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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.
PERANCANGAN SISTEM PENGAMBILAN OBAT BERBASIS WEB PADA RSU CAHAYA MEDIKA Satrio Singgih; Handini Widyastuti; Bambang Junadi; Yuni Fitriani; Sri Utami; Renditya Akbar
Journal of Information System, Informatics and Computing Vol 10 No 1 (2026): JISICOM (June 2026)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jisicom.v10i1.2442

Abstract

The Medication pickup process at RSU Cahaya Medika is still manual, causing delays, queues, and data errors. This study aims to implement a web-based information system to improve pharmacy service efficiency and accuracy. The system was developed using the waterfall model with PHP, MySQL, and Framework. It helps manage prescriptions, medication status, and reports in an integrated way. The result show that the system speeds up services, reduces errors, and provides clear information to patients. It is expected to enhance the performance of the hospital pharmacy.
Quality Analysis of the Shopee E-Commerce Application Based on ISO/IEC 25010: Functional Suitability, Usability, and Performance Efficiency Aspects Marcello Kanzi; Sri Utami; Yuni Fitriani; Handini Widyastuti; Bambang Junadi
Jurnal Teknologi Informatika dan Komputer Vol. 12 No. 2 (2026): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v12i2.3803

Abstract

Shopee is the e-commerce platform with the largest number of users in Indonesia, making its application quality an important subject for objective evaluation based on established standards. This study aims to analyze the quality of the Shopee e-commerce application based on the ISO/IEC 25010 standard, focusing on three characteristics: Functional Suitability, Usability, and Performance Efficiency. This research applies a descriptive quantitative approach using three instruments. Functional Suitability was tested through Black Box Testing on eight main features elaborated into 16 test cases. Usability was measured using a System Usability Scale (SUS) questionnaire with a 1-5 Likert scale distributed to 105 active Shopee users selected through purposive sampling. Performance Efficiency was measured using Xcode Instruments on an iOS device through CPU Usage and Memory Usage parameters across five main features. The results show that Functional Suitability achieved a success rate of 100% (Good category), Usability obtained an average SUS score of 77.38 (Good category) with a Cronbach's Alpha of 0.780, while Performance Efficiency recorded an average CPU usage of 41.02% (Fair category) and an average memory consumption of 819.84 MB (Poor category), resulting in an overall Fairly Good category. The Shopee application is recommended to optimize memory consumption, particularly on the Checkout and Home Page features.