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All Journal PROCEEDING IC-ITECHS 2014 JOIN (Jurnal Online Informatika) JOIV : International Journal on Informatics Visualization Jurnal Informatika Universitas Pamulang Applied Information System and Management JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Teknik Informatika (JUTIF) Jurnal Teknologi dan Sistem Tertanam Journal Social Science And Technology For Community Service Journal of Soft Computing Exploration Jurnal Pendidikan dan Teknologi Indonesia Jurnal Telematics and Information Technology (TELEFORTECH) Jurnal Locus Penelitian dan Pengabdian Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Informatika: Jurnal Pengembangan IT
Styawati, Styawati
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Aerospace Engineering Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics

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Journal : Journal of Soft Computing Exploration

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IoT-based implementation of rickshaws for real-time monitoring and measuring the weight of cattle Satrya, Alan; Styawati, Styawati; Ismail, Izudin; Alim, Syahirul
Journal of Soft Computing Exploration Vol. 5 No. 1 (2024): March 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i1.265

Abstract

In the era of modern agriculture that is increasingly dependent on technology, livestock management has become crucial to increasing efficiency and productivity. An important aspect in livestock management is providing appropriate feed to fattening cattle. Manual monitoring of feed weight is often complex and prone to errors, which can have a significant impact on operational efficiency and result in losses. Accuracy in monitoring feed weight is the key to maintaining optimal health and growth of cattle. Internet of Things (IoT) technology is emerging as an innovative solution to overcome these challenges. The use of Angkong load cells, a tool connected to IoT, allows automatic monitoring of feed weight with a high level of precision. The test results show an error rate close to zero, with a Mean Absolute Percentage Error (MAPE) of around 0.158%, making the Angkong load cell a reliable tool. With this capability, farmers can monitor cow feed weight in real-time with minimal error rates. This not only increases the operational efficiency of the farm but also optimizes the health and growth of livestock more efficiently, having a positive impact on overall farm productivity. The aim of this research is to monitor the amount of feed given to cows with an adequate level of accuracy. Rickshaw load cells can be well suited for this use due to their ability to handle relatively large weights with fairly good accuracy, but do not necessarily have the level of precision required in laboratory measurements or the pharmaceutical industry.
Automation of aquaponics systems through integration of RTC modules, turbidity sensors, and water level sensors Jaya, Dicky Suman; Styawati, Styawati; Syahirul, Alim
Journal of Soft Computing Exploration Vol. 4 No. 4 (2023): December 2023
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v4i4.267

Abstract

Automation of aquaponics systems is key in increasing agricultural efficiency and productivity. A system considered an innovative method of sustainable food production that combines fish farming with agriculture simultaneously. The problem that often occurs is crop failure, due to the lack of technology that can monitor automatically, so that farmers experience losses as a result of fish and plant growth does not thrive, and problems in urban areas that require land for planting and fish farming due to limited land in urban areas. There is another problem with the lack of accurate timing and monitoring of water quality in aquaponics. The purpose of this research is to implement an IoT system in aquaponics that is connected to various sensors, such as Turbidity sensors, Water Level sensors, and RTC Modules. To monitor water quality conditions in tilapia habitat and accurate time measurement to provide fish feed automatically so as to improve fish health and growth and support better and consistent yields. The findings of this study show that the implementation of IoT systems in aquaponics can overcome environmental monitoring and control problems effectively. Using the integration of RTC modules, turbidity sensors, and water level sensors effectively improves the automation of aquaponics systems. This optimized system provides better monitoring of environmental conditions, reduces reliance on manual maintenance, and increases overall productivity. It helps increase tilapia growth and plant productivity in a modern aquaponics system. This research demonstrates the great potential of IoT technology in increasing efficiency and productivity in aquaponics aquaculture, so that it can push the fisheries sector towards a more advanced and competitive direction. So the main conclusion is expected that this automation can increase the productivity of ecosystem balance, and can face food security challenges and move towards more environmentally friendly solutions, towards effective management in the future.
Co-Authors Adrian, Qodhli Jafar Afredha, Arya Agustian, Rezi Dwi Al Faroqi, M. Ibnu Aldo Pramana Amanda, Feby Andi Nurkholis Andika, Rio Andrey Ferriyan, Andrey Anggita, Rizki Devi Apriyadi, Chandra Ardani, Ravi Ari Tri Arfat, Muhammad Fadilah Asyad, Chafidz Azahra, Maulida Bagas Setiawan, Bagas deviana, lyla putri Dewa, Ananda Asmoro Edistira, Khusnul Febriyansyah, Akhmad Febriyo Hepri, Alfian I Komang Arya Ganda Wiguna Ida Bagus Gede Sarasvananda Indra Kurniawan Indraningtyas, Lathifa Ismail, Izudin Jaya, Dicky Suman Jupriyadi, Jupriyadi Khoiri, Rizky Dafa Kurniawan, Medy Dwi Kuswara, Muhammad Shidiq Mahendra, Anton Pranata, Rangga Prastowo, Agung Tri Pratama, Ariski Qadhli Jafar Adrian Rahayu, Usman Puji Rifai, Jefri Andri Rizki Dalimunthe, Ernando S. Samsugi Saputra, Dian Tri Saputra, Hendi Satrya, Alan Suhartanto, Alvi Syahirul Alim Syahirul, Alim Wijaya, Rio Yudha, Sandy Yulistiani Yulistiani, Yulistiani Yuri Rahmanto