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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan Zeta - Math Journal Jurnal Teknologi Informasi untuk Masyarakat (Jurnal Teknokrat)
Darmawan, Kezia Eunike
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Physics Transportation

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Peran Mahasiswa dalam Memanfaatkan Teknologi pada Program Asistensi Mengajar di EL DE’OT Private Course Darmawan, Kezia Eunike; Chamidah, Nur
Jurnal Teknologi Informasi untuk Masyarakat Vol. 3 No. 1 (2025): Jurnal Teknologi Informasi untuk Masyarakat (Teknokrat)
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jt.v3i1.30229

Abstract

The Teaching Assistance Program is one of the implementations of the Merdeka Belajar Kampus Merdeka (MBKM) program, which aims to provide opportunities for students to participate in teaching and deepening their knowledge by becoming teachers, facilitators, tutors, trainers, or mentors in educational institutions within the community. This article documents the implementation of the Teaching Assistance Program by students of Universitas Airlangga at EL DE'OT Private Course. The students play the role of teaching assistants, creating teaching materials and being directly involved in the teaching and learning process in a non-formal institution in the form of private tutoring. In its implementation, students learn how to prepare teaching materials and teach using various teaching approaches, including fun learning, interactive PowerPoint, and exercises. It can be concluded that the program's objectives were successfully achieved, and the program provided various positive impacts for the students, the learners, and EL DE'OT Private Course as the institution where the teaching assistance took place. The students gained teaching experience, the learners acquired knowledge, and the institution involved obtained learning materials that could be used in the future.
MODELING LONGITUDINAL FLOOD DATA IN WEST SUMATRA USING THE GENERALIZED ESTIMATING EQUATION (GEE) APPROACH Nitasari, Alfi Nur; Sa'idah, Andini; Faizun, Nurin; Darmawan, Kezia Eunike; Fitri, Marfa Audilla; Chamidah, Nur
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss4pp2181-2190

Abstract

Flooding is one of the many natural disasters that often hit Indonesia. In July 2023, three areas in West Sumatra experienced floods and landslides which caused damages and even 2 missing victims. Since November 16th, 2023, 8 hamlets in Meranti Village, Landak District, West Sumatra have been inundated by floods which affected families and many public facilities. This research uses data from West Sumatra Province Central Statistics Agency. The data used is 2014, 2018 and 2021. The response variable used is the number of villages/sub-districts experiencing natural disasters according to district/city ( ). The predictor variables used are regional topography , the number of water channels such as rivers, reservoirs, etc. , the number of fields cleared through burning , the number of villages/sub-districts in C excavation area , and the number of dumpsters . This research uses Negative Binomial Regression with the Generalized Estimating Equation (GEE) approach. In the Poisson regression test, the QIC value based on Independent Working Correlation Structure (WCS) is with deviance value of , degree of freedom of , and dispersion score of 4,6144. Because the dispersion value is greater than 1, it can be concluded that there is overdispersion. Because there is more than one overdispersion, it is overcome by using negative binomial. The results of parameter estimation using negative binomial regression based on Independent WCS showed that only one variable was significant, which is the number of fields cleared through burning with deviance value of , degrees of freedom of and a QIC of . Negative Binomial regression model that was formed is ). From the two regression models used, namely Poisson and negative binomial, it was found that the negative binomial regression model was the best model because it had the lowest QIC value of .
Penerapan Analisis Diskriminan terhadap Data Penjualan Ikan Darmawan, Kezia Eunike; Putra, Mochamad Rasyid Aditya; Fitriyani, Mubadi’ul; Dewi, Berlianti Alisa; Amelia, Dita; Mardianto, M. Fariz Fadillah; Ana, Elly
Zeta - Math Journal Vol 8 No 1 (2023): Mei
Publisher : Universitas Islam Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31102/zeta.2023.8.1.30-38

Abstract

Lautan memiliki lebar yang sangat luas dibanding daratan yang ada di bumi kita. Tidak hanya daratan saja yang dihabitati oleh makhluk hidup, tetapi perairan juga. Peraian sendiri dibagi menjadi berbagai macam yaitu air tawar, air laut, dan air payau Banyaknya kelompok dan jenis ikan yang ada membuat kita harus mengelompokkannya berdasarkan kelompok untuk dapat membedakannya. Kelompok ikan didasarkan dengan berbagai macam kelompok seperti habitat, bentuk, anatomi, hingga ukurannya. Mengutip dari data yang didapatkan pada laman kaggle, terdapat jenis ikan yang memiliki bentuk hampir menyerupai satu sama lain. Jenis-jesnis ikan yang disebutkan dalam data yaitu ikan bream, ikan parkki, ikan pearch, ikan smelt, ikan whitefish, ikan pike, dan juga ikan roach. Dilakukanlah analisis diskriminan untuk mengklasifikasikan ikan yang belum dapat dibedakan karena bentuk fisiknya yang hampir menyerupai ke dalam gugus/kelompok yang sudah ditentukan supaya tidak terjadi kerugian dalam penjualan pasar ikan. Pada hasil analisis dengan uji Wilk’s Lambda didapatkan masing-masing jenis ikan memiliki perbedaan yang signifikan, lalu kelima fungsi diskriminan dapat secara nyata membedakan ketujuh kategori target kelompok.
Co-Authors Dewi, Berlianti Alisa Dita Amelia, Dita Elly Ana Faizun, Nurin Fitri, Marfa Audilla Fitriyani, Mubadi’ul M. Fariz Fadillah Mardianto Nitasari, Alfi Nur Nur Chamidah Putra, Mochamad Rasyid Aditya Sa'idah, Andini