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All Journal Jurnal Pengabdian Multidisiplin Journal of Information System and Computer Scientific Journal of Informatics
Alzena Dona Sabilla
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Public Health Social Sciences Other

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Pendampingan Pemanfaatan Media Digital Pada Pengelolaan Kegiatan Ekstrakurikuler di Madrasah Aliyah Hasyim Asy’ari Bangsri Jepara Olyvia Revalita Candraloka; Azzah Nor Laila; Alzena Dona Sabilla; Oktania Nayohan
Jurnal Pengabdian Multidisiplin Vol. 4 No. 1 (2024): Jurnal Pengabdian Multidisiplin
Publisher : Kuras Institute & Scidac Plus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51214/00202404823000

Abstract

Lembaga pendidikan formal seringkali fokus pada proses pembelajaran akademik. Akan tetapi proses ekstrakurikuler juga penting, dan perlu dikelola secara baik. Mitra pengabdian ini MA NU Hasyim Asy’ari Bangsri Jepara. Tujuan pengabdian ini meningkatkan ketrampilan mitra dalam pengelolaan ekstrakurikuler dengan memanfaatkan media digital. Metode pengabdian ini meliputi sosialisasi, pelatihan, penerapan teknologi, dan evaluasi. Hasil pengabdian ini menunjukkan peserta yang terlibat para pembina serta tutor ekstrakurikuler sejumlah 20. Para peserta setelah mengikuti pelatihan manajemen ekstrakurikuler dan pemetaan minat bakat siswa, 80% peserta mampu memahami materi serta ragam model pengelolaannya. tersebut menunjukkan pada aspek kebermanfaatan kegiatan 76% peserta sangat setuju, dan 24% setuju. Aspek materi sesuai kebutuhan 47% sangat setuju, 40% setuju, dan 13% cukup setuju. Materi mudah dipahami direspon 57% sangat setuju, 43% setuju. Aspek waktu memadai direspon 54% sangat setuju, 46% setuju. Secara umum ketrampilan mitra meningkat 80%, tutor beserta pembina terampil serta dapat menerapkan media aplikasi berbasis website MAHABA dalam mengelola ekstrakurikuler.
ASISTEN DIGITAL CEPAT DAN PRAKTIS CHATBOT PMB MENGGUNANKAN ALGORITMA NEURAL NETWORK Sabrina, Dinta; Arina Zulfa; Heru Saputro; Alzena Dona Sabilla
Journal of Information System and Computer Vol. 4 No. 2 (2024): Desember 2024
Publisher : Universitas Islam Nahdlatul Ulama Jepara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34001/jister.v4i2.1216

Abstract

Demand for accurate information services, and responsiveness is increasing in the modern era, especially in the process of receiving new students. The limitations of human resources that provide information services in a direct way cause user delays and dissatisfaction. Therefore, an automatic solution that can provide efficient and effective information services, is the chatbot service (PMB) using AI to make it easier for prospective students and educational institutions to communicate. The study created a chatbot that could understand a better natural language by combining the neural convolutional network (CNN) and long short-term memory (LSTM) supported by embedding gloves. To ensure that the neural network's models can process text optimally, development processes involve important stages such as tokenization, padding, and the formation of the embedding matrix. Test results show that models have high training accuracy, but validation charts show overfitting, which is indicated by the big difference between losing training and losing validation. Embedding gloves, however, successfully enhance word representation and help people better understand the context of the text included. The CNN-LSTM PMB chatbot aims to provide a faster, more, relevant, and accurate service to prospective students
Analysis of Sentiment Towards Educational Services in Modern Islamic Boarding Schools using the Naïve Bayes Method Minardi, Joko; Noor Azizah; Ahmad Saefudin; Alzena Dona Sabilla; Dinta Sabrina; Yulia Savika Rahmi
Scientific Journal of Informatics Vol. 11 No. 4: November 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i4.15861

Abstract

Purpose: This study aims to analyze public sentiment regarding educational services in modern Islamic boarding schools using the Naïve Bayes method. The findings provide recommendations for improving educational quality. Methods: The research follows the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework, utilizing web scraping techniques to collect data from social media and online discussion forums. The Naïve Bayes algorithm is used for sentiment classification. Result: A dataset of 387 reviews was analyzed, showing that 82.8% of reviews were positive, while 17.2% were negative. The model achieved an accuracy of 88%. Novelty: Unlike previous studies, this research focuses specifically on modern Islamic boarding schools, employing machine learning for sentiment classification to provide actionable recommendations.
Co-Authors Ahmad Saefudin Arina Zulfa Dinta Sabrina Heru Saputro Joko Minardi, Joko Laila, Azzah Nor Noor Azizah Oktania Nayohan Olyvia Revalita Candraloka Sabrina, Dinta Yulia Savika Rahmi