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All Journal Jurnal Ekonomi Manajemen Sistem Informasi CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika)
Gina Purnama Insany
Universitas Nusa Putra, Sukabumi, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Law, Crime, Criminology & Criminal Justice

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Implementasi Automatic Speech Recognition Pada Penilaian Hafalan Al-Quran Dengan Metode Muroja’ah Berbasis Android Alun Sujjada; Gina Purnama Insany; Muhamad Fajar Nugraha
CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Vol 10 No 2 (2024): CICES
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cices.v10i2.3247

Abstract

This research implements Automatic Speech Recognition (ASR) technology in the process of assessing Al-Qur'an memorization to overcome the problem of the increasing number of people who cannot read the Al-Qur'an fluently. With ASR, computers can recognize and transcribe human speech accurately, thereby improving the quality and accuracy of pronunciation and providing constructive feedback to learners. An Android-based application that uses the ASR service from the Google Speech API allows users to recite verses from the Koran and automatically recognize and evaluate what they have memorized. The hope is that the use of ASR technology can improve the ability to memorize the Al-Qur'an more effectively and flexibly without requiring direct teacher assistance. This system was developed using the Rapid Application Development (RAD) method with Blackbox Testing.
Implementasi Metode Kanban pada Penjadwalan Mata Kuliah Berbasis Web Juan Cerah Joseph; Alun Sujjada; Kamdan Kamdan; Gina Purnama Insany
Jurnal Ekonomi Manajemen Sistem Informasi Vol. 6 No. 5 (2025): Jurnal Ekonomi Manajemen Sistem Informasi (Mei - Juni 2025)
Publisher : Dinasti Review

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/jemsi.v6i5.5298

Abstract

Penjadwalan mata kuliah di Universitas Nusa Putra yang sebelumnya dilakukan secara manual dengan Excel sehingga pengunanya sering menghadapi kendala seperti bentrok jadwal dan alokasi ruangan yang kurang optimal. Penelitian ini mengembangkan sistem penjadwalan berbasis web menggunakan metode Kanban, dengan HTML dan Bootstrap sebagai frontend, Laravel sebagai backend, dan MySQL sebagai database. Metode Kanban dipilih karena kesederhanaan, fleksibilitas, dan kemampuan visualisasi alur kerja secara real-time. Hasil survei dengan skala Likert menunjukkan nilai rata-rata 3,7 (netral) untuk kemudahan antarmuka dan pembuatan jadwal, 3,6 (netral) untuk efektivitas mengurangi konflik jadwal, serta 4,0 (baik) untuk pengurangan pekerjaan manual dan kepuasan pengguna. Pengujian black box testing menunjukkan sistem berfungsi sesuai rencana. Implementasi sistem ini meningkatkan efisiensi dan akurasi penjadwalan, memberikan manfaat bagi dosen, mahasiswa, dan staf administrasi.
Sistem Prediksi Konsumsi Energi Listrik Subsidi dan Non Subsidi Berbasis Web dengan Metode RNN (Kasus Kota Sukabumi) Gina Purnama Insany; Alun Sujjada; Salwa Dwi Lidena; Muhammad Sahrul Fadilah; Refi Wilianti
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 2 (2025): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i2.917

Abstract

Sukabumi City experiences an annual increase in electricity consumption, especially in subsidized and non-subsidized categories. However, the energy distribution planning process remains manual and reactive. This research developed a web-based electricity consumption prediction system using the Recurrent Neural Network (RNN) method integrated with the Laravel framework. The development process applied the Rapid Application Development (RAD) method and system modeling using UML. The RNN model achieved a prediction accuracy of 92.4% with an MAE of 12.38 kWh and RMSE of 16.12 kWh. The application provides interactive prediction visualizations to support more efficient energy planning.
Co-Authors Alun Sujjada Juan Cerah Joseph Kamdan Muhamad Fajar Nugraha Muhammad Sahrul Fadilah Refi Wilianti Salwa Dwi Lidena