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Analysis of Naïve Bayes Algorithm Method for Outstanding Students at Yapendak Ajamu Private Junior High School Putri Erwina; Ibnu Rasyid Munthe; Rahma Muti’ah
Budapest International Research and Critics Institute-Journal (BIRCI-Journal) Vol 6, No 3 (2023): Budapest International Research and Critics Institute August
Publisher : Budapest International Research and Critics University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33258/birci.v6i3.7704

Abstract

Academic achievement is a change in skills or abilities that can be enhanced through learning situations. However, an issue arises at Yapendak Ajamu Private Junior High School, where student assessments are still manually inputted, resulting in inefficiency when transferring grades to paper, which are later re-entered into the e-Report system. The calculation of student scores is also done manually, and the criteria for determining outstanding students heavily rely on academic grades, while non-academic aspects are only considered as supporting data with unclear weighting. Consequently, the assessment lacks fairness in determining outstanding students. Moreover, the manual nature of the assessment and the fact that it is held solely by the homeroom teachers make it difficult to access. The Naïve Bayes algorithm method applies a classification system that includes academic grades, attitudes, attendance, and extracurricular activities. School is a place where students weigh knowledge for future needs, each school also has its own permissibility, both in terms of the best student creator school and a school that only has a few smart students, but it can be ascertained that every school wants all its students to have high intelligence, but intelligence is also not only created by the school but intelligence is also based on the students, Yapendak Ajamu Private Junior High School is a private school that has smart students Where this make Yapendak Ajamu Private Junior High School known  to many people. These factors can be utilized by the school to determine outstanding students. Out of the 34 data training sessions processed in the Orange application, 30 students were predicted to be outstanding, while the remaining students were classified as not outstanding. The precision for predicting outstanding students is 1.000, while for predicting non-outstanding students, it is 0.104. Therefore, the conclusion drawn is that the grades of outstanding students are higher compared to those of non-outstanding students.
PELATIHAN PEMBELAJARAN KALKULUS DENGAN MEDIA MACROMEDIA FLASH Irmayanti; Zuhri Harahap, Syaiful; Masrizal; Putri Erwina; Juli Hati Fitri
Jurnal Pengabdian Masyarakat Gemilang (JPMG) Vol. 1 No. 1: Januari 2021
Publisher : HIMPUNAN DOSEN GEMILANG INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (198.795 KB) | DOI: 10.58369/jpmg.v1i1.12

Abstract

Kalkulus merupakan salah satu bagian dari materi matematika yang penting serta banyak diterapkan pada ilmu pengetahuan yang lain, misalnya pada sains dan teknologi, pertanian, kedokteran, serta perekonomian, dan sebagainya. Pada pembelajaran kalkulus salah satu yang menjadi masalah mendasar yaitu masalah limit fungsi, di samping kalkulus diferensial serta integral. Pembelajaran kalkulus dapat kita kelompokkan menjadi dua cabang besar, yakni kalkulus diferensial dan kalkulus integral. Jika diperhatikan, inti dari pelajaran kalkulus tak lain dan tak bukan adalah limit suatu fungsi. Bahkan, secara ekstrim kalkulus dapat didefinisikan sebagai pengkajian tentang limit. Oleh karena itu, pemahaman tentang konsep dan macam?macam fungsi di berbagai cabang ilmu pengetahuan serta sifat?sifat dan operasi limit suatu fungsi merupakan syarat mutlak untuk memahami kalkulus diferensial dan kalkulus integral lebih lanjut.