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Nadya Husenti
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Agriculture, Biological Sciences & Forestry Education Environmental Science Languange, Linguistic, Communication & Media Social Sciences Other

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Peningkatan Pemahaman Implementasi Data Mining bagi Siswa SMK Dharma Wanita Gresik Farhanna Mar'i; Nadya Husenti; Choridatul Bahiyyah; Hafidz Ubaidillah
Indonesian Journal of Community Service and Innovation (IJCOSIN) Vol 2 No 2 (2022): Juli 2022
Publisher : LPPM IT Telkom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (403.178 KB) | DOI: 10.20895/ijcosin.v2i2.615

Abstract

Seiring berkembangnya teknologi informasi pada revolusi industri 4.0 diperlukan teknik implementasi Data Mining untuk menggali pengetahuan pada data untuk dapat dimanfaatkan sebaik-baiknya. Pengenalan implementasi Data Mining pada siswa SMK khususnya pada jurusan Rekayasa Perangkat Lunak (RPL) sangat penting untuk dilakukan untuk membekali siswa tentang implementasi Data Mining pada proses perancangan Aplikasi. Berdasarkan hasil wawancara yang dilakukan oleh tim Pengabdian Kepada Masyarakat (PKM) Program Studi Teknik Informatika Universitas Muhammadiyah Gresik dengan pihak SMK Dharma Wanita Gresik khususnya di kelas XII jurusan Rekayasa Perangkat Lunak diketahui bahwa siswa belum pernah diberikan pembekalan ilmu mengenai implementasi Data Mining. Sehingga kegiatan peningkatan pemahaman implementasi Data Mining pada siswa SMK Dharma Wanita Gresik khususnya pada Jurusan Rekayasa Perangkat Lunak dilakukan dengan cara melakukan sosialisasi ilmu Data Mining disertai dengan pelatihan mengenai penggunaan salah satu tools Data Mining yaitu Rapid Miner. Adapun hasil yang tercapai dari kegiatan PKM ini adalah adanya peningkatan pemahaman dan kemampuan siswa SMK Dharma Wanita Gresik jurusan Rekayasa Perangkat Lunak mengenai Data Mining dan teknik implementasinya pada data nyata yang diukur menggunakan post test.
Pelatihan Pemahaman Implementasi Teori Euclidean Distance dalam Metode K-Nearest Neighbour (K-NN) untuk Komputasi Cerdas bagi Siswa SMA Farhanna Mar'i; Nadya Husenti; Rakhmadhan Rizki Brilian; Agung Gumilang
Indonesian Journal of Community Service and Innovation (IJCOSIN) Vol 3 No 2 (2023): Juli 2023
Publisher : LPPM IT Telkom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/ijcosin.v3i2.1124

Abstract

SMA Muhammadiyah 8 Cerme is a senior high school with grades X, XI, and XII which have majors in Natural Sciences and Social Sciences. Based on the results of interviews conducted by the Community Service Team (PKM) Informatics Engineering Study Program, Muhammadiyah University of Gresik, to the Muhammadiyah 8 Cerme High School, information was obtained that the school was trying to apply the independent learning curriculum to its students and they had never been introduced to the implementation of mathematical formulas in computer science. especially intelligent computing theory. The target of this PKM activity is students majoring in science class XI as many as 55 people. The method that will be used for this PKM activity is socialization and training on the importance of studying mathematics, especially the two-point distance formula or the Euclidean Distance theory and its application in Intelligent Computing using the K-Nearest Neighbor(K-NN) Classification that is a part of Data Mining. PKM activities last 2 hours 30 minutes and divided by 3 sessions. The first session is filled with socialization and manualization of the Euclidean Distance, then the second session is the implementation of K-NN in Intelligent Computing, then the last session, namely session 3, is filling in the post test to find out students' understanding of the material that has been presented. Based on the results of the post test, it shows that students understand the Euclidean distance theory and its application to intelligent computing using the KNN algorithm, as evidenced by the highest point for the post test that has been answered correctly, which is 96.3%.
Co-Authors Agung Gumilang Choridatul Bahiyyah Hafidz Ubaidillah Mar'i, Farhanna Rakhmadhan Rizki Brilian