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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JTT (Jurnal Teknologi Terpadu) JSAI (Journal Scientific and Applied Informatics) International Journal of Informatics and Computation REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Jurnal E-Komtek Jurnal Teknologi Informatika dan Komputer Jurnal Restikom : Riset Teknik Informatika dan Komputer Jurnal Ilmiah Wahana Pendidikan Journal of Technology and Informatics (JoTI) Bulletin of Information Technology (BIT) Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Pengabdian Pelitabangsa Indonesian Journal of Multidisciplinary on Social and Technology JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah VIDHEAS: Jurnal Nasional Abdimas Multidisiplin SAINTEK International Journal of Integrated Science and Technology Jurnal Ekonomi Manajemen Dan Bisnis (JEMB) Akademika Jurnal Teknologi Pendidikan
Ahmad Turmudi Zy
UNiversitas Pelita Bangsa
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering 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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences Other

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PERANCANGAN KLASIFIKASI ALGORITMA NAIVE BAYES PADA DATA PEMILIHAN JURUSAN SISWA Juan Fakhri; Aswan Supriyadi Sunge; Ahmad Turmudi zy
Jurnal Teknologi Terpadu Vol 11, No 2 (2023): JTT (Jurnal Teknologi Terpadu)
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32487/jtt.v11i2.1823

Abstract

Penelitian yang berjudul "Perancangan Algoritma Naive Bayes Dalam Klasifikasi Pemilihan Jurusan Siswa". Penelitian ini bertujuan untuk pembuatan suatu prediski dan impelemtasi metode dalam kalsifikasi Naive Bayes, serta untuk mengevaluasi dampak ketidak seimbangan kelas terhadap kinerja model klasifikasi. Penelitian ini juga menemukan adanya kelebihan sampel data secara tidak sengaja, dan eksperimen dengan menggunakan teknik SMOTE dilakukan untuk mengatasi ketidak seimbangan kelas tersebut. Data pemilihan jurusan siswa dari SMA Negeri 2 Cikarang Selatan digunakan untuk mengidentifikasi ketidak seimbangan kelas. Eksperimen ini membandingkan hasil klasifikasi sebelum dan setelah penerapan teknik SMOTE. Hasil analisis menunjukkan bahwa sebelum menggunakan teknik SMOTE, terdapat ketidak seimbangan kelas yang signifikan dalam data pemilihan jurusan siswa. Ketidak seimbangan ini memiliki dampak negatif terhadap kinerja model klasifikasi, terutama dalam mengenali kelas minoritas. Namun, setelah penerapan teknik SMOTE, ketidak seimbangan kelas berhasil dikurangi dan kinerja model klasifikasi mengalami peningkatan yang signifikan. Recall untuk kelas IPS meningkat menjadi 0,76, sementara recall untuk kelas MIPA tetap tinggi dengan nilai 0,92. Precision untuk kelas IPS meningkat menjadi 0,87, sedangkan precision untuk kelas MIPA tetap stabil di 0,85. Dengan menggunakan precision dan recall, skor F1 mencapai 0,8846. Berdasarkan temuan penelitian ini, dapat disimpulkan bahwa kinerja model klasifikasi dalam memilih jurusan siswa dapat dipengaruhi oleh kelebihan sampel data. Metode SMOTE efektif dalam mengurangi ketidak seimbangan kelas dan meningkatkan kinerja model klasifikasi. Metode Naive Bayes dapat digunakan sebagai alternatif yang efektif dalam memprediksi penjurusan siswa di SMA Negeri 2 Cikarang Selatan setelah menerapkan teknik SMOTE.
Pengebangan Media Pembelajaran Berbasis Android Untuk Pengenalan Huruf Hijaiyah di TK Islam Pelita Insan Agung Nugroho; Wiyanto Wiyanto; Ahmad Turmudi Zy
VIDHEAS: Jurnal Abdimas Multidisiplin Vol. 1 No. 1 (2023): Juni 2023
Publisher : VINICHO MEDIA PUBLISINDO

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

Abstract

Teknologi makin berkembang seiring dengan perkembangan jaman, begitu juga dalam bidang Pendidikan. Pemanfaatan teknologi menjadi hal yang penting diterapkan dalam bidang pembelajaran. Kegiatan pengabdian ini dalam rangka meningkatkan kualitas pembelajaran dengan memanfaatkan teknologi informasi sebagai sarana mendukung proses pembelajaran yang interaktif melalu penerapan game edukasi dalam mengenal huruf hijaiyah.
Dampak Game Terhadap Anak Usia Dini Edora Edora; Ahmad Turmudi Zy
Prosiding Sains dan Teknologi Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/SAINTEK0101.9195

Abstract

Digital technology changes many aspects of the daily life of Indonesian people, from socializing to education, from formal and informal matters to all involving digital technology, and this also involves all age groups, from early childhood to the elderly. There are also many digital games that are loved by all ages. The problem is the impact of digital-based games using mobile phones or tablets. Here the author focuses on research on the impact of digital games on an early age in terms of benefits on the growth and development of early childhood, in this paper some research from various parties who are competent in this research will be presented. those it can be concluded that there are positive and negative impacts of digital games (games) in early childhood. Keywords: Digital Technology, Game, Childhood, Impact.
Web-Based Grape Seed Information System Using the Agile Methodology for the Cikarang Grape Community Ahmad Turmudi Zy; Bagas Pamungkas; Sunita Dasman; M.Makmun Effendi; Rosa Noviyanti
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 8 No 2 (2024)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v8i2.2149

Abstract

This research applies the Agile methodology to develop a web-based grape seed information system for the Cikarang Grape Community. This method was chosen to enhance flexibility and responsiveness in development, with active involvement from community members at every stage. The process begins with a needs analysis through surveys and interviews, followed by an iterative user-focused solution design. Development is conducted in sprints, allowing features to be tested and evaluated regularly. The implementation results show that the system not only improves efficiency in managing and distributing grape seeds but also strengthens cooperation among community members. With transparent and real-time data access, the community is better equipped to make informed decisions regarding production and marketing. This research is expected to serve as a model for future similar information system development.
MEDIA PEMBELAJARAN HURUF HIJAIYAH UNTUK ANAK USIA DINI BERBASIS GAME ANDROID Ahmad Turmudi Zy; Edora Edora
Akademika Vol 11 No 02 (2022): Akademika : Jurnal Teknologi Pendidikan
Publisher : Akademika : Jurnal Teknologi Pendidikan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34005/akademika.v11i02.2019

Abstract

As religious people we must fortify ourselves as early as possible with the provision of religious knowledge. One of them is in reading the Koran. For early childhood, the initial stage of reading the Koran is being able to master the hijaiyah letters. The problem in this research is the lack of interest in children's learning and the lack of media that is applied in the process of learning hijaiyah letters. The media used is still conventional so that the learning objectives are not achieved optimally. Therefore, a learning media for early childhood was made in the form of an Android-based educational game. This research applies the MDLC (Multimedia Development Life Cyrcle) method. Testing the functional requirements in this application through the stages of black box testing. The black box test results are 100%, meaning that this application is in line with user needs and all functions run according to functional requirements. Therefore, it can be concluded that this educational game is attractive and effective in increasing hijaiyah letter learning skills
Sentiment Analysis on Canva Reviews Using Naive Bayes Method Faiza Muhammad Julianto; Ahmad Turmudi Zy; Elkin Rilvani
International Journal of Informatics and Computation Vol. 7 No. 1 (2025): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v7i1.107

Abstract

Sentiment analysis for user review is a growing research topic in digital applications. In this study, we analyze user reviews from the Google Play Store to classify sentiments as positive or negative. The primary objective of this research is to evaluate the performance of the Naive Bayes classifier in sentiment classification. The methodology involves comprehensive data preprocessing, model training, and evaluation using performance metrics such as accuracy, precision, recall, and F1-score. The results indicate that the proposed model achieves an accuracy = 92%, precision = 85%, recall = 88%, and F1-score= 86%, respectively. These findings show the effectiveness of the proposed method that can extract valuable insights from user reviews to increase user satisfaction.
Strengthening Web-Based Login Security Using Vigenère Cipher and AES ENCRYPT() Method in MySQL Rhendy Diki Nugraha; Muhamad David Ali; Nadya Khairunnisa; Danang Nurcahyo; Ahmad Turmudi Zy
Journal of Technology and Informatics (JoTI) Vol. 7 No. 1 (2025): Vol. 7 No.1 (2025)
Publisher : Universitas Dinamika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37802/joti.v7i1.954

Abstract

As technology advances further, more crimes are being committed on social media. These days, people can connect to the internet using technological devices like PCs (Personal Computers) or portable electronic devices like smartphones or tablets. This study presents a dual-layer encryption system combining the Vigenère Cipher and MySQL’s AES_ENCRYPT() to enhance the security of web-based login systems. The system encrypts user credentials on the client side using the Vigenère Cipher and applies additional encryption on the server side with AES_ENCRYPT(). This approach ensures secure data transmission and storage, reducing risks of plaintext exposure and unauthorized access. Comparative testing demonstrated that the dual-layer encryption method significantly improves resistance to brute-force attacks and database breaches compared to conventional techniques like SHA-256. Encrypted credentials remain secure even in the event of a database compromise, as decryption requires the correct secret keys. The system’s design also highlights the importance of robust key management to maintain data confidentiality and integrity. While this method introduces minor performance overhead and requires careful implementation, its advantages in safeguarding sensitive user information outweigh these limitations. This dual-layer approach is particularly suited for applications demanding high-security standards, making it a viable solution for mitigating contemporary cyber threats effectively.
Enhancing Network Security: Evaluating SDN-Enabled Firewall Solutions and Clustering Analysis Using K-Means through Data-Driven Insights Ahmad Turmudi Zy; Isarianto; Rifa’i, Anggi Muhammad; Nugroho, Agung; Ghofir, Abdul
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 1 (2025): February 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i1.6056

Abstract

In the face of escalating and increasingly complex cyber threats, enhancing network security has become a critical challenge. This study addresses this issue by investigating the optimization of SDN-enabled firewall solutions using a data-driven approach. The research employs K-Means clustering to analyze attack patterns, aiming to identify and understand distinct patterns for improved firewall effectiveness. Through the clustering process, attack data was classified into three clusters: Cluster 0, indicating concentrated attack sources likely tied to high-activity regions or networks; Cluster 1, representing a dispersed distribution of attacks, pointing to diverse origins; and Cluster 2, linked to specific geographic regions or unique attack behaviors. The clustering efficacy was evaluated using the Silhouette Score (0.606) and the Davies-Bouldin Index (0.614), indicating meaningful and reliable clustering outcomes. These findings provide actionable insights into network threat patterns, enabling the refinement and enhancement of SDN-enabled firewalls. The study contributes to the field by demonstrating the potential of clustering techniques in uncovering patterns overlooked by traditional methods and paving the way for further research into alternative clustering algorithms and broader applications in network security.
Eye Disease Detection and Classification Optimization Using EfficientNet-B5 with Emphasis on Data Augmentation and Fine-Tuning Anggi Muhammad Rifai; Muhammad Fatchan; Ahmad Turmudi Zy; Donny Maulana; Sufajar Butsianto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 5 (2025): October 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i5.6519

Abstract

Eye diseases such as glaucoma, cataract, and diabetic retinopathy pose significant global health challenges, underscoring the need for accurate and efficient diagnostic systems. This study employed the EfficientNet-B5 model to enhance the detection and classification of eye diseases by incorporating advanced data augmentation and fine-tuning techniques. The research utilizes the Ocular Disease Intelligent Recognition (ODIR) dataset, consisting of 4,217 fundus images categorized into four classes: normal, glaucoma, cataract, and diabetic retinopathy. The methodology comprises three phases: baseline model training, model training with data augmentation, and fine-tuning. The baseline model achieved an accuracy of 60.43%, which improved to 63.03% with data augmentation—an increase of 2.6 percentage points. Fine-tuning further elevated the accuracy to 93.23%, representing a notable improvement of 33.8 percentage points over the baseline. Model performance was evaluated using standard classification metrics including accuracy, precision, recall, and F1-score. These findings demonstrate the technical efficacy of combining augmentation and fine-tuning to enhance model generalization. The proposed approach offers a robust framework for developing dependable AI-driven diagnostic tools to support early detection and facilitate informed clinical decision-making.
Advanced ANN Techniques for Precise Detection and Classification of Welding Defects Faza Ardan Kusuma; Muhammad Fatchan; Ahmad Turmudi Zy
International Journal of Integrated Science and Technology Vol. 2 No. 5 (2024): May 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijist.v2i5.1907

Abstract

The implementation of the artificial neural network (ANN) algorithm for detecting and classifying welding defects is detailed in this study. A total of 558 welding workpiece images were processed using techniques such as resizing, auto-orientation, flipping, rotation, and annotation, ultimately expanding the dataset to 1,288 images. Feature extraction identified 24 traits across 12,000 data points, which were then condensed to 5,735 data points for the ANN model. The model employed 100 hidden layers, the ReLU activation function, and the L-BFGS-B solver, running for 200 iterations. The configuration achieved near-perfect results, with metrics such as the area under the curve (AUC), classification accuracy, and F1 score averaging a precision of 0.97. These outcomes demonstrate the ANN model's high efficacy in detecting and classifying welding defects, underscoring its potential application for quality assurance in the welding industry. Further investigation into specific defect types, including porosity, spatter, cracks, and undercuts, could further improve detection accuracy.
Co-Authors Abdul Ghofir Agung Nugroho Ahmad Rivaldi Anggi Muhammad Rifa'i Anggi Muhammad Rifai Annaas Nurhuda Asidiq Antika Zahrotul Kamalia Aprilia Nur Sa'adah Ary Fahrizal Aswan S Sunge Aswan S Sunge Aswan S. Sunge Aswan Supriyadi Sunge Bagas Pamungkas Butsianto, Sufajar Danang Nurcahyo Daspar Daspar Diani Putri Kusumaningrum Donny Maulana Edora Edora Edora Edora Edy Widodo Elkin Rilvani Endrik Ermanto Ermanto Faiza Muhammad Julianto Faza Ardan Kusuma Gufranaka Samudra Hendi Herlambang Irfan Afriantoro Irma Nurmaulida* Isarianto Juan Fakhri Lutfi Adji Ardiansyah M.Makmun Effendi Maha Putra Miftahuljannah Mudakir Muhamad David Ali Muhamad Fatchan Muhammad Adipa Muhammad Fatchan Muhammad Makmun Effendi Muhtajuddin Danny Nadya Khairunnisa Nugroho, Agung Putri Nurhafenda Harun Qori yumansyah Qori Ray Fathur Rizky Rhendy Diki Nugraha Riani Riani Rismawati Rismawati Rosa Noviyanti Sunita Dasman Suprapto Suriyanti Suriyanti Wira Syuhada Wiyanto Wiyanto Zaenur Rozikin Zaky Ali Husaeni