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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JTT (Jurnal Teknologi Terpadu) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab 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 International Journal of Educational and Life Sciences (IJELS) Jurnal Pelita Pengabdian SAINTEK International Journal of Integrated Science and Technology Jurnal Ekonomi Manajemen Dan Bisnis (JEMB) Cahaya Pengabdian Akademika Jurnal Teknologi Pendidikan
Ahmad Turmudi Zy
UNiversitas Pelita Bangsa
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy 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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UMKM Kreatif Karangbahagia Menuju Pasar Digital Syuhada, Wira; Maha Putra; Ahmad Turmudi Zy
Jurnal Ekonomi Manajemen Dan Bisnis (JEMB) Vol. 1 No. 6 (2024): Juli
Publisher : Publikasi Inspirasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62017/jemb.v1i6.1685

Abstract

Micro, Small and Medium Enterprises (MSMEs) in the creative industry sector have great potential in driving economic growth. However, the main challenge faced by MSMEs is limited market access, especially in the current digital economy era. The development of information technology and e-commerce platforms opens new opportunities for MSMEs to expand their marketing reach and increase competitiveness. This research aims to design a human resource development program for creative industry MSMEs in Cikarang Baru in effectively utilizing e-commerce platforms. The research methodology used is a mixed method approach with data collection techniques through surveys, in-depth interviews, and literature studies. Surveys are conducted to identify the profiles, challenges, and opportunities of creative industry MSMEs in Cikarang Baru. In-depth interviews are conducted to explore more information about the constraints and obstacles in utilizing e-commerce platforms as well as the need for human resource development. The research results show that most MSMEs have not optimally utilized e-commerce platforms due to limited knowledge and skills of human resources in managing online sales. The proposed development program includes training, assistance, and capacity building for human resources to operate and manage sales through e-commerce effectively. The development materials cover digital marketing strategies, product and content optimization, online store management, and customer service. With the improvement of human resource skills through this program, it is hoped that creative industry MSMEs in Cikarang Baru can increase market access, expand their marketing reach, and improve competitiveness in the digital economy era
Implementasi Algoritma K-Nearest Neighbors Untuk Klasifikasi Spam Email Diani Putri Kusumaningrum; Ahmad Turmudi Zy; Suprapto
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.7531

Abstract

In modern life, internet access has become essential for communication. Email is one of many communication tools. Cyberattacks such as ransomware, phishing, and cryptojacking continue to evolve and are difficult to detect by security systems as technology rapidly advances. Therefore, this study uses email spam as the subject of research. The aim of this study is to implement and calculate the accuracy of the K-Nearest Neighbors (KNN) algorithm in classifying spam emails with ham and spam labels. An accuracy of 85%, precision of 87%, recall of 93%, and F1-score of 90% were obtained from tests conducted with an 80% training data and 20% testing data ratio. The results show that the K-Nearest Neighbors algorithm can effectively classify spam emails.
Implementasi Retrieval Augmented Generation (RAG) Dalam Perancangan Chatbot Kesehatan Pencernaan Gufranaka Samudra; Ahmad Turmudi Zy; Ermanto
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.7678

Abstract

The development of artificial intelligence technology, especially in the development of chatbots, has brought significant progress, especially in the health sector. However, the main challenge in using large language models (LLM) is the potential for bias and lack of accuracy in providing information, especially on critical topics such as digestive health. This study aims to implement Retrieval-Augmented Generation (RAG) in designing a digestive health chatbot to improve the accuracy and relevance of the information delivered. The RAG method integrates a generative model with a document-based retrieval system to provide more reliable and evidence-based answers. The research process involves collecting digestive health datasets through data scraping from Alodokter, as well as data processing through the preprocessing stage, embedding using the Indonesian language model (firqaaa/indo-sentence-bert-base), and data processing using a vector database with the HNSW index. The Llama 3.1:8b model is used to generate generative responses. The results of the study show that the application of RAG can reduce model bias and improve the quality of chatbot responses. Evaluation using metrics such as Mean Reciprocal Rank (MRR) 93%, Faithfullness 62%, Answer Relevancy 57%, and Semantic Similarity 81% showed good performance in providing accurate and relevant answers according to context. With this approach, chatbots are able to provide more accurate and contextual information according to user needs, and can reduce the risk of hallucinations in the information provided. This research contributes to the development of more reliable health chatbot technology, especially in the digestive health domain, and opens up opportunities for further application in other health fields
Implementasi Metode Plan-Do-Check-Action (PDCA) Untuk Mengurangi Defect Tetesan Karat Dan Meningkatkan Efisiensi Electrodeposition Coating Di PT XYZ Annaas Nurhuda Asidiq; Hendi Herlambang; Ahmad Turmudi Zy
Indonesian Journal of Multidisciplinary on Social and Technology Vol. 4 No. 2 (2026): Maret - Juni
Publisher : PT Ilmu Data Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/ijmst.v4i2.9044

Abstract

Tekanan kompetitif pada sektor otomotif Indonesia menuntut peningkatan mutu produk yang dijalankan beriringan dengan efisiensi operasional. Data Key Performance Indicator (KPI) PT XYZ periode Januari–Maret 2025 memperlihatkan dua permasalahan dominan pada proses Electrodeposition (ED) Coating, yaitu defect tetesan karat dengan Defect Per Unit (DPU) 4,2 dan konsumsi air industri 324 m³/hari, yang berdampak langsung pada biaya operasional dan mutu produk akhir. Penelitian ini diarahkan untuk mengeliminasi defect tetesan karat sekaligus meningkatkan efisiensi proses melalui penerapan metode Plan-Do-Check-Action (PDCA) berbasis Quality Control Circle (QCC) yang didukung QC Seven Tools. Tahap Plan dipakai untuk pemetaan masalah dan analisis akar penyebab melalui diagram Fishbone serta metode 5W+1H. Tahap Do menerjemahkan rencana ke dalam lima paket perbaikan teknis, yaitu cleaning-coating-covering chamber, instalasi lampu dan panel kontrol spray otomatis, re-setting tekanan pompa, modifikasi nozzle area inner, serta penggantian air industri dengan air demineralisasi. Tahap Check mengukur stabilitas proses pasca-perbaikan menggunakan control chart, dan tahap Action menutup siklus melalui standardisasi prosedur. Data primer diperoleh dari observasi lini PTC-ED, wawancara terstruktur, dan pengukuran parameter proses, sedangkan data sekunder bersumber dari dokumen produksi internal. Hasil implementasi menunjukkan defect tetesan karat berhasil dieliminasi penuh dari 4,2 DPU menjadi 0 DPU, dan konsumsi air Final Rinse ED berkurang dari 324 menjadi 100 m³/hari (efisiensi 69,1%). Penghematan biaya tahunan tercatat Rp3,33 miliar dengan Return on Investment (ROI) 1.253,66% dan payback period 27 hari produksi. Temuan ini menunjukkan siklus PDCA efektif diterapkan pada proses ED Coating sekaligus mendukung continuous improvement dan eco-friendly manufacturing di industri otomotif.  
Analysis of Customer Satisfaction Quality in the Painting & Welding Monitoring System with the Naïve Bayes Algorithm Miftahu Rizkiyah; Aswan Supriyadi Sunge; Ahmad Turmudi Zy
International Journal of Educational and Life Sciences Vol. 3 No. 1 (2025): January 2025
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijels.v3i1.169

Abstract

The painting and welding monitoring system represents an advancement intended to improve efficiency and quality in manufacturing procedures. This study evaluates customer satisfaction levels concerning the system by employing the Naive Bayes algorithm. Data was gathered through customer surveys, concentrating on essential factors such as reliability, ease of use, and the accuracy of the information delivered by the system. The Naive Bayes algorithm was applied to forecast customer satisfaction based on the collected survey data. The findings suggest that customer satisfaction levels can be determined with high precision, with reliability being the most significant factor. These results offer important insights for system developers to enhance the functionality of the painting and welding monitoring system.
PENERAPAN TEKNIK PENETRATION TESTING TERHADAP CROSS SITE SCRIPTING (XSS) DALAM PENGEMBANGAN WEBSITE Ahmad Alfian Chandra; Ahmad Turmudi Zy; Agung Nugroho
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 9 No 2 (2024): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v9i2.4822

Abstract

The increasing use of websites in various aspects of daily life has led to an urgent need to ensure the security of the information presented. One of the significant threats in website security is Cross-Site Scripting (XSS), where an attacker inserts malicious code into a web page to be executed by the user. This research aims to apply penetration testing techniques as a method to detect and resolve XSS vulnerabilities in website development. The research was conducted through three stages: installation of software to support penetration testing, execution of penetration testing using OWASP ZAP to identify vulnerabilities, and evaluation and implementation of solutions to address the vulnerabilities found. The results show that the implementation of the htmlspecialchars function in PHP is effective in preventing the execution of malicious scripts, thereby reducing the risk of XSS attacks. In addition, penetration testing techniques proved to be an effective method in identifying and mitigating security risks in web applications. Thus, this research emphasizes the importance of thorough security testing and implementation of appropriate preventive measures to maintain the integrity and user trust of web applications.
Prediksi Ketebalan Powder Coating Menggunakan Algoritma SVM Dan Naïve Bayes Zaenur Rozikin; Ahmad Turmudi Zy; Antika Zahrotul Kamalia
Bulletin of Information Technology (BIT) Vol 4 No 2: Juni 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i2.687

Abstract

Data Mining is a method that has been widely used to make scientific discoveries from a collection of datasets which so far have only been stored without further management. In the industrial world the use of data mining methods has helped with problems that are often found in the industrial field. Data mining helps in making predictions regarding thickness quality problems in a panel box product. Data mining is very useful for finding patterns in complex manufacturing data processing processes. Especially when we talk about consumers or service users of our product panels who want the panel to have good powder coating quality. This made the researchers conduct research to find the accuracy value which would later be used as a definite reference regarding the thickness of the powder coating. The results of this test the svm algorithm is better than naïve Bayes because the data in general can be categorized as a good result which has an accuracy of 97.60%, precision 99.56% and 96.03% recall. This res ult is an illustration for consumers to ensure that the panels to be purchased are of the best quality. By showing the data that has been processed, the consumer is sure that the purchase is really valid
Sistem Smart Door Lock Menggunakan Voice Recognition Berbasis Arduino Ray Fathur Rizky; Ahmad Turmudi Zy; Aswan S. Sunge
Bulletin of Information Technology (BIT) Vol 4 No 2: Juni 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i2.696

Abstract

Penelitian ini mencakup implementasi algoritma HMM pada smart door lock dengan menggunakan pengenalan suara berbasis Arduino. Tujuan penelitian ini adalah untuk meningkatkan keamanan pintu agar terhindar dari upaya pembobolan dan kejahatan. Saat ini, penguncian pintu rumah masih dilakukan secara manual. Dalam penelitian ini, algoritma yang digunakan adalah Hidden Markov Model. Pembuatan alat ini dilakukan dengan menggunakan bahasa pemrograman C++. Hasil penelitian ini dapat diimplementasikan dalam bentuk alat/robotik, di mana sistem dapat membuka dan menutup pintu rumah sesuai dengan rancangan yang telah direncanakan, yaitu melalui perintah suara.
Prediksi Jumlah Kasus Klaim Indemnity Dengan Menggunakan Algoritma Regresi Linear Pada Asuransi Mandiri Inhealth Qori yumansyah Qori; Ahmad Turmudi Zy; Muhamad Fatchan
Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i3.733

Abstract

Insurance is a type of financial institution that aims to provide guarantees to customers against risks that may occur in the future. In this study, by utilizing some data on indemnity claim cases on inhealth insurance through a prediction method approach and can be applied in analyzing data to make predictions of future insurance data based on the level of need. The prediction process of a simple Linear Regression algorithm can be implemented where the results also provide new insights for the prediction needs of claim data. Tests using rapidminer produce performance that is relevant to the scenario being modeled. The simple Linear Regression equation model after comparing the results of calculations manually and also with the Rapid Miner application generally shows the same data. The RMSE value is also obtained when evaluating the performance of the applied model, with an RMSE value of 0.273 with a standard deviation of +- 0.0.
Explainable DDoS Detection with a CNN-LSTM Hybrid Model and SHAP Interpretation Amali Amali; Anggi Muhammad Rifa'i; Edy Widodo; Ahmad Turmudi Zy; Dhani Ariatmanto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 6 (2025): December 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i6.6865

Abstract

The rising frequency and complexity of Distributed Denial of Service (DDoS) attacks pose a severe threat to network security. This study aims to develop an effective and interpretable DDoS detection framework using a hybrid deep learning approach. The proposed method integrates Convolutional Neural Networks (CNN) to capture local traffic patterns and Long Short-Term Memory (LSTM) networks to model temporal dependencies. The CICIDS 2017 dataset, after preprocessing steps including data cleaning, standardization, and class balancing with SMOTE, was used to train and evaluate the model. Experimental results show that the framework achieved 99.98% accuracy and a 99.83% F1-Score, with minimal false positive and false negative rates. This study integrates SHAP to improve model interpretability, aligning feature importance with network security expertise. Future research will focus on real-time deployment, cross-dataset validation, and exploring alternative explainable AI techniques for improved scalability.
Co-Authors Abdul Ghofir Agung Nugroho Ahmad Alfian Chandra Ahmad Rivaldi Amali Amali Anggi Muhammad Rifa'i 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 Dhani Ariatmanto 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 Isarianto Isarianto Juan Fakhri Lutfi Adji Ardiansyah M.Makmun Effendi Maha Putra Miftahu Rizkiyah Miftahuljannah Mudakir Muhamad David Ali Muhamad Fatchan Muhammad Adipa Muhammad Fatchan Muhammad Makmun Effendi Muhtajuddin Danny Nadya Khairunnisa Nugroho, Agung Purnama Sakhrial Pradini 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