyanto Abdullah
JTIM : Jurnal Teknologi Informasi dan Multimedia Vol 5 No 2 (2023): August
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v5i2.372

Abstract

Farming using hydroponic systems has emerged as an effective alternative to address the problem of limited agricultural land. However, hydroponic farming requires strict maintenance and control. In light of these challenges, the development of monitoring technology is necessary to assist in monitoring and controlling hydroponic systems. The development of a monitoring system is carried out to address the challenges of maintenance and control in hydroponic farming through the development of effective and accurate monitoring technology, thus enhancing the overall productivity and success of hydroponic plant cultivation. This study aims to develop a monitoring system using Arduino Mega 2560, Wemos D1 R2, E201 sensor, DHT22 sensor, HC-SR04 sensor, and BH1750 sensor. In this research, the fuzzy logic method was applied to generate outputs for the water pump actuator, pH up pump, and pH down pump. The HC-SR04 and E201 sensor data served as fuzzy inputs, while the Arduino Mega 2560 functioned as the fuzzy data processor, and the Wemos D1 R2 was responsible for sending data to the server via the internet. The data successfully stored in the server's database would be displayed on the monitoring dashboard. The HC-SR04 sensor testing results showed an average %error of 0% and an accuracy of 100%. The E201 sensor exhibited an average %error of 0.07% and an accuracy of 99.33%. The DHT22 sensor had an average %error of 0.05% and an accuracy of 99.49% for temperature data, while for humidity data, it had an average %error of 2.58% and an accuracy of 75.23%. The BH1750 sensor had an average %error of 0.13% and an accuracy of 99.66%. The results of this study demonstrate that the hydroponic plant monitoring system using the described devices and methods can be implemented successfully.

Page 16 of 16 | Total Record : 152

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