Directorate of Vocational Studies – Vocational higher education research continues to be encouraged to produce various appropriate technological innovations to help overcome problems in society. One of them is an innovation based seed identification tool machine learning which was developed by Sidiq Syamsul Hidayat, lecturer and researcher from Semarang State Polytechnic (Polines).
Sidiq and his team succeeded in developing a rice-based seed identification tool machine learning which can help farmers to increase agricultural productivity and support national strategic programs in the field of food. This tool is able to identify the quality of rice seeds more quickly and accurately.
“Previously, the process of identifying the quality of rice seeds by farmers was usually done manually. So, this process makes the time needed for identification quite long and not always accurate," said Sidiq.
According to Sidiq, the tool he has developed can help farmers identify the quality of rice seeds with a high degree of accuracy. In addition, the identification process can also be done more quickly and efficiently. Thus, the existence of this tool can help farmers increase their agricultural productivity.
"We have conducted trials on this rice seed identification tool and the results of the trials have shown satisfactory results," said Sidiq.
Currently, Sidiq and his team are still developing the device so that it can be widely used by farmers throughout Indonesia.
"We hope that this tool can provide real benefits to farmers throughout Indonesia and increase agricultural productivity in our country," said Sidiq.
Not only continuing to develop, Sidiq and his team have also collaborated with the industry to develop and produce this tool for mass production. At the moment, Sidiq has at least partnered with CV Adika Engineering as a cooperation partner who will produce/multiply identification tools. Apart from CV Andika Engineering, Sidiq is also working with CV Restu Tani Jember who will use this product.
For information, besides involving Polines lecturers and students, the development of rice seed identification tools is based machine learning this also involved a number of lecturers and students from the Jember State Polytechnic (Polije) as collaborators. They are Dwi Rahmawati (a seed expert from the Polije Seed Center) and a Polije Diploma Program student, Bima Oktasa.
Meanwhile from Polines, apart from Sidiq, the research funded from the LPDP grants for 2022 also involved Lilik Triyono (Computer Engineering Engineering Study Program), M. Cahyo Edi Prabowo (Electronics Polines Study Program), Muhlasah Novita Mara and Resistant Prahara (Polines Telecommunications Study Program). The team was also assisted by two Polines Applied Telecommunication Master students, Feny Rahmasari and Thomas as well as a diploma student on behalf of Ilham Budi Prasetyo. (Polines/Nan/Cecep)
Source: vocational.kemdikbud.go.id