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All Journal Gaung Informatika Teknik dan Ilmu Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial JISICOM (Journal of Information System, Infomatics and Computing) Journal of Information System, Applied, Management, Accounting and Research Technologia: Jurnal Ilmiah INTERACTION: Jurnal Pendidikan Bahasa Jurnal Informatika dan Rekayasa Perangkat Lunak INFORMASI (Jurnal Informatika dan Sistem Informasi) Reputasi: Jurnal Rekayasa Perangkat Lunak IMTechno: Journal of Industrial Management and Technology Profitabilitas Jurnal Insan
Handini Widyastuti
Universitas Bina Sarana Informatika
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences

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PERANCANGAN VIDEO PEMBELAJARAN ANIMASI MENGENAI PENCEMARAN AIR PADA USIA REMAJA Utami, Melinda; Widyastuti, Handini; Junadi, Bambang
Journal of Information System, Applied, Management, Accounting and Research Vol 10 No 1 (2026): JISAMAR (February 2026)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jisamar.v10i1.2231

Abstract

The decline in water quality that is the impact of water pollution will greatly affect the survival and ecosystem. Lack of education causes teenagers' understanding of water pollution to be relatively low because education related to water pollution is still rarely conveyed and less interesting. Education about water pollution needs to be conveyed especially to teenagers to instill awareness of maintaining environmental conservation. This research aims to develop learning media in the form of interactive animation applications as a web-based water pollution education media. This research uses the waterfall system development method with structured and systematic stages. This application is web-based so it is easily accessible as long as it is connected to the internet and built using HTML, CSS, and Javascript. The result of this research is in the form of an interactive animation application for water pollution education with an attractive appearance with complex and effective materials as an educational medium. Based on the questionnaire that was distributed to 49 adolescent respondents with an age range of 10 to 18 years old, a positive response was obtained that the application made could be an educational media with a satisfactory response.
Analisa Komparasi Kinerja Model Logistic Regression dan Random Forest dalam Memprediksi Risiko Turnover Karyawan Pahlevi, Omar; Yuni Fitriani; Dewi Ayu Nur Wulandari; Handini Widyastuti; Sri Utami; Astriana Mulyani
Jurnal INSAN Journal of Information System Management Innovation Vol. 5 No. 2 (2025): Desember 2025
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/j-insan.v5i2.11111

Abstract

Turnover karyawan merupakan salah satu nilai tolak ukur bagi keberhasilan suatu perusahaan dalam menjalankan kegiatan bisnisnya. Memprediksi turnover karyawan merupakan kegiatan signifikan yang penting bagi setiap perusahaan yang berkelanjutan, dimana informasi dini tentang status turnover karyawan memungkinkan organisasi untuk mengambil langkah-langkah pencegahan. Pada penelitian ini peneliti akan mengaplikasikan dan membandingkan dua buah model algoritma supervised learning, diantaranya model algoritma Logistic Regression dan Random Forest untuk memprediksi risiko turnover karyawan, kemudian membandingkan mana dari dua model algoritma tersebut yang paling akurat. Berdasarkan hasil pengukuran kinerja kedua model dengan menggunakan metode Confusion Matrix. Berdasarkan hasil penelitian, diketahui bahwa model Logistic Regression memiliki tingkat akurasi sebesar 84,64% serta F1-Score yang baik dengan nilai sebesar 0,89, nilai presisi sebesar 0,82, dan nilai recall sebesar 0,96. Performa model Random Forest memiliki tingkat akurasi sebesar 80,12%, F1-Score sebesar 0,85 menunjukkan keseimbangan antara presisi sebesar 0,80 dan recall dengan nilai 0,92. Hal ini membuktikan bahwa model algoritma Logistic Regression adalah yang paling baik untuk untuk prediksi risiko turnover karyawan.
Co-Authors Ade Christian Astriana Mulyani Bambang Junadi Dewi Ayu Nur Wulandari Faizah Faizah Fattya Ariani Husni Mubarok Insan Muhammad Muttaqien Juarni Siregar Junadi, Bambang Muhammad Farish Muttaqien, Insan Muhammad Niyanti, Niyanti Nur Lutfiyana Omar Pahlevi Riswandi Ishak Rizat Sakmir Roida Pakpahan Sahwa Wulanuari Setiaji Setiaji Siahaan, Fernando SRI UTAMI Sri Utami Sugiyanti Sugiyanti Tubagus Aria Utami, Melinda Wulanuari, Sahwa Yuni Fitriani Yuni Fitriani Yuni Fitriani, Yuni