Articles
<![CDATA[MACHINE VISION AND GLOBAL POSITIONING SYSTEM FOR AUTONOMOUS ROBOTIC NAVIGATION IN AGRICULTURE: A REVIEW ]]>
<![CDATA[Rahmadian, Reza]]>;
<![CDATA[Widyartono, Mahendra]]>
<![CDATA[ JIEET (Journal of Information Engineering and Educational Technology) Vol 1, No 1 (2017) ]]>
Publisher : <![CDATA[Universitas Negeri Surabaya ]]>
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DOI: 10.26740/jieet.v1n1.p46-54
<![CDATA[Interest on robotic agriculture system has led to the development of agricultural robots that helps to improve the farming operation and increase the agriculture productivity. Much research has been conducted to increase the capability of the robot to assist agricultural operation, which leads to development of autonomous robot. This development provides a means of reducing agriculture?s dependency on operators, workers, also reducing the inaccuracy caused by human errors. There are two important development components for autonomous navigation. The first component is Machine vision for guiding through the crops and the second component is GPS technology to guide the robot through the agricultural fields.]]>
<![CDATA[Learning Strategy to Develop Critical Thinking, Creativity, and Problem-Solving Skills for Vocational School Students ]]>
<![CDATA[Samani, Muchlas]]>;
<![CDATA[Sunwinarti, Sunwinarti]]>;
<![CDATA[Putra, Bima A.W.]]>;
<![CDATA[Rahmadian, Reza]]>;
<![CDATA[Rohman, Juni Noor]]>
<![CDATA[ Jurnal Pendidikan Teknologi dan Kejuruan Vol 25, No 1 (2019): (May) ]]>
Publisher : <![CDATA[Faculty of Engineering, Universitas Negeri Yogyakarta ]]>
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DOI: 10.21831/jptk.v25i1.22574
<![CDATA[Critical thinking, creativity, and problem-solving skills are critical for vocational schools graduates to enter the workforce in the industrial era 4.0. This study aims to find a learning strategy that can develop these three skills. The study was carried out at SMK X Mojokerto in the Automotive Technology Program in the academic year of 2017/2018. Data were collected using an observation sheet validated by three experts and tested with inter-rater reliability. The data analysis method is t-test. The results of data analysis showed that the Contextual Project Based Learning (CPjBL) was generally effective to improve critical thinking, creativity, and problem-solving skills. Detailed observation included each of these aspects. The findings showed that the implementation of contextualized learning problems could improve the aspect of originality and problem understanding skills, which was usually difficult to improve. On the other hand, CPjBL was not effective in developing the ability of analysis in critical thinking and look-back in problem-solving skills.]]>
<![CDATA[PENERAPAN MACHINE VISION UNTUK SISTEM PANEN OTOMATIS DI ROBOT AGRIKULTUR ]]>
<![CDATA[Rahmadian, Reza]]>;
<![CDATA[Widyartono, Mahendra]]>
<![CDATA[ JIEET (Journal of Information Engineering and Educational Technology) Vol 4, No 1 (2020) ]]>
Publisher : <![CDATA[Universitas Negeri Surabaya ]]>
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DOI: 10.26740/jieet.v4n1.p47-52
<![CDATA[Peningkatan hasil dari sector agrikultur adalah salah satu hasil keuntungan dari berkembangnya penelitian tentang sistem robot di agrikultur. Penelitian-penelitian tersebut berguna untuk meningkatkan kapabilitas robot tersebut untuk semakin efektif dalam membantu di sektor agrikulutur, yang salah satu kapabilitasnya adalah otomatisasi. Dengan adanya otomasi dalam robot agrikultur maka kefektifitasan dalam membantu sektor ini juga bertambah, juga mengurangi kurangnya akurasi atau kesalahan yang di hasilkan jika menggunakan pekerja manual. Salah satu komponen penting dalam perkembangan robot agrikultur adalah sistem panen otomatis yang menerapkan teknologi Machine Vision sebagai inti dari sistem tersebut.]]>
<![CDATA[Harvesting System for Autonomous Robotic in Agriculture: A Review. ]]>
<![CDATA[rahmadian, Reza]]>;
<![CDATA[Widyartono, Mahendra]]>
<![CDATA[ INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) Vol 2, No 1 (2019) ]]>
Publisher : <![CDATA[Jurusan Teknik Elektro Fakultas Teknik UNESA ]]>
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DOI: 10.26740/inajeee.v2n1.p1-6
<![CDATA[Technology in the modern day has led to the development of agricultural robots that helps to increase the agriculture productivity. Numerous research has been conducted to help increasing the capability of the robot in assisting agricultural operation, which leads to development of autonomous robot. The development aim is to help reducing agriculture’s dependency on operators, workers, also reducing the inaccuracy caused by human errors. There are two important development components for autonomous harvesting. The first component is Machine vision for detecting the crops and guiding the robot through the field and the second component actuator to grab or picking the crops or fruits.]]>
<![CDATA[POTENSI OTEC DI PROVINSI PAPUA INDONESIA ]]>
<![CDATA[Widyartono, Mahendra]]>;
<![CDATA[Rahmadian, Reza]]>
<![CDATA[ INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) Vol 2, No 1 (2019) ]]>
Publisher : <![CDATA[Jurusan Teknik Elektro Fakultas Teknik UNESA ]]>
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DOI: 10.26740/inajeee.v2n1.p17-21
<![CDATA[Abstrak –Provinsi Papua merupakan salah satu provinsi terkaya di Indonesia dengan luas wilayahnya tiga kali lebih luas wilayah Pulau Jawa, namun kekayaan alam yang begitu besar belum dapat diolah karena belum adanya jaringan jalan yang memadai untuk menghubungkan wilayah-wilayah sentra produksi sehingga masih banyak wilayah-wilayah di Papua yang masi terisolasi dan kurang berkembang. Sama halnya dengan kondisi kelistrikan di Provinsi Papua, berdasarkan Statistik Ketenagalistrikan Tahun 2018 diketahui bahwa rasio elektrifikasi di Provinsi Papua sebesar 61,42 % yang merupakan terendah kedua dari rasio elektrifikasi seluruh Indonesia. Permasalahan di atas hanya mungkin dapat diatasi dengan melakukan diversifikasi sumber energi baik menyangkut jenis maupun jumlahnya melalui pemanfaatan berbagai sumber energi alternative khususnya sumber energi terbarukan (renewable energy). Karena sistem OTEC dipasang di daerah pantai atau lepas pantai maka potensi OTEC di Provinsi Papua terdapat di daerah-daerah di sepanjang perairan Provinsi Papua yang memiliki kedalaman laut ± 1000 m. Efisiensi maksimum sistem OTEC di perairan Nabire sebesar 0,76 sedangkan di perairan Biak, Bonggo, dan Jayapura mempunyai efisiensi maksimum yang hampir sama yaitu 0,84.Kata Kunci: OTEC, konversi energi.                            ]]>
<![CDATA[Machine Vision and Global Positioning System for Autonomous Robotic Navigation in Agriculture: A Review ]]>
<![CDATA[Rahmadian, Reza]]>;
<![CDATA[Widyartono, Mahendra]]>
<![CDATA[ JIEET (Journal of Information Engineering and Educational Technology) Vol 1, No 1 (2017) ]]>
Publisher : <![CDATA[Universitas Negeri Surabaya ]]>
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DOI: 10.26740/jieet.v1n1.p46-54
<![CDATA[Interest on robotic agriculture system has led to the development of agricultural robots that helps to improve the farming operation and increase the agriculture productivity. Much research has been conducted to increase the capability of the robot to assist agricultural operation, which leads to development of autonomous robot. This development provides a means of reducing agriculture’s dependency on operators, workers, also reducing the inaccuracy caused by human errors. There are two important development components for autonomous navigation. The first component is Machine vision for guiding through the crops and the second component is GPS technology to guide the robot through the agricultural fields.]]>
<![CDATA[Penerapan Machine Vision untuk Sistem Panen Otomatis di Robot Agrikultur ]]>
<![CDATA[Rahmadian, Reza]]>;
<![CDATA[Widyartono, Mahendra]]>
<![CDATA[ JIEET (Journal of Information Engineering and Educational Technology) Vol 4, No 1 (2020) ]]>
Publisher : <![CDATA[Universitas Negeri Surabaya ]]>
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DOI: 10.26740/jieet.v4n1.p47-52
<![CDATA[Peningkatan hasil dari sector agrikultur adalah salah satu hasil keuntungan dari berkembangnya penelitian tentang sistem robot di agrikultur. Penelitian-penelitian tersebut berguna untuk meningkatkan kapabilitas robot tersebut untuk semakin efektif dalam membantu di sektor agrikulutur, yang salah satu kapabilitasnya adalah otomatisasi. Dengan adanya otomasi dalam robot agrikultur maka kefektifitasan dalam membantu sektor ini juga bertambah, juga mengurangi kurangnya akurasi atau kesalahan yang di hasilkan jika menggunakan pekerja manual. Salah satu komponen penting dalam perkembangan robot agrikultur adalah sistem panen otomatis yang menerapkan teknologi Machine Vision sebagai inti dari sistem tersebut.]]>
<![CDATA[POTENSI OTEC DI PROVINSI PAPUA INDONESIA ]]>
<![CDATA[Widyartono, Mahendra]]>;
<![CDATA[Rahmadian, Reza]]>
<![CDATA[ INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) Vol 2, No 1 (2019) ]]>
Publisher : <![CDATA[Jurusan Teknik Elektro Fakultas Teknik UNESA ]]>
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DOI: 10.26740/inajeee.v2n1.p17-21
<![CDATA[Abstrak –Provinsi Papua merupakan salah satu provinsi terkaya di Indonesia dengan luas wilayahnya tiga kali lebih luas wilayah Pulau Jawa, namun kekayaan alam yang begitu besar belum dapat diolah karena belum adanya jaringan jalan yang memadai untuk menghubungkan wilayah-wilayah sentra produksi sehingga masih banyak wilayah-wilayah di Papua yang masi terisolasi dan kurang berkembang. Sama halnya dengan kondisi kelistrikan di Provinsi Papua, berdasarkan Statistik Ketenagalistrikan Tahun 2018 diketahui bahwa rasio elektrifikasi di Provinsi Papua sebesar 61,42 % yang merupakan terendah kedua dari rasio elektrifikasi seluruh Indonesia. Permasalahan di atas hanya mungkin dapat diatasi dengan melakukan diversifikasi sumber energi baik menyangkut jenis maupun jumlahnya melalui pemanfaatan berbagai sumber energi alternative khususnya sumber energi terbarukan (renewable energy). Karena sistem OTEC dipasang di daerah pantai atau lepas pantai maka potensi OTEC di Provinsi Papua terdapat di daerah-daerah di sepanjang perairan Provinsi Papua yang memiliki kedalaman laut ± 1000 m. Efisiensi maksimum sistem OTEC di perairan Nabire sebesar 0,76 sedangkan di perairan Biak, Bonggo, dan Jayapura mempunyai efisiensi maksimum yang hampir sama yaitu 0,84.Kata Kunci: OTEC, konversi energi.                            ]]>
<![CDATA[Harvesting System for Autonomous Robotic in Agriculture: A Review. ]]>
<![CDATA[rahmadian, Reza]]>;
<![CDATA[Widyartono, Mahendra]]>
<![CDATA[ INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) Vol 2, No 1 (2019) ]]>
Publisher : <![CDATA[Jurusan Teknik Elektro Fakultas Teknik UNESA ]]>
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DOI: 10.26740/inajeee.v2n1.p1-6
<![CDATA[Technology in the modern day has led to the development of agricultural robots that helps to increase the agriculture productivity. Numerous research has been conducted to help increasing the capability of the robot in assisting agricultural operation, which leads to development of autonomous robot. The development aim is to help reducing agriculture’s dependency on operators, workers, also reducing the inaccuracy caused by human errors. There are two important development components for autonomous harvesting. The first component is Machine vision for detecting the crops and guiding the robot through the field and the second component actuator to grab or picking the crops or fruits.]]>
<![CDATA[Machine Vision and Global Positioning System for Autonomous Robotic Navigation in Agriculture: A Review ]]>
<![CDATA[Reza Rahmadian]]>;
<![CDATA[Mahendra Widyartono]]>
<![CDATA[ JIEET (Journal of Information Engineering and Educational Technology) Vol. 1 No. 1 (2017) ]]>
Publisher : <![CDATA[Universitas Negeri Surabaya ]]>
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DOI: 10.26740/jieet.v1n1.p46-54
<![CDATA[Interest on robotic agriculture system has led to the development of agricultural robots that helps to improve the farming operation and increase the agriculture productivity. Much research has been conducted to increase the capability of the robot to assist agricultural operation, which leads to development of autonomous robot. This development provides a means of reducing agricultures dependency on operators, workers, also reducing the inaccuracy caused by human errors. There are two important development components for autonomous navigation. The first component is Machine vision for guiding through the crops and the second component is GPS technology to guide the robot through the agricultural fields.]]>
