Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal Infotech Journal Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer
Wahyu Amaldi
Universitas Bina Bangsa
Computer Science & IT

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
SISTEM PAKAR REKOMENDASI JURUSAN DI SMK BERBASIS LARAVEL DENGAN METODE RULE-BASED REASONING DAN FORWARD CHAINING Agung Dumadi; Ahmad Munawir; Wahyu Amaldi
INFOTECH journal Vol. 11 No. 2 (2025)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/infotech.v11i2.15260

Abstract

The choice of major at the vocational high school level is a crucial factor influencing students' motivation, academic achievement, and future careers. However, the manual selection process often lacks objectivity and efficiency. This study designs and develops a web-based expert system for major recommendation using the Laravel framework with a rule-based reasoning approach. The system includes student biodata input, an interest questionnaire, a forward chaining inference engine, and an interactive admin dashboard. Development used the Waterfall model, while black-box testing and user acceptance testing (UAT) ensured accuracy and user acceptance. Test results show the system provides major recommendations matching student profiles, with additional details such as major descriptions, job prospects, and interest score visualizations. Furthermore, the UAT user satisfaction rate reached 85.25%, indicating the system is feasible to support a digital and objective major selection process.
GAME EDUKASI ADMINISTRASI ARSIP SURAT BERBASIS CONSTRUCT 2 DI BIRO UMUM SEKRETARIAT DAERAH Mochammad Darip; Ali Rochman; Wahyu Amaldi
INFOTECH journal Vol. 12 No. 1 (2026)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/infotech.v12i1.15275

Abstract

Pengelolaan arsip surat yang efektif merupakan elemen vital dalam menunjang efisiensi birokrasi dan akuntabilitas kerja di lingkungan pemerintahan. Namun, masih banyak pegawai yang memiliki pemahaman terbatas mengenai prosedur kearsipan, akibat kurangnya media pembelajaran yang menarik dan kontekstual. Penelitian ini bertujuan untuk mengembangkan aplikasi game edukasi sebagai media pembelajaran interaktif dalam memahami prosedur pengelolaan arsip surat di biro umum sekretariat daerah. Metode pengembangan yang digunakan adalah model ADDIE. Aplikasi dirancang berbasis Construct 2 dengan fitur utama berupa materi pengelolaan surat, simulasi permainan, serta pengenalan kode jenis surat. Hasil pengujian menunjukkan bahwa aplikasi dinilai sangat layak oleh pengguna, dengan mayoritas responden menyatakan sangat setuju terhadap manfaat, tampilan, dan kemudahan aplikasi. Temuan ini menunjukkan bahwa game edukasi dapat menjadi solusi inovatif dalam meningkatkan pemahaman kearsipan secara digital, khususnya bagi pegawai yang memiliki latar belakang non-arsiparis. Aplikasi ini juga berpotensi diterapkan sebagai media pelatihan berbasis kompetensi dalam sistem birokrasi pemerintahan.
Perancangan Aplikasi Pintar Monitoring Dan Deteksi Anomali BBM Menggunakan Machine Learning Di PT. BDR Solehudin Solehudin; Ahmad Munawir; Wahyu Amaldi
BETRIK Vol. 16 No. 02 (2025): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/cfdvkr55

Abstract

In the digital era, the need for technology-based monitoring systems is increasing, especially in the transportation and logistics industry. PT BDR faces challenges in reporting and monitoring fuel consumption for operational vehicles due to the manual recording process, making it difficult to detect anomalous data and making monitoring less efficient. This study aims to develop a web-based application capable of automatically monitoring and detecting fuel consumption anomalies by utilizing machine learning and deep learning technologies. The system development method uses the CRISP-DM approach, which includes the stages of business understanding, data understanding, data preparation, modeling, evaluation, and implementation. The Isolation Forest algorithm is used to detect anomalies based on fuel volume data, mileage, and vehicle consumption ratio, while the MobileNetV2-based Content-Based Image Retrieval (CBIR) method is applied to validate the suitability of gas station photos. The trained model is then integrated into the API using the Flask framework, with testing conducted through blackbox and whitebox testing. The test results show that the system is able to detect anomalies with a good level of accuracy and can be used practically by users. The implementation of this application is expected to improve the company's operational efficiency, reduce potential losses due to fuel misappropriation, and support the digitalization of the fuel monitoring process to be more accurate, effective, and integrated.
Co-Authors Agung Dumadi Ahmad Munawir Ali Rochman Mochammad Darip Solehudin Solehudin