Article Per Year (5 Year)
p-Index From 2021 - 2026
4.219
P-Index
This Author published in this journals
All Journal Journal of Electrical Technology METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Sisfokom (Sistem Informasi dan Komputer) International Journal of Engineering, Science and Information Technology JURNAL ILMIAH GLOBAL EDUCATION International Journal of Economic, Business, Accounting, Agriculture Management and Sharia Administration (IJEBAS) Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Algoritma Jurnal Teknologi Terapan and Sains 4.0 Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms INOVTEK Polbeng - Seri Informatika
Fuadi, Wahyu
Unknown Affiliation
Religion Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

Published : 27 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 27 Documents
Search

 1   2   3 
Cataract Eye Disease Diagnosis Using the Random Forest Method Novita, Lilis; Fuadi, Wahyu; Kurniawati, Kurniawati
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.777

Abstract

This study developed a machine learning-based classification model using the Random Forest algorithm to detect cataract risk based on 11 variables: age, gender, family history, lens opacity, visual acuity reduction, light sensitivity, color changes, double vision, intraocular pressure, slit-lamp results, and visual acuity. Feature importance analysis revealed that lens opacity and visual acuity variables contributed most significantly to cataract risk prediction, followed by intraocular pressure and visual acuity reduction. The system was designed using Google Colab for model training and Streamlit as an interactive interface, enabling real-time predictions with intuitive result visualization. After optimization using Grid Search, the model achieved an accuracy of 92.0%, precision of 95.0%, sensitivity of 90.0%, F1 Score of 92.4%, and specificity of 98.0%. This system is expected to serve as an effective supporting tool for medical professionals in the early diagnosis of cataracts.
Design of Attendance System for Informatics Engineering Lecturers Using RFID Sensors Based on IoT and Telegram Applications Akbar, Andry Maulana; Fuadi, Wahyu; Nunsina, Nunsina
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.794

Abstract

The attendance system is an essential element in the academic environment to ensure lecturer attendance in the lecture process. However, the manual attendance method still has various weaknesses, such as the potential for data manipulation and inefficiency in recording attendance. To overcome these problems, this research designs and implements an Internet of Things (IoT)-based lecturer attendance system using Radio Frequency Identification (RFID) sensors integrated with the Telegram application. The research method includes hardware design with ESP32 microcontroller, ESP32-CAM, RFID sensor, and HC-SR04 ultrasonic sensor. This system works by detecting lecturer attendance through RFID cards confirmed by ESP32, taking pictures with ESP32-CAM, and sending automatic notifications via the Telegram bot. Lecturer attendance data is then stored in a web-based database to facilitate the monitoring and evaluation. The test results show that the developed system can detect and record lecturer attendance accurately, with the response speed of the RFID sensor in reading cards ranging from 1-5 cm. The ultrasonic sensor also successfully detects objects accurately within a predetermined distance range. Lecturer attendance notifications sent via Telegram allow administrators to conduct real-time monitoring. With this IoT-based attendance system, the attendance recording process becomes more efficient and transparent and can reduce the risk of data manipulation. Further development can be done by adding data encryption and biometric authentication features to improve system security.
Student Learning Style Decision-Making System Using the Multi-Attribute Utility Theory Method at SMA Negeri 1 Jangka Munawarah, Munawarah; Fuadi, Wahyu; Aidilof, Hafizh Al Kautsar
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.842

Abstract

Education plays a vital role in shaping individual development and national progress. One key factor influencing learning effectiveness is students' learning styles, which determine how individuals absorb, organize, and process information. Understanding these differences is crucial for designing effective teaching methods. This research develops a Decision Support System (DSS) to determine student learning styles at SMA Negeri 1 Jangka using the Multi-Attribute Utility Theory (MAUT) method. MAUT is chosen for its ability to evaluate multiple criteria, convert them into numerical values, and systematically identify the most suitable learning approach. The alternatives in this study include Project Based Learning (PBL), Problem-Based Learning (PrBL), Inquiry-Based Learning (IBL), Discovery Learning (DL), and Contextual Teaching and Learning (CTL). The MAUT analysis considers five criteria: student activeness, material understanding, collaboration, initiative and creativity, and teacher-student communication. The research stages include literature study, data collection, system and database design, MAUT implementation, and system evaluation. The results, based on MAUT calculations, show that Inquiry-Based Learning (IBL) scores the highest at 13.611, followed by Discovery Learning (DL) at 13.018, Problem-Based Learning (PrBL) at 12.975, Contextual Teaching and Learning (CTL) at 12.929, and Project Based Learning (PBL) at 12.558. This system assists educators in designing personalized learning strategies that align with students' strengths. Leveraging data-driven analysis enhances education quality, fosters a student-centred learning environment, and improves academic performance and lifelong learning habits.
Application of Ant Colony Algorithm to Determine the Shortest Route for Nature and Culinary Tourism in North Aceh Teguh, Muhammad; Fuadi, Wahyu; Fitri, Zahratul
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.857

Abstract

This Research aims to design and implement a shortest route determination system for natural and culinary tourism locations in North Aceh using the Ant Colony Optimization (AntCO) algorithm. The developed system is designed to help tourists plan their trips efficiently by considering the distance and travel time between tourist destinations. The system implementation using the AntCO algorithm successfully displayed optimal routes for 28 tourist destinations in North Aceh. The system successfully implemented filtering features based on tourism categories and route visualization on an interactive map using different markers (green for natural tourism and red for culinary tourism). The research results show that the system successfully optimized tourist travel routes and provided comprehensive information, including automatic location detection, a list of tourist destinations, travel route details, and optimal visit sequences based on selected tourism categories. This system proved effective in helping tourists plan their trips in North Aceh by providing efficient routes according to their preferred tourism category preferences.
PENDETEKSIAN BAHASA ISYARAT INDONESIA SECARA REAL-TIME MENGGUNAKAN LONG SHORT-TERM MEMORY (LSTM) Putri, Husna Moetia; Fadlisyah, Fadlisyah; Fuadi, Wahyu
Jurnal Teknologi Terapan and Sains 4.0 Vol 3 No 1 (2022): Jurnal Teknologi Terapan & Sains
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/tts.v3i1.6853

Abstract

Bahasa Isyarat Indonesia (BISINDO) adalah salah satu cara teman Tuli untuk berkomunikasi. BISINDO muncul secara alami dari interaksi Tuli dengan lingkungannya dan dikenal sebagai budaya Tuli di Indonesia. Namun saat ini terdapat kendala dalam berkomunikasi antar teman Tuli dengan teman dengar dalam menggunakan fasilitas publik dikarenakan petugas pada pelayanan publik tersebut tidak dapat mengerti apa yang disampaikan oleh teman Tuli. Penelitian ini bertujuan untuk menjadi alat penghubung komunikasi satu arah antar teman Tuli dengan teman dengar yang diharapkan dapat mempermudah dalam berkomunikasi. Sistem yang dihasilkan akan mengklasifikasi dan mendeteksi gestur dari kosakata isyarat BISINDO secara langsung yang dikonversi menjadi sebuah teks. Klasifikasi BISINDO pada penelitian ini menggunakan metode Long short-term memory (LSTM) dan Mediapipe Holistic untuk mendeteksi kerangka pada tangan, wajah dan badan. Objek yang digunakan pada penelitian ini merupakan 30 kosakata isyarat BISINDO yang sering digunakan teman Tuli. Dari hasil evaluasi deteksi real-time penelitian ini mendapatkan akurasi sebanyak 92% untuk model 10 kelas dengan bidirectional layer LSTM, epoch 1000, hidden layer 64, batch size 32 dan mendapatkan akurasi sebanyak 65% untuk model 30 kelas dengan 2 layer LSTM epoch 500, hidden layer 64, batch size 64.
Classification of Coronary Heart Disease Based on Community Health Centre Medical Record Data Using SVM Algorithm Kausar, M Reza; Fuadi, Wahyu; Fitri, Zahratul
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/ng11kk81

Abstract

Coronary heart disease (CHD) is one of the leading causes of death worldwide and demands a fast and accurate diagnostic system, especially in community health centres (Puskesmas) where medical resources are limited. This study aims to develop a classification system for CHD using the Support Vector Machine (SVM) algorithm based on numerical medical record data. It also addresses the gap in previous studies that rarely applied SVM to tabular data from primary healthcare facilities. The methodology includes variable weighting, min-max normalization, model training with a linear kernel, and performance evaluation using a confusion matrix. The dataset consists of 100 patient records with variables such as age, blood pressure, heart rate, respiratory rate, and chest pain. The results show that the SVM model achieved an accuracy of 95%, a precision of 100%, recall of 88.9%, and an F1-score of 94.1%. The model was further integrated into a web-based application using Flask to support automated early diagnosis. This study demonstrates that SVM is effective in classifying heart disease based on medical records and offers a practical solution to improve healthcare service quality in Puskesmas.
PERAMALAN PERSEDIAAN GABAH KERING GILING (GKG) DENGAN MENGGUNAKAN METODE LOT SIZING DI KILANG PADI MARKOM Syahputra, Irwanda; Fuadi, Wahyu; Pratama, Angga
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 1 No. 2 (2017): Sisfo: Jurnal Ilmiah Sistem Informasi, Oktober 2017
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v1i2.242

Abstract

Seiring dengan semakin berkembangnya teknologi, kondisi persaingan didalamdunia usaha menjadi semakin ketat. Untuk menghadapi persaingan yang ketat inidiperlukan suatu sistem yang dapat meramalkan persediaan agar proses produksitidak terganggu dengan masalah bahan baku. Gabah kering giling (GKG)merupakan Untuk meramalkan persediaan ini maka dibagun sebuah sistem yangdapat memperkirakan permitaan kedepan dengan data dari tahun sebelumnya,serta dapat memaksimalkan dari segi biaya yang dikeluarkan untuk melakukanpersediaan tersebut. Perancagan penelitian ini menggunakan metode unifiedmodeling language (UML), yaitu dengan use case diagram, sequence diagram,activity diagram serta class diagram. Adapun tahapan dalam penelitian ini terdiridari proses peramalan permintaan dari gabah kering giling untuk satu tahunkedepan dengan menggunakan metode peramalan kuantitatif, selanjutnya akandicari nilai safety stock dan menghitung biaya pemesanan terkecil dari periodeyang ada dengan metode lot sizing. Dari hasil pengujian yang telah dilakukandidapatkan hasil untuk total permintaan selama tahun 2016 adalah sebesar 464360kg dan turun 12,06 % dari permintaan tahun 2015, dimana hasil tersebutselanjutnya dibagikan kembali atas 12 periode yang ada dalam setahunberdasarkan pola yang terbentuk dari data sebelumnya. Untuk perhitungan lotsizing nya didapatkan hasil berupa biaya pemesanan perperiode dengan biayapaling kecil jika pemesanan dilakukan pada setiap periode, sehingga menjadikanjumlah pemesanan dalam setahun sebanyak 12 kali pemesanan.Kata Kunci: Lot Sizing, Silver Meal, GKG, Safety Stock, Peramalan, UML.
Job Vacancy Recommendation System using JACCARD Method On Graph Database Riza, Saiful; Fuadi, Wahyu; Afrillia, Yesy
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 3 (2025): JULY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v14i3.2387

Abstract

In the rapidly evolving digital era, recommendation systems play a crucial role in helping users discover relevant information aligned with their preferences. PT Nirmala Satya Development, a company engaged in psychology and human resource development, faces challenges in utilizing big data consisting of 500 applicants, 500 job postings, and 500 job applications to generate accurate and relevant job recommendations. This study develops a job recommendation system using the Jaccard Coefficient method to measure similarity between users based on their job application history, implemented within a Neo4j graph database. The system models the relationships between entities through nodes and edges, allowing dynamic analysis using the Cypher Query Language. Testing on 237 users demonstrated that the majority received at least one relevant recommendation, with recall values often reaching 1.0, especially among users who had a single job target. The system achieved precision values ranging from 10% to 20%, which is considered acceptable given that ten recommendations are generated per user. The highest F1-score reached 0.33, although some users received F1 = 0 due to limited application history or unique preferences. Overall, the system effectively delivers personalized and efficient job recommendations, particularly for active users. This research also proves that combining the Jaccard Coefficient with a graph database structure is a powerful approach to representing and analyzing complex relationships between users and job postings in a modern recruitment platform.
Decision Support System for Determining Disease and Pest Handling in Chili Plants Using WP and VIKOR Methods Jalila, Muhammad Mulkan; Fuadi, Wahyu; Razi, Ar
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 3 (2025): JULY
Publisher : ISB Atma Luhur

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

Abstract

Abstract— Chili plants are an important horticultural commodity that plays a major role in the agricultural and economic sectors of Indonesia. However, the high risk of pest and disease attacks is a major challenge for farmers in increasing productivity. Many farmers have difficulty in determining the right handling strategy, so technology-based solutions are needed to assist the decision-making process. This study developed a Decision Support System (DSS) for handling diseases and pests in chili plants using two methods, namely Weighted Product (WP) and VIšekriterijumsko Kompromisno Rangiranje (VIKOR). The WP method is used to calculate attribute assessments by multiplication, where each criterion is weighted according to its level of importance. The final results show that the best alternative is fusarium wilt disease (Fusarium oxysporum) with code A2, having a vector score of 0.09899. In the VIKOR method, the alternative with the lowest Qi index value is considered the best solution. Alternative A2 is again ranked at the top with a Qi value of 0. The process of developing this DSS involves identifying disease and pest symptom criteria, normalizing the decision matrix, and calculating the ideal solution for each alternative. This approach has proven effective in providing accurate recommendations and helping farmers choose the most optimal management strategy. By utilizing WP and VIKOR-based SPK, it is hoped that chili farmers can increase efficiency in identifying and overcoming plant disorders, so that agricultural productivity can increase significantly.
Implementation of Singular Value Decomposition with Constraint Base Approach for Internship Recommendation System for Vocational High School Students Taufik, Nugraha Muhammad; Fuadi, Wahyu; Maryana, Maryana
Jurnal Ilmiah Global Education Vol. 6 No. 3 (2025): JURNAL ILMIAH GLOBAL EDUCATION
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/jige.v6i3.4179

Abstract

Vocational education in Indonesia, especially through Vocational High Schools, plays a crucial role in preparing students for the workforce. However, mismatches between student competencies and industry requirements often result in ineffective internship placements. This study focuses on SMK Negeri 2 Banda Aceh, where the internship placement process has been carried out manually and lacks an objective and personalized system. To address this challenge, a hybrid recommendation system was developed by combining Singular Value Decomposition with a constraint-based approach. The SVD method predicts student-industry compatibility by uncovering latent patterns in the rating data, while constraint-based filtering ensures that recommendations meet specific criteria such as major compatibility, skill alignment, and availability of industry capacity. The system was implemented as a web-based application using Python and MySQL, providing real-time recommendations with response times between one and three seconds. Testing with data from 344 students and more than 120 industry partners at SMK Negeri 2 Banda Aceh demonstrated the system’s ability to generate accurate and relevant recommendations. For example, although an industry with a predicted rating of 0.58 matched the student’s major and skills, it was not recommended due to full capacity. Instead, another industry with a lower predicted rating of 0.44 was recommended because it met all the required constraints. This system helps schools carry out internship placements more objectively, efficiently, and in alignment with student profiles and industry.
Co-Authors Aidilof, Hafizh Al Kautsar Akbar, Andry Maulana amri, maulana Andik Bintoro Aqsa, Dina Alfini Asran Asran Auji, Muhammad Fathah Badriana, Badriana Bakhtiar Bakhtiar Cut Ita Erliana Dedi Fariadi Eva Darnila Eva Darnila Fadlisyah Fadlisyah Fajriana, Fajriana Halimatun Sakdiah, Halimatun Harahap, Lina Mardiana Irwanda Syahputra Irwansyah, Defi Jabbar, Salamul Jalila, Muhammad Mulkan Kamilaini, Kamilaini Karmawati Karmawati Kausar, M Reza Khairawati Khairawati, Khairawati Kurniawati Kurniawati Kurniawati Lidya Rosnita Maryana Maryana Maryana Maryana, Maryana MUHAMMAD TEGUH, MUHAMMAD Munawarah Munawarah, Munawarah Mutammimul Ula Muthmainnah Muthmainnah Mutia Zahara mutiara mutiara Naturizal, Rayhan Novita, Lilis Nunsina, Nunsina Pohan, Muhammad Wahyu Putri, Husna Moetia Rahma, Putri Rahmawati M, Rahmawati Rahmawati, Rahmawati Ramadhansyah, Rizki Razi, Ar Rini Meiyanti Risawandi, Risawandi RISKA YANTI, RISKA Riza, Saiful Rozzi Kesuma Dinata Safwandi Sahputra, Ilham Saifuddin Muhammad Jalil Selamat Meliala Sofyan, Diana Khairani Sukatin, Sukatin Syintia, Icut Taufik, Nugraha Muhammad Teuku Multazam wandi, risa Yesy Afrillia Zahratul Fitri, Zahratul Zara Yunizar Zulfia , Anni Zuraida Zuraida