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All Journal SMARTICS Journal SENTIA 2016 Citra Delima Scientific journal of Citra Internasional Institute Journal of Intelligent Decision Support System (IDSS) COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi Citra Delima Scientific journal of Citra Internasional Institute Nusantara Journal of Computers and its Applications Akiratech Khatulistiwa : Journal of Artificial Intelligence
Hasyim, Fuadz
Universitas Nurul Jadid
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Health Professions Mechanical Engineering Nursing Public Health Transportation Other

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Perancangan Sistem E-Learning Adaptif untuk Meningkatkan asil Belajar Siswa SD Negeri I Dawuan Syaiful, Syaiful; Hasyim, Fuadz
COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi Vol 4, No 2 (2023): Pengaruh Big Data Analytics terhadap Pengambilan Keputusan Strategis di Organisa
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/coreai.v4i2.7524

Abstract

Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem e-learning adaptif guna meningkatkan hasil belajar siswa di SD Negeri I Dawuan  . Latar belakang penelitian ini mencakup permasalahan rendahnya hasil belajar siswa di sekolah meliputi ; Motivasi siswa yang rendah kerena meteri yang disajikan terlalukaku, metode pengajaran yang tidak sesuai dengan gaya belajar siswa saat ini atau kurangnya variasi dalam pendekatan pembelajaran dapat menghambat pemahaman dan retensi materi, fasilitas dan sumber daya pembelajaran yang kurang memadai, baik di sekolah maupun di rumah, membatasi akses siswa terhadap materi pelajaran. Potensi teknologi e-learning adaptif sebagai solusi dalam meningkatkan efektivitas pembelajaran. Metode penelitian yang digunakan adalah studi literatur untuk menganalisis teori-teori pendukung dan teknologi e-learning adaptif, observasi di SD Negeri I Dawuan  untuk memahami kebutuhan dan tantangan yang dihadapi, serta analisis kebutuhan pengguna yang dilakukan melalui survei. Selanjutnya, berdasarkan hasil analisis, dilakukan perancangan sistem e-learning adaptif yang sesuai dengan kebutuhan pengguna dan kurikulum pendidikan yang berlaku. Rencana pembahasan mencakup tahapan implementasi sistem, pengujian, dan evaluasi untuk menilai kinerja dan efektivitas sistem e-learning adaptif yang telah dikembangkan. Kata kunci: e-learning adaptif, hasil belajar, SD Negeri I Dawuan.Kata kunci: e-learning adaptif, hasil belajar, SD Negeri I Dawuan.
Analisis Analisis Dan Perancangan Sistem Kredit Point Menggunakan Metode Ooad (Study Kasus Ma Dan Mts Taklimus Shibyan) Jasri, Moh.; Fuadz Hasyim; Nafilatul Azizah
SMARTICS Journal Vol 9 No 1 (2023): SMARTICS Journal (April 2023)
Publisher : Universitas PGRI Kanjuruhan Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/smartics.v9i1.7477

Abstract

The system for recording violation points and student achievement points at MTs and MA Taklimus Shibyan is currently not well integrated. Because the bookkeeping of violation points and achievements are in different ledgers. Credit Point calculation errors will have an impact on the score on the selection of the Student Star award candidate at every turn of the semester. With the Analysis and Design of a Student Credit Point Information System at MTs and MA Taklimus Shibyan, it is hoped that it can provide an overview of the Credit Point application that will make it easier for students to recap student Credit Points and determine student stars easily. Credit points are an installment system for recording violation points and achievement points to measure student discipline and non-discipline in facilitating school students in choosing class stars each semester. In this research, the system development method uses the OOAD (Oriented Object Analysis and Design) method. To make it easier for users to understand the designs made by researchers. So it is more efficient and easy. Based on the analysis and trials that have been carried out, it can be concluded that this research has resulted in the design of a Credit Point Information System for MA and MTs Taklimus Shibyan Students using the OOAD (Oriented Object Analysis and Design) method in accordance with the credit point rules in MA and MTs Taklimus Shibyan.  
Development of a web-based citizen contribution management system to optimize the financial management of community associations Rizal, Fathur; Fani, Ubed Dwi; Sonda, Bima Tsaqif Syahhama; Hakam, Syaif; Urip, Muhammad; Fuadz Hasyim
Journal of Intelligent Decision Support System (IDSS) Vol 7 No 4 (2024): December: Intelligent Decision Support System
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v7i4.279

Abstract

This research aims to develop a web-based citizen contribution management system at D'Tar Residence to improve financial efficiency and transparency. Manual management of citizen contributions often causes transparency problems and delays in payment recapitulation. This research method uses the Waterfall system development model which includes the stages of needs analysis, system design, implementation, testing, distribution, and maintenance. Data collection was carried out through interviews, observations, and literature studies involving housing association administrators. This application was developed using the PHP programming language with the CodeIgniter framework and MySQL database. System testing was carried out using the Black Box Testing method to ensure that the application functions according to residents' needs. The results of the study indicate that the developed application can improve the efficiency of citizen contribution management and provide more transparent access to financial information. However, there are three features that require further refinement. Overall, this application is expected to encourage citizen participation in decision-making related to housing finances and increase satisfaction with the financial management of the association.
Implementasi Data Mining Dalam Menentukan Strategi Promosi Program KB Menggunakan Algoritma K-Means Clustering Hasyim, Fuadz; Muafi, Muafi
COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi Vol 3, No 1 (2022): Pengembangan Aplikasi Berbasis Mobile untuk Layanan Publik: Studi Implementasi d
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1160.943 KB) | DOI: 10.33650/coreai.v3i1.4292

Abstract

Strategi promosi program KB yang dilakukan oleh pihak Badan Kependudukan dan Keluarga Berencana Nasional (BKKBN) melalui Balai Penyuluhan Program Keluarga Berencana (BPPKB) masih menyamaratakan seluruh daerah tanpa melihat keberhasilan program KB. Dibutuhkan analisis data agar strategi yang dilakukan bisa tepat sasaran. Data yang akan dianalisis merupakan data rekapitulasi kependudukan yang ada pada BPPKB. Untuk menganalisis data tersebut dibutuhkan metode atau teknik analisis data yang tepat yaitu dengan analisis data mining menggunakan algortima k-means clustering. Dengan cara melihat pola keterkaitan antar data yang digunakan sebagai penentu keberhasilan program KB, pihak BPPKB dapat dengan mudah dalam menentukan strategi promosi program KB hanya melihat pola data dari masing-masing klaster. Data penelitian diambil dari BPPKB Kecamatan Gading untuk data peserta KB aktif tahun 2019-2021, yang mencakup data dari 19 Desa di wilayah Kecamatan Gading Kabupaten Probolinggo. Dari hasil penelitian yang telah dilakukan didapatkan kesimpulan bahwa strategi promosi terbaik bagi calon peserta KB baru agar tepat sasaran adalah dengan mengirim tim admisi BPPKB yang sesuai dengan program KB yang paling banyak diminati dan melakukan promosi berdasarkan wilayah peserta KB baru dengan melakukan penyelarasan menggunakan promotion mix.
Analisis Sentimen Masyarakat Indonesia Terhadap Aplikasi TikTok Menggunakan Algoritma Logistic Regression Fathur Rizal; Andi Wijaya; Fuadz Hasyim
Akiratech Vol. 1 No. 2 (2024)
Publisher : CV. Akira Java Bulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63935/akiratech.v1i2.33

Abstract

Meningkatnya popularitas aplikasi TikTok di kalangan masyarakat Indonesia telah menimbulkan reaksi yang beragam dari masyarakat, memicu kebutuhan untuk analisis yang lebih mendalam mengenai sentimen publik terhadap platform ini. Penelitian ini bertujuan untuk memahami sikap yang dominan baik positif dan negatif terhadap TikTok di kalangan pengguna Indonesia. Dengan menggunakan algoritma Logistic Regression, yang dikenal dengan kemudahannya dan kapasitas interpretasi yang baik dalam klasifikasi sentimen, penelitian ini mengolah data ulasan pengguna yang diambil dari Google PlayStore. Analisis sentimen melibatkan tahapan pengambilan data, pra-pemrosesan (termasuk case folding, tokenisasi, normalisasi, dan stemming), serta pembobotan terms menggunakan TF-IDF. Hasil penelitian menunjukkan tingkat akurasi klasifikasi sentimen hampir sempurna, percobaan pertama (rasio 80:20) memberikan performa terbaik dengan akurasi 83%, yang menunjukkan efektivitas Logistic Regression dalam menganalisis sentimen. Performa model menunjukkan konsistensi dalam precision dan recall di semua rasio pengujian, mengindikasikan bahwa model tersebut cukup robust terhadap perubahan proporsi data pelatihan dan pengujian. Percobaan kedua dan ketiga juga memberikan perfoma yang baik pula dengan akurasi 81%.
Siamtek Unuja Security Analysis Using Two-Factor Algorithm Biometric Scan With Fingerprint zainal Arifin; Fuadz Hasyim
Khatulistiwa SMART: Science, Methodology, Artificial intelligence, Research, and Technology Vol 1 No 2 (2025): Juni 2025
Publisher : Khatulistiwa : Journal of Artificial Intelligence

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

Abstract

Student data security is a critical priority in academic information systems, particularly at Nurul Jadid University (UNUJA), which utilizes the SIAMTEK platform to manage practicum and final project activities. This study aims to analyze the effectiveness of implementing Two-Factor Authentication (2FA) using biometric fingerprint scanning to enhance the security of the SIAMTEK application. The research employed an experimental approach that included literature review, system analysis, system design, development, and testing. The authentication process consisted of two stages: verification via username and password, followed by a fingerprint scan. System testing was conducted using a Likert scale questionnaire distributed to 4th and 6th semester students, who are active users of the SIAMTEK application. The results indicated a 62% satisfaction index for the user interface and a 65% index for the functionality of the 2FA system. These results suggest that users are moderately satisfied with the added layer of security. Unlike One-Time Password (OTP) methods, which depend on mobile credit or connectivity, fingerprint biometric scanning offers a cost-effective and secure solution without requiring additional user expenses. This study also reviewed previous research on 2FA and Multi-Factor Authentication (MFA), highlighting the vulnerabilities of single-factor systems, particularly to phishing attacks and unauthorized access. The findings confirm that implementing fingerprint-based 2FA in the SIAMTEK system is both feasible and beneficial, significantly reducing risks of data breaches and account misuse. The integration of biometric technology as an additional authentication layer positively contributes to digital academic system security and supports data protection efforts for students' personal and academic information.
Web-Based Classification Optimization of Grape Leaf Diseases Using Transfer Learning in CNN to Improve Model Accuracy and Efficiency. Diana Indri Rukmana; Zainal Arifin; Fuadz Hasyim
Khatulistiwa SMART: Science, Methodology, Artificial intelligence, Research, and Technology Vol 2 No 1 (2025): Desember 2025
Publisher : Khatulistiwa : Journal of Artificial Intelligence

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

Abstract

Grapes are a high-value crop, but their yield is easily reduced due to leaf disease. This study focuses on developing a web-based grape leaf disease classification system that works automatically and in real time. The approach used is Convolutional Neural Network (CNN) with transfer learning using the EfficientNetB0 architecture. The research data consists of 8,000 grape leaf images divided into four classes (healthy, black rot, black spot, and leaf spot) with a composition of 80% for training, 10% for validation, and 10% for testing. The initial CNN model achieved an accuracy of 97%, which then increased to 99% after optimization using EfficientNetB0 with fine-tuning. The implementation of the system through Flask showed fast and accurate prediction results, proving that transfer learning plays an important role in improving classification performance.
Co-Authors Abdullah Faqih Andi Wijaya Andi Wijaya ANDI WIJAYA Diana Indri Rukmana Fani, Ubed Dwi Fathur Rizal Hakam, Syaif Jasri, Moh. Khairi, Ahmad Malik, Kamil Mochammad Faid Muafi Musleh Al Hayubi Nafilatul Azizah Samsul Arifin Shudiq, Wali Ja'far Sonda, Bima Tsaqif Syahhama Syaiful . Urip, Muhammad Widjiyanto Widjiyanto Yudistira Yudistira Zainal Arifin Zainal Arifin Zainal Arifin Zainal Munir