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All Journal Unisda Journal of Mathematics and Computer Science (UJMC) J-SAKTI (Jurnal Sains Komputer dan Informatika) J-SAKTI (Jurnal Sains Komputer dan Informatika) TEKIBA : Jurnal Teknologi dan Pengabdian Masyarakat Journal of Applied Statistics, Mathematics, and Data Science Jurnal Informatika dan Teknik Elektro Jurnal Pengabdian Kepada Masyarakat Jurnal FORTECH
Aprilia, Ira
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Mathematics Mechanical Engineering Social Sciences

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Journal : Unisda Journal of Mathematics and Computer Science (UJMC)

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Aplikasi Android Mendiagnosa Hama dan Penyakit Tanaman Bawang Merah Menggunakan Fuzzy Logic Kartini, Dwi Putri; Ariyanti, Dyah; Aprilia, Ira
UJMC (Unisda Journal of Mathematics and Computer Science) Vol 9 No 2 (2023): Unisda Journal of Mathematics and Computer science
Publisher : Mathematics Department, Faculty of Mathematics and Sciences Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/ujmc.v9i2.6110

Abstract

The productivity of shallots in Indonesia from year to year is still low from maximum productivity, especially in Probolinggo district because it is caused by attacks of pests and diseases so often decreases the economic value and the quality of shallots. Lack of information for farmers, especially novice farmers on shallot plants, results in late countermeasures to prevent pest and disease attacks on shallots. For that, an application system is needed, namely an expert application system that can be implemented into machine language easily and efficiently by using Fuzzy Logic. The use of the Fuzzy Logic expert system can bridge machine language that is very precise with human language which tends to be not precise. In this study the logic used is fuzzy logic with the Sugeno method based on Android using the Java programming language by testing 16 expert data. From the results of testing this application system, researchers obtained an accuracy rate of 93.75% with details of 15 accurate data and 1 inaccurate data.
Co-Authors Abdul Ghofur Achmadin, Wahyu Nur Ahmad Izzuddin Ariyanti, Dyah Dani Hari Tunggal Prasetiyo Dwicaksono, Pramuditya F. Hikmah, Nuzul Indrawati, Putri Wahyuni Kartini, Dwi Putri Mas Ahmad Baihaqi Masruroh, Zuwidatul Misdiyanto, M Muhammad Anas Rahmawati , Anisa T, Yustina Suhandini Tjahjaningsih, Yustina Suhandini Tri Prihatiningsih Umi Zuhro, Mimik Wahyu Nur Achmadin