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All Journal International Journal of Applied Power Engineering (IJAPE) TELKOMNIKA (Telecommunication Computing Electronics and Control) INTEGER: Journal of Information Technology Jurnal Media Elektro : Journal of Electrical Power, Informatics, Telecommunication, Electronics, Computer and Control System Prosiding Seminar Nasional Sains dan Teknologi Terapan JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA) SinarFe7 Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK)
Hari Agus Sujono
Institut Teknologi Adhi Tama Surabaya
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Implementasi Model Prototype Dalam Pengembangan Aplikasi Perpustakaan Smp Negeri 13 Ujung Pangkah Gresik Alfikri, Allif Mufti; Rachman, Andy; susilowati, Sulistyowati; Fahrurrozi, Nanang; Sujono, Hari Agus; alala, Pratama sandi
Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) 2025: SNESTIK V
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/p.snestik.2025.7457

Abstract

Perkembangan sistem informasi yang pesat di era globalisasi memberikan dampak signifikan di berbagai sektor, termasuk pendidikan. Di SMP Negeri 13 Ujungpangkah Gresik, pengelolaan administrasi perpustakaan yang masih menggunakan metode konvensional kurang efektif dan efisien. Penelitian ini bertujuan untuk mengembangkan sistem informasi perpustakaan berbasis aplikasi yang mencakup manajemen user, buku, katalog, peminjaman, pengembalian, dan pelaporan data. Metode yang digunakan adalah model prototype, yang memungkinkan perbaikan sistem secara berkelanjutan melalui evaluasi pengguna. Proses pengembangan melibatkan tahapan pengumpulan kebutuhan, pembuatan prototype, evaluasi, pembuatan aplikasi, dan pengujian sistem. Sistem informasi yang dikembangkan diharapkan dapat meningkatkan efisiensi dan efektivitas pengelolaan perpustakaan.
Rancang Bangun Estimasi Daya Output Pada Photovoltaic Menggunakan Metode Fuzzy Anfis Sugeno riny sulistyowati; Sujono, Hari Agus; H., Gatot Basuki; Saputra, Ariyanto Dwi
JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA) Vol. 10 No. 1 (2026): April
Publisher : Muhammadiyah University, Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/jeeeu.v10i1.1733

Abstract

General Background: The increasing demand for electrical energy has accelerated the development of renewable energy systems, particularly photovoltaic (PV) technology, which requires reliable power estimation under varying environmental conditions. Specific Background: PV output power is strongly affected by environmental parameters such as light intensity, voltage, current, and temperature, making prediction difficult when nonlinear relationships occur among variables. Knowledge Gap: Conventional multi-regression approaches have limitations in modeling nonlinear PV characteristics, while comparative evaluations of Adaptive Neuro-Fuzzy Inference System (ANFIS) configurations for PV power estimation remain limited. Aims: This study aims to develop and evaluate an ANFIS Sugeno-based model for estimating PV output power and compare its performance with multi-regression methods using real-time environmental data collected through an Arduino-based data logger. Results: The developed data logger successfully recorded stable real-time data, while the ANFIS model demonstrated substantially lower prediction errors than multi-regression. The best-performing configuration, Gauss555, achieved Mean Absolute Percentage Error (MAPE) values of 2.03% for training data and 2.13% for testing data, whereas multi-regression produced errors of 54.63% and 79.19%, respectively. Gaussian membership functions consistently generated lower and more stable Absolute Percentage Error (APE) values than triangular and trapezoidal functions. Novelty: The study integrates real-time PV environmental monitoring with comparative ANFIS membership function configurations to identify the most suitable nonlinear prediction model for PV output estimation. Implications: The findings demonstrate that ANFIS provides a robust and accurate approach for photovoltaic power estimation, supporting reliable renewable energy management and future intelligent PV monitoring systems.
Co-Authors Al Ahmad, Ubaidillah Alala, Pratama Sandy Alfikri, Allif Mufti Amirillah, Risky Anaz, Vitra Farizal Andy Rachman Badruz Zaman Djoko Purwanto Enggar Alfianto Erwanti, Nariyah Silviana Fahrurrozi, Nanang Fahruzi, Akhmad Fungki Apriyanto Fungki Apriyanto, Fungki H., Gatot Basuki Hendro Juwono Husein, Ferrary Faisal Ilham , Ilham Joshua Noviandy Luky Agus Hermanto Luky Agus Hermanto, Luky Agus Misbahul Munir Muhammad Amin Muhammad Rivai Pambudi, Wildan Agung Pratama Sandi Alala Pratama, Moch. Farhan Putra Prawidya, Ganesha Fikri Putranto, Hilman Fadhli Riny Sulistyowati Rudi Setiawan Saputra, Ariyanto Dwi Silviana Erwanti, Nariyah Sulistyowati, Riny Sulistyowati, Sulistyowati Sulistyowati Susilowati, Arda Gusema susilowati, Sulistyowati Taufiqurohman, Mohamad Nawal Ubaidilah, Alfi Nur Uinsa Pradana