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All Journal Teknosains: Media Informasi Sains dan Teknologi ROUTERS: Jurnal Sistem dan Teknologi Informasi
Putri, Yunita Dwi
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Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Library & Information Science Physics

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Prediksi Kelulusan Siswa dengan Algoritma Pembelajaran Mesin: Aplikasi Regresi Linear dan Logistik pada Faktor-Faktor Pendidikan Fenni Aprilia; Anggraini, Rasti Aulia; Putri, Yunita Dwi
ROUTERS: Jurnal Sistem dan Teknologi Informasi Vol. 3 No. 1, Februari 2025
Publisher : Program Studi Teknologi Rekayasa Internet, Politeknik Negeri Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25181/rt.v3i1.3897

Abstract

The main challenge in education lies in accurately predicting student graduation and understanding the factors influencing it. This study aims to provide a data-driven solution using machine learning algorithms, specifically linear regression to predict student exam scores and logistic regression to classify student graduation. The study contributes by developing predictive models that serve as tools to support strategic decision-making in educational institutions. This study utilized the Student Performance Factors dataset, comprising 6,607 samples with independent variables such as study hours, attendance, and parental involvement. Data analysis involved cleaning, transformation, and normalization before applying regression models. The findings showed that linear regression achieved a Mean Squared Error (MSE) of 3.256, indicating high accuracy in predicting exam scores. Logistic regression demonstrated an accuracy of 99.85% in classifying student graduation. These models complement each other by offering strategic insights to enhance educational quality.
Identifikasi Gejala Penyakit Dan Cendawan Patogen Pada Tanaman Cabai Merah Keriting (Capsicum annum var. Lado) Sukmawaty, Eka; Putri, Yunita Dwi; Meriem, Selis; Zuraidah, Zuraidah; Nur, Fatmawati; Hajrah, Hajrah
Teknosains Vol 20 No 1 (2026): Januari-April
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/teknosains.v20i1.64519

Abstract

Cabai merah keriting (Capsicum annuum L. var. Lado) merupakan komoditas hortikultura bernilai ekonomi tinggi namun rentan mengalami gagal panen akibat serangan cendawan patogen. Penelitian ini bertujuan untuk mengidentifikasi gejala serangan penyakit di lapangan serta jenis cendawan patogen penyebabnya. Metode penelitian meliputi isolasi, purifikasi, uji patogenitas (hipersensitivitas) pada daun tembakau, serta karakterisasi morfologi. Hasil observasi lapangan menemukan enam gejala penyakit utama, yaitu busuk buah antraknosa, busuk hitam pangkal batang, busuk batang, bercak daun Cercospora, penyakit embun bulu, dan hawar daun. Berdasarkan uji patogenitas, seluruh isolat mampu memicu gejala nekrosis pada daun tembakau yang mengindikasikan sifat patogenik. Hasil identifikasi menunjukkan bahwa cendawan penyebab penyakit tersebut tergolong ke dalam genus Colletotrichum, Fusarium, Curvularia, dan Phytophthora. Dapat disimpulkan bahwa keempat genus cendawan tersebut merupakan agen penyebab utama berbagai penyakit yang mengancam produktivitas tanaman cabai merah keriting di lokasi penelitian.
Co-Authors Anggraini, Rasti Aulia Fatmawati Nur Fenni Aprilia Hajrah Hajrah, Hajrah Meriem, Selis Sukmawaty, Eka ZURAIDAH ZURAIDAH