Article Per Year (5 Year)
p-Index From 2021 - 2026
1.295
P-Index
This Author published in this journals
All Journal Pro Bisnis Telematika JUITA : Jurnal Informatika Proceeding Seminar LPPM UMP Tahun 2014 Jurnal Informatika Upgris JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Infotekmesin Respati Jurnal Teknik Informatika (JUTIF) Solidaritas: Jurnal Pengabdian Jurnal Pengabdian Mitra Masyarakat (JPMM) J-ABDIPAMAS (Jurnal Pengabdian Kepada Masyarakat)
Andi Dwi Riyanto
Universitas Amikom Purwokerto
Religion Humanities Automotive Engineering Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Other

Published : 23 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 23 Documents
Search

 1   2   3 
Peningkatan Kapasitas Digital Berkelanjutan pada PAC GP Ansor Kroya Riyanto, Andi Dwi; Wahid, Arif Mu’amar; Pratiwi, Aniec Anafisah
Solidaritas: Jurnal Pengabdian Vol. 4 No. 2 (2024): Solidaritas: Jurnal Pengabdian
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat UIN Prof. K.H. Saifuddin Zuhri

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Skill digital merupakan kompetensi dasar yang harus dimiliki oleh organisasi di era digital. GPAnsor Cabang Kroya mengalami permasalahan tidak semua organisasi ranting memiliki mediainformasi dan promosi. Pengelolaan media sosial yang dimiliki masih minimalis dan memerlukan pendampingan. Tujuan dari program ini adalah untuk meningkatkan kapasitas digital danmengatasi kesenjangan penggunaan media sosial di tingkat ranting. Program ini melibatkanserangkaian pelatihan praktis yang fokus pada pembuatan konten, interaksi dengan pengguna,dan strategi penggunaan platform digital untuk memaksimalkan jangkauan dan pengaruh sosial. Metodologi pelaksanaan meliputi diskusi awal, pelatihan interaktif, mentoring, monitoring,dan evaluasi. Output kegiataan adalah dnegan menekankan pada peningkatan jumlah akun aktif,kualitas konten, konsistensi publikasi, dan interaksi dengan pengikut. Evaluasi akhir menunjukkan peningkatan signifikan dalam keaktifan dan kualitas pengelolaan media sosial diantara peserta. Saran untuk perbaikan meliputi penerapan pelatihan virtual yang lebih luas dan pengembangan materi pelatihan yang lebih adaptif untuk mendukung keberlanjutan keterlibatan digitaldi masa depan.
Pengembangan Sistem Layanan Penerimaan Peserta Didik Baru Berbasis Web Riyanto, Andi Dwi; Charis Prasetya, Subani; Alif Jamaluddin, Ilham
Infotekmesin Vol 15 No 1 (2024): Infotekmesin: Januari, 2024
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v15i1.2165

Abstract

In today's digital era, technology has become an important element in various aspects of life, including in the education sector. YPE Kroya Vocational High School in Cilacap, which currently has a manual new learner registration process, faces challenges in managing registration data that can lead to errors such as incorrect name writing and column placement. To overcome this problem, the research team developed a website-based New Learner Admission service system. This system is designed to facilitate the registration and selection process while improving efficiency in data management. The development of this system follows the System Development Life Cycle (SDLC) method, resulting in an effective website-based PPDB service system. This system not only facilitates the registration process and data management of prospective students but also provides solutions to problems that exist in the conventional registration process. System testing has been conducted through Black Box and User Acceptance Testing (UAT) methods validating the reliability and usability of the system. The results of the UAT analysis showed that the system received a very positive assessment from the users with an average score of 4.48 (90%) for Design, 4.44 (89%) for Efficiency, and 4.42 (88%) for Service.
ANALYSIS OF FACTORS DETERMINING STUDENT SATISFACTION USING DECISION TREE, RANDOM FOREST, SVM, AND NEURAL NETWORKS: A COMPARATIVE STUDY Riyanto, Andi Dwi; Wahid, Arif Mu'amar; Pratiwi, Aniec Anafisah
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2188

Abstract

Student satisfaction is crucial in higher education, impacting student loyalty, retention rates, and institutional reputation. This study addresses the gap in applying advanced machine learning techniques to predict and understand key determinants of student satisfaction. The primary objective is to analyze and predict the factors determining student satisfaction using four machine learning models: Decision Tree, Random Forest, SVM, and Neural Networks. The dataset comprises 2527 entries with seven relevant features. Data preprocessing involved normalization and exploratory data analysis (EDA) to ensure accurate analysis. The Neural Network model achieved the highest accuracy with an MSE of 0.001399, RMSE of 0.037397, MAE of 0.030773, and R² of 0.998154, followed closely by the SVM model. These results suggest that advanced machine learning models, particularly Neural Networks and SVM, are effective in predicting student satisfaction and identifying key areas for improvement. This study contributes to understanding the determinants of student satisfaction using machine learning models, providing practical implications for educational administrators to develop targeted strategies to enhance student satisfaction by focusing on critical factors such as academic support and financial aid. The findings highlight the importance of using advanced predictive techniques to gain deeper insights into student satisfaction, thereby enabling institutions to implement more effective interventions. Future research should explore additional variables and more sophisticated model architectures to further improve predictive accuracy and expand the applicability of these models in educational settings.
Co-Authors Abidarin Rosidi Alfiana Oktaviani Alif Jamaluddin, Ilham Andrianto Andrianto Charis Prasetya, Subani Dani Arifudin Desta Nur Efika Ardini Dhipa Ringi Rizky Didit Suhartono Dwi Nurhidayat Eka Riyana Fabriyan Fandi Dwi Imaniawan Galuh Kusumastuti Galuh Kusumastuti Ilham Alif Jamaluddin Ilyas Ma'ruf Imam Tahyudin Khatirudin Ma’arif Leni Setiani Muhammad Faiz Noeris Muliasari Pinilih Prasetyo, Agung Pratiwi, Aniec Anafisah Primandani Arsi Purwadi Purwadi Rozak, Rofiq ‘Abdul Subani Charis Prasetya Suliswaningsih Suparmono Suparmono Tahyudin, Imam Zaheen Tarto Supriyoko Wahid, Arif Mu'amar Wahid, Arif Mu’amar Yogi Widy Astomo Yusyida Munsa Idah Zelin Arif Krisna Murti