Article Per Year (5 Year)
p-Index From 2021 - 2026
4.573
P-Index
This Author published in this journals
All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Journal of Electrical Technology METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Serambi Engineering KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Djtechno: Jurnal Teknologi Informasi Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) Journal of Renewable Energy, Electrical, and Computer Engineering TECHSI - Jurnal Teknik Informatika Jurnal Malikussaleh Mengabdi Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) INOVTEK Polbeng - Seri Informatika JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) ITEJ (Information Technology Engineering Journals)
Wahyu Fuadi
Universitas Malikussaleh
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Social Sciences Other

Published : 30 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 30 Documents
Search

 1   2   3 
CLUSTERING TINGKAT KECANDUAN GAME MOBILE LEGENDS TERHADAP KEHARMONISAN KELUARGA MENGGUNAKAN METODE K-MEANS Muhammad Fadhil; Wahyu Fuadi; Maryana
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6439

Abstract

Penelitian ini bertujuan untuk menganalisis tingkat kecanduan game Mobile Legends dan dampaknya terhadap keharmonisan keluarga menggunakan pendekatan machine learning dengan algoritma K-Means Clustering. Metode penelitian menggunakan pendekatan kuantitatif dengan mengumpulkan data dari 297 responden melalui kuesioner yang mencakup 10 variabel, terdiri dari 5 variabel addiction dan 5 variabel keharmonisan. Data yang terkumpul kemudian diproses menggunakan preprocessing dengan teknik encoding dan scaling, selanjutnya dianalisis menggunakan algoritma K-Means Clustering dengan optimasi jumlah cluster melalui kombinasi Elbow Method, Silhouette Analysis, dan Davies-Bouldin Index. Hasil penelitian menunjukkan bahwa algoritma K-Means berhasil mengidentifikasi tiga cluster optimal (K=3) dengan kualitas clustering yang memadai, ditunjukkan oleh Davies-Bouldin Index sebesar 1.580, Silhouette Score 0.233, dan Inertia 2089. Distribusi cluster menunjukkan bahwa 60.3% responden berada dalam kategori kecanduan ringan dengan keharmonisan tinggi (Cluster 1), 32.7% dalam kategori sedang-sedang (Cluster 0), dan 7.1% dalam kategori kecanduan berat dengan keharmonisan rendah (Cluster 2). Temuan utama penelitian mengkonfirmasi hipotesis adanya hubungan invers yang signifikan antara tingkat kecanduan game Mobile Legends dengan keharmonisan keluarga, dimana semakin tinggi tingkat kecanduan semakin rendah keharmonisan keluarga. Principal Component Analysis menunjukkan bahwa dua komponen utama mampu menjelaskan 60% varians data, memberikan validasi visual terhadap hasil clustering. Penelitian ini memberikan kontribusi penting dalam memahami dampak psikologis gaming addiction terhadap dinamika keluarga dan dapat menjadi dasar pengembangan strategi intervensi yang tepat sasaran untuk meningkatkan keharmonisan keluarga.
ANALISIS SENTIMEN REVIEW APLIKASI STOCKBIT DI GOOGLE PLAY STORE DAN X(TWITTER) MENGGUNAKAN SUPPORT VECTOR MACHINE: SENTIMENT ANALYSIS OF STOCKBIT APPLICATION REVIEWS ON GOOGLE PLAY STORE AND X (TWITTER) USING SUPPORT VECTOR MACHINE Yusril; Wahyu Fuadi; Yesy Afrillia
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6446

Abstract

This study examines sentiment analysis of user reviews of the Stockbit application obtained from the Google Play Store and platform X (formerly Twitter). The aim of this research is to classify user opinions into two sentiment categories: positive and negative, using the Support Vector Machine (SVM) method. A total of 3,000 review data points were used in this study, consisting of 2,100 training data points and 900 test data points (stratified split with a 70:30 ratio) to ensure balanced sentiment distribution. The research process includes text preprocessing, feature weighting using Term Frequency-Inverse Document Frequency (TF-IDF), sentiment classification with the SVM algorithm, and model performance evaluation. Based on the evaluation results, the SVM model demonstrated high performance with an accuracy of 95.5%, precision of 93.5%, recall of 97.4%, and an F1-score of 95.3%. Although its accuracy is lower than that of Maulana et al.'s (2024) study, which achieved 99.50% on the Pluang application, this research excels in using data from two different platforms and evaluating class imbalance, making the analysis results more representative of real-world conditions. These findings indicate that SVM remains an effective method for text-based sentiment analysis in digital financial service applications.
PERANCANGAN GAME EDUKASI INTERAKTIF BERBASIS WEB UNTUK PEMBELAJARAN SIRAH NABAWIYAH DENGAN SISTEM ADAPTIF MENGGUNAKAN FUZZY LOGIC: DESIGN OF A WEB-BASED INTERACTIVE EDUCATIONAL GAME FOR LEARNING SIRAH NABAWIYAH WITH AN ADAPTIVE SYSTEM USING FUZZY LOGIC Mirza Mirza; Wahyu Fuadi; Rini Meiyanti
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6533

Abstract

This study aims to develop a web-based interactive educational game designed specifically to help students understand the subject of Sirah Nabawiyah in a more engaging and adaptive way. In its development, the system adopts a fuzzy logic approach as an adaptive method that allows the adjustment of question difficulty levels based on each user’s ability. The system utilizes parameters such as score, response speed, and answer accuracy, which are processed to classify users into three ability categories: Advanced, Intermediate, or Beginner. The development process follows the waterfall methodology through the stages of needs analysis, system design, implementation, and testing. Black box testing results indicate that all features function properly and the system is capable of delivering accurate adaptive responses. Furthermore, trials conducted with 30 elementary school students showed a 28% improvement in material comprehension, based on a comparison between pre-test and post-test results before and after using the educational game. Thus, the implementation of fuzzy logic in this educational game provides a tangible contribution to technological innovation in Islamic education, particularly in delivering religious content in a digital and enjoyable manner for elementary students.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN SUNSCREEN KULIT BERJERAWAT MENGGUNAKAN METODE FUZZY ANALYTICAL HIERARCHY PROCESS Elvina Mutiara Vina; Wahyu Fuadi; Yesy Afrillia
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.7744

Abstract

Tingginya paparan sinar ultraviolet di wilayah tropis meningkatkan urgensi penggunaan sunscreen, terutama bagi pemilik kulit berjerawat yang memerlukan ketelitian dalam memilih produk agar tidak memperburuk kondisi kulit. Banyaknya pilihan merek di pasaran sering kali menimbulkan kesulitan bagi konsumen dalam menentukan produk yang paling sesuai. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem pendukung keputusan (SPK) pemilihan merek sunscreen terbaik untuk kulit berjerawat menggunakan metode Fuzzy Analytical Hierarchy Process (F-AHP). Metode ini dipilih karena mampu mengakomodasi ketidakpastian dan subjektivitas dalam penilaian kriteria. Data diperoleh melalui observasi, wawancara, dan kuesioner kepada 300 responden. Kriteria yang digunakan meliputi harga, tekstur, komposisi, kandungan SPF, dan jenis sunscreen. Hasil penelitian menunjukkan bahwa komposisi bahan merupakan kriteria paling dominan, diikuti oleh tekstur produk. Berdasarkan hasil perhitungan F-AHP, Azarine Calm My Acne Sunscreen meraih peringkat pertama dengan skor 0,6876, disusul oleh Facetology Triple Care Sunscreen (0,6371) dan Wardah UV Shield Acne Calming Sunscreen (0,6297).
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN JURUSAN SEKOLAH PADA MAN MENGGUNAKAN METODE WASPAS Rifky Firzani Marpaung; Wahyu Fuadi; Hafizh Al Kautsar Aidilof
TECHSI - Jurnal Teknik Informatika Vol. 15 No. 1 (2024)
Publisher : Teknik Informatika Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/techsi.v15i1.19471

Abstract

Penentuan jurusan sekolah pada Madrasah Aliyah Negeri (MAN) merupakan proses penting yang harus mempertimbangkan berbagai faktor seperti nilai akademik, minat, dan bakat siswa. Namun, penentuan jurusan sering kali masih dilakukan secara manual, sehingga kurang efisien dan memerlukan waktu yang lama. Penelitian ini bertujuan untuk merancang dan membangun Sistem Pendukung Keputusan (SPK) berbasis web yang menggunakan metode Weighted Aggregated Sum Product Assessment (WASPAS) guna membantu pihak sekolah dalam menentukan jurusan yang sesuai dengan kemampuan siswa. SPK ini menggabungkan berbagai kriteria seperti nilai raport, hasil tes akademik, serta kemampuan praktek untuk memberikan rekomendasi penjurusan yang optimal. Metode WASPAS dipilih karena kemampuannya dalam mengkombinasikan metode Weighted Sum Model (WSM) dan Weighted Product Model (WPM), yang menghasilkan perhitungan yang lebih akurat. Hasil pengujian menunjukkan bahwa sistem yang dibangun mampu memberikan rekomendasi jurusan dengan lebih cepat dan efektif dibandingkan dengan metode manual. Sistem ini diharapkan dapat membantu sekolah dalam mengelola penjurusan siswa dengan lebih efisien dan objektif.
PkM Pemanfaatan Artificial Intelligence Writing Tools untuk Melatih Skill Siswa Fakhruddin Ahmad Nasution; Syarifah Asria Nanda; Khairul Amna; Veri Ilhadi; Emi Maulani; Wahyu Fuadi
Jurnal Malikussaleh Mengabdi Vol. 5 No. 1 (2026): Jurnal Malikussaleh Mengabdi, Januari 2026
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jmm.v5i1.25194

Abstract

Pemanfaatan Artificial Intelligence (AI) Writing Tools dalam dunia pendidikan semakin berkembang seiring dengan kemajuan teknologi digital. Penelitian ini bertujuan untuk menganalisis peran dan efektivitas penggunaan alat bantu berbasis kecerdasan buatan dalam melatih keterampilan menulis siswa. AI writing tools, seperti ChatGPT, Grammarly, dan QuillBot, mampu memberikan umpan balik otomatis, memperbaiki kesalahan tata bahasa, serta memberikan saran perbaikan gaya penulisan secara instan. Melalui pemanfaatan teknologi ini, siswa dapat belajar menulis dengan lebih interaktif dan mandiri. Metode penelitian yang digunakan bersifat deskriptif kualitatif dengan mengkaji literatur dan studi kasus terkait penggunaan AI dalam proses pembelajaran menulis. Hasil penelitian menunjukkan bahwa penggunaan AI writing tools mampu meningkatkan kemampuan siswa dalam aspek struktur kalimat, kosakata, dan konsistensi ide. Selain itu, siswa menunjukkan peningkatan motivasi belajar karena proses umpan balik yang cepat dan personal. Namun demikian, terdapat tantangan dalam hal ketergantungan siswa terhadap alat bantu serta potensi menurunnya kemampuan berpikir kritis jika tidak diimbangi dengan bimbingan guru. Oleh karena itu, diperlukan integrasi antara penggunaan AI writing tools dengan pendekatan pembelajaran konvensional yang berfokus pada kreativitas dan orisinalitas. Kesimpulannya, AI writing tools memiliki potensi besar sebagai media pendukung pembelajaran menulis yang efektif, asalkan digunakan secara bijak dan terarah dalam konteks pendidikan yang menumbuhkan kemandirian berpikir serta kemampuan literasi digital siswa.
Implementation of VRRP for Internet Optimization at Class I Sultan Iskandar Muda Meteorological Station - Banda Aceh Kasihan Muhammad Fajar; Wahyu Fuadi; Yesy Afrillia
Journal of Renewable Energy, Electrical, and Computer Engineering Vol. 4 No. 1 (2024): March 2024
Publisher : Institute for Research and Community Service (LPPM), Universitas Malikussaleh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jreece.v4i1.15812

Abstract

Class I Sultan Iskandar Muda - Banda The Aceh Meteorological Observatory is an environmental engineering implementing agency for observation and data processing, under the responsibility of the Meteorology, Climatology and Geophysical Agency. When using a government agency`s Internet network, failures such as unstable connections, failures, errors, and broken main routers often occur. If the main router goes down, no backup is available. To avoid this, a backup router must exist. Therefore, in this study, we apply an implementation of the virtual redundant router protocol to optimize the Internet network. The reseacrh aims explore to investigate the quality of WiFi network services. Researchers use her QoS analysis using packet loss, delay, and jitter parameters. Testing was conducted using Wireshark software during peak office hours in January and February 2023. The latency parameter findings were 3.49 ms in January and 4.89 ms in February on the main router (very good). The average jitter parameter was 3.49ms in January and 4.89ms in February (very good). The packet loss parameter is 2.05% (good) in February, while the overall average value in January is 0.83%. Overall, the calculation of the three parameters according to the TIPHON standardization is within a good range. His implementation of VRRP at the Sultan Iskandar Muda Weather Observatory proves the effectiveness of his VRRP in improving network availability and reliable backup systems.
Classification of Coronary Heart Disease Based on Community Health Centre Medical Record Data Using SVM Algorithm M Reza Kausar; Wahyu Fuadi; Zahratul Fitri
Journal of Innovation and Technology Polbeng Series on Informatics (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.
ANALISIS SENTIMEN MASYARAKAT TERHADAP PEMERINTAH DI ERA KABINET PRABOWO SUBIANTO BERDASARKAN SOSIAL MEDIA X MENGGUNAKAN NAÏVE BAYES CLASSIFIER Adetia Irvanda; Wahyu Fuadi; Maryana Maryana
Djtechno: Jurnal Teknologi Informasi Vol 7, No 2 (2026): Agustus
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v7i2.9459

Abstract

Kebijakan awal pemerintahan Kabinet Prabowo Subianto memicu beragam opini masyarakat di media sosial X, namun opini tersebut belum terklasifikasi ke dalam polaritas sentimen sehingga sulit dijadikan bahan evaluasi. Penelitian ini bertujuan mengimplementasikan dan mengevaluasi algoritma Naïve Bayes Classifier (NBC) dalam mengklasifikasikan sentimen masyarakat terhadap pemerintahan Kabinet Prabowo Subianto ke dalam kelas positif, negatif, dan netral. Sebanyak 587 tweet dikumpulkan melalui teknik scraping sejak 20 Oktober 2024, kemudian diproses melalui enam tahap text preprocessing, dilabeli otomatis menggunakan InSet Lexicon, dan dibobotkan dengan TF-IDF yang menghasilkan 317 fitur. Data dibagi 70:30 secara stratified menjadi 410 data latih dan 177 data uji, lalu diklasifikasikan menggunakan Multinomial Naïve Bayes dengan Laplace smoothing α=1,0. Hasil pelabelan menunjukkan dominasi sentimen negatif sebesar 55,7% (327 tweet), diikuti netral 30,7% (180 tweet) dan positif 13,6% (80 tweet). Model memperoleh akurasi 61,58% dengan presisi weighted 60,39%, recall weighted 61,58%, dan F1-score weighted 55,60%. Ketidakseimbangan kelas menyebabkan model bias terhadap kelas negatif, sehingga penyeimbangan data disarankan pada penelitian berikutnya.
Sistem Pendeteksi Tingkat Kesegaran Daging Ayam pada Citra Menggunakan Metode Convolutional Neural Network (CNN) Berbasis Android Rayhan Naturizal; Wahyu Fuadi; Lidya Rosnita
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 2 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No2.pp301-312

Abstract

This research develops a chicken meat freshness detection system based on image processing, implemented on an Android platform using the Convolutional Neural Network (CNN) method optimized with TensorFlow Lite. The system classifies chicken meat into three categories: fresh, less fresh, and rotten. The CNN model uses 32 filters to enhance feature extraction from the meat images. Testing on 30 samples, with each category tested 10 times, showed an accuracy of 90%, with 27 correct detections and 3 errors in the less fresh category. While the system effectively identifies fresh and rotten categories, there is a challenge in distinguishing the less fresh category due to its ambiguous visual characteristics. One limitation is the lack of a bounding box, causing the application to still provide detection results even when the scanned object is not chicken meat. This application is specifically designed to detect chicken meat pieces, so it is not recommended for use outside this context.
Co-Authors Adetia Irvanda Aina Rahmadani Ar Razi Ar Razi Arifinal Ayu Indah Lestari Ayu Ramazani Dedi Fariadi Elvina Mutiara Vina Emi Maulani Ermatita Ermatita Ermatita Ermatita Eva Darnila Eva Darnila Fadlisyah Fadlisyah Faizar Abdurrahman Fajriana, Fajriana Fakhruddin Ahmad Nasution Hafizh Al Kautsar Aidilof Hafizh Al Kautsar Aidilof Iwan Pahendra Kamilaini Kamilaini Kasihan Muhammad Fajar Khairul Amna Kurniawati Lidya Rosnita Lina Mardiana Harahap M Reza Kausar Maryana Maryana, Maryana Maulana Amri Mirza Mirza Muhammad Fadhil Muhammad Ihsan Muhammad Sadli Muhammad Sadli, Muhammad Muhammad Wahyu Pohan Nunsina, Nunsina Nurul Islami, Nurul Putri Rahma Rahmawati M Rayhan Naturizal Rifky Firzani Marpaung Rifky Firzani Marpuang Rini Meiyanti Risawandi, Risawandi Riska Yanti Safwandi Salamul Jabbar Selamat Meliala Syarifah Zahra Veri Ilhadi Yesy Afrillia Yusril Zahidi Pratama Zahratul Fitri