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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Informatika Jurnal Tekinkom (Teknik Informasi dan Komputer) MEANS (Media Informasi Analisa dan Sistem) Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) International Journal Of Science, Technology & Management (IJSTM) Jurnal Media Informatika Jurnal Sistem Informasi, Teknik Informatika dan Teknologi Pendidikan (JUSTIKPEN) Journal of Computer Science and Information Systems (JCoInS) Internet of Things and Artificial Intelligence Journal Dike
Sihombing, Volvo
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering Social Sciences Transportation Other

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Journal : Internet of Things and Artificial Intelligence Journal

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Drone simulation for agriculture and LoRa based approach adi, Puput Dani Prasetyo; Mustamu, Novilda Elizabeth; siregar, Victor M.M.; Sihombing, Volvo
Internet of Things and Artificial Intelligence Journal Vol. 1 No. 4 (2021): Volume 1 Issue 4, 2021 [November]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1480.208 KB) | DOI: 10.31763/iota.v1i4.501

Abstract

Spraying appropriately and regularly will help develop rice plants' growth and development to produce superior rice. These pesticides' spraying is sometimes uneven because of the vast land, limited human labor, and several other factors. that appropriate technology is needed that helps in the process of spraying rice pesticides using drones. Drones are deemed appropriate in spraying its advantages, among others, more effective, reducing the involvement of humans in work. Drones help track consistently and in detail the part of agricultural land that will be sprayed with pesticides, unlike humans. It is more automatic in monitoring, with the camera used on the drone can see the growth of rice plants directly and do recording or real-time connecting to the application server or IoT. Besides spraying pesticides, regular monitoring of plants can be done with drones. This study uses a UAV simulation for mapping the location of pesticide spraying, the results of contributions to large areas, and analysis of drone power consumption, which means allocating Drones to the area of land being managed.
The Relationship of Teacher Activity in the Teaching and Learning Process to Elementary Student Learning Outcomes Using Bootstrap Machine Learning Hia, Faomaha; Sihombing, Volvo; Juledi, Angga Putra
Internet of Things and Artificial Intelligence Journal Vol. 3 No. 4 (2023): Vol. 3 No. 4 (2023): Volume 3 Issue 4, 2023 [November]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v3i4.669

Abstract

Often, after the learning and teaching process is over, students will be tested with quizzes, midterm exams, and even end-of-semester exams, but these exams still take time after the teacher has taught several weeks or months that have passed; what if after teaching, for example, a math lesson, and students immediately understand or do not understand at all, and this can be detected using Machine Learning. The variable that can be raised is the value or quiz grade of a particular subject; for example, mathematics is one of the disliked subjects for most elementary school students, but how to find out that the student is able or unable to solve math problems and predict the end of semester grades for mathematics, this can be determined using Machine Learning, using the KNN Algorithm or K-MEANS method, or other methods that are deemed appropriate to the existing case study. In this case study, it is predicted whether a variable affects each other or affects other variables; this is done by doing or drawing relationships between variables. This research successfully concluded from the performance of machine learning in predicting students' understanding of math lessons after teaching and learning activities ended. The parameters that will be used for testing are population and sampling, and then data analysis, validity, and reliability tests are carried out.
Co-Authors Abdillah, Ihsan Abdillah, Syakira Adi, Puput Dani Prasetyo Aditya, Nanda Alam, Dewi Pathimah Alpiansyah, Fredy Andriyani, Wahyu Fitri Angreani Hulu, Linca Elma Popi Ariska, Fevi Aurianda, Rieke Bangun, Budianto Barasa, Kristina Dewi Utami, Yarma Agustya Dwiyanti, Dida Dwiyanti, Didan Efendi, Davina Rizky Fadilla Hasibuan, Intan Gultom, Gregorius Apri K Halawa, Prianus Harefa, Sinema Hasibuan, Dilla Puspita Hasibuan, Mila Nirmala Sari Hasibuan, Sabdi Albi Hendriyanti, Yurika Cici Hia, Faomaha Hutagalung, Charles Efendy Irmayani , Deci Irmayani Irmayani Irmayani, Deci Jannah , Ely Jati, Dewi Sekar Juledi, Angga Putra Juni Yanris, Gomal Lumban Gaol, Tid Verawati Maizura, Safrina Manurung, Romtika mawarni, Putri Sigit Mega, Mega Muhammad Halmi Dar Muliani, Sonia Sri Munthe , Ibnu Rasyid Munthe, Ibnu Rasyid Mustamu, Novilda Elizabeth Nasution, Fitri Aini Pakto, Dedi Pertiwi, Nur Fajar Kurnia Purba, Mila Hanim Purwati Purwati Ramadhani, Siska Rangkuti, M. Andri Gautama Rani Rahayu, Rani Rusmiana, Rusmiana Safitri, Nina Simamora, Rikardo Lasroha siregar, Victor M.M. Siti Kholijah, Siti Kholijah Sitio, Arjon Samuel Sitompul, Joni Awendri Sitorus, Anggiat Selamat Syafitri, Risma Syahputra, Rapian Tasyabila, Tasyabila Tawanta Natalia Sembiring, Sri Tiara, Dewi Tria Wulandari Yanris, Gomal Juni