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All Journal Jurnal Ilmu Komputer dan Agri-Informatika Ekasakti Jurnal Penelitian dan Pengabdian (EJPP)
Gustri Efendi
Universitas Nahdlatul Ulama Sumatera Barat
Agriculture, Biological Sciences & Forestry Computer Science & IT Library & Information Science Public Health

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K-Nearest Neighbor untuk Frasa Guna Mendukung Keputusan dalam Mencari Guru Terbaik Januardi Nasir; Roni Saputra; Gustri Efendi; April Zahmi; Yasha Langitta Setiawan
Jurnal Ilmu Komputer dan Agri-Informatika Vol 9 No 1 (2022)
Publisher : Departemen Ilmu Komputer, Institut Pertanian Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jika.9.1.13-22

Abstract

There are several ways to assess the best teacher in determining the potential teacher. This aims to encourage teachers to excel and see the motivation, dedication, and loyalty of teachers, as well as see the professionalism of a teacher in technological advancements based on 4.0. From the research conducted in determining the best teacher, there are problems, including in the selection of the best teacher, the principal tends to choose based on observations made only by the principal himself and does not pay attention to the criteria and indicators of assessment in the form of professional, personality and social which makes the teachers less than optimal in their work. Therefore we need a system to solve some of the problems that occur. A system was built to overcome the problem in the form of a decision support system. A decision support system is a system aimed at management in helping to make the right decisions. The method used is K-Nearest Neighbor, which is a method for making decisions using supervised learning where the results of the new input data are classified based on the closest in the value data. Calculations were carried out in 2020 and 2021. The total value of data in the previous year was 70 lines of data. If it is further detailed, the data used is 1190 value data. The assessment prediction data used is teacher data in 2021, as many as 37 lines of data. The k-NN algorithm uses the value of k to determine the number of nearest neighbors whose status will be calculated.
Sosialisasi Pencegahan Kekerasan terhadap Anak dan Perempuan dalam Perspektif Hukum Perlindungan Anak dan Perempuan di Nagari Kasang, Kecamatan Batang Anai, Kabupaten Padang Pariaman Rangga Prayitno; Radiyan Rahim; Rica Azwar; April zahmi; Ade Triawan; Gustri Efendi
Ekasakti Jurnal Penelitian dan Pengabdian Vol. 5 No. 2 (2025): Ekasakti Jurnal Penelitian dan Pegabdian
Publisher : LPPM Universitas Ekasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31933/ejpp.v5i2.1313

Abstract

Violence against children and women is a serious issue that threatens welfare, security, and human rights. In Padang Pariaman Regency, particularly in Nagari Kasang, cases still occur that reflect the community's low awareness of legal protection mechanisms. This outreach activity aims to increase public understanding of legal protection for children and women in accordance with Law No. 23 of 2004 on the Elimination of Domestic Violence and Law No. 35 of 2014 on Child Protection. The implementation methods included interactive legal lectures, group discussions, educational video screenings, and case reporting simulations to the authorities. Evaluation results from pre-tests and post-tests indicated a significant improvement in participants’ legal knowledge, from an average of 58% to 87%. The community also demonstrated increased awareness in reporting violence cases to the relevant authorities. Supporting factors included the commitment of local government officials and participants’ enthusiasm, while challenges faced were patriarchal culture and limited complaint facilities. This activity proves that community-based participatory outreach is effective in promoting violence prevention and strengthening legal protection for victims.
Co-Authors Ade Triawan April Zahmi Azwar, Rica januardi nasir Prayitno, Rangga Radiyan Rahim Roni Saputra Yasha Langitta Setiawan