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Analisis Perbandingan Algoritma Machine Learning Dalam Prediksi Akademik Mahasiswa Berbasis Data Apriliana Putri Maulikha; Najwa Aisha Hirania Hirania; Fatecha Athallah Ahmad; Celvin Rasya Pamungkas; Muhammad Faiz Ardiansyah; Faridhatun Nikmah
Edutechno : Educational Technology Journal Vol. 2 No. 01 (2026): Volume 02 Nomor 01 (Juni 2026)
Publisher : PT Ininnawa Paramacitra Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62330/edutechno.v2i01.798

Abstract

Tingginya angka kegagalan akademik merupakan salah satu indikator signifikan yang memengaruhi kualitas dan akreditasi institusi perguruan tinggi. Penelitian ini bertujuan untuk menganalisis perbandingan algoritma Machine Learning dalam memprediksi performa akademik dan merumuskan strategi cara mengatasi mahasiswa yang teridentifikasi berisiko gagal. Metode penelitian yang digunakan yaitu Systematic Literature Review (SLR) terhadap literatur yang dipublikasikan antara tahun 2019-2025. Hasil analisis menunjukan bahwa algoritma Decision Tree (C4.5) merupakan model paling optimal untuk pengelompokkan risiko dengan tingkat akurasi mencapai hingga 97.80% yang mampu menangani dalam data administratif yang bersifat kategorikal. Sementara itu, analisis regresi linear menunjukkan adanya korelasi linear yang kuat antara perilaku belajar mahasiswa dengan capaian akademik, variabel presensi juga memberikan kontribusi sebesar 94% (R2 = 0,94) terhadap akurasi prediksi. Tidak hanya itu temuan lain mengungkapkan bahwa integrasi data real time dari Learning Management System (LMS) secara signifikan dapat meningkatkan presisi pada model dibandingkan dengan penggunaan data historis statis. Simpulan penelitian ini menegaskan bahwa penerapan hasil prediksi melalui Early Warning System yang diintegrasikan dengan bimbingan akademik intensif oleh Dosen Pembimbing Akademik (DPA) merupakan solusi efektif untuk menekan angka kegagalan studi secara dini dan objektif.
Analisis Data Konsumsi BBM sebagai Respons Kebijakan Efisiensi akibat Penutupan Selat Hormuz Elvina Alya; Naufal Faaiq Alluqman; Habibi Khoirul Rosit; Taqiy Faqihuddin; Alvin Adrian Fauzi Pramudita; Faridhatun Nikmah
JARUM: Journal of Analysis Research and Management Review Vol. 3 No. 2 (2026): May
Publisher : PT. Samudra Solusi Profesional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62952/jarum.v3i2.128

Abstract

Global energy demand, which still heavily depends on fossil fuels, has made world energy stability highly influenced by international geopolitical conditions. One of the most strategic regions in global oil distribution is the Strait of Hormuz, meaning that disruptions in this route can affect global oil prices and impact fuel consumption in various countries, including Indonesia. This study aims to analyze fuel oil (BBM) consumption as a response to energy efficiency policies resulting from geopolitical dynamics in the Strait of Hormuz and to identify their impacts on Indonesian society. This research employs a qualitative method with a descriptive approach. The data used are secondary data obtained from scientific journals and various other supporting sources. Data collection techniques were carried out through documentation studies and literature reviews, which were then analyzed descriptively to understand the relationship between global geopolitical conditions, fuel efficiency policies, and changes in public consumption patterns. The results show that the threat of disruption to oil distribution in the Strait of Hormuz has caused an increase in global oil prices, which consequently affected fuel price adjustments in Indonesia. These conditions encouraged the government to implement efficiency policies such as restrictions on subsidized fuel, digital distribution monitoring, biodiesel development, and the promotion of electric vehicles. These policies have influenced public behavior in energy consumption and increased public awareness of the importance of national energy efficiency.