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All Journal Dinamik Techno.Com: Jurnal Teknologi Informasi JSI: Jurnal Sistem Informasi (E-Journal) Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) CESS (Journal of Computer Engineering, System and Science) Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Journal of Information System, Applied, Management, Accounting and Research Technologia: Jurnal Ilmiah International Journal of Informatics and Computation JATI (Jurnal Mahasiswa Teknik Informatika) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Jurnal Sistem Informasi dan Sains Teknologi Jurnal Teknologi Informatika dan Komputer Journal of Computer Networks, Architecture and High Performance Computing Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) ACADEMIA: Jurnal Inovasi Riset Akademik Journal Automation Computer Information System (JACIS) Bulletin of Information Technology (BIT) Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB Joong-Ki : Jurnal Pengabdian Masyarakat Joutica : Journal of Informatic Unisla Journal of Practical Computer Science (JPCS) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Malcom: Indonesian Journal of Machine Learning and Computer Science Riwayat: Educational Journal of History and Humanities VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Jurnal Pelita Pengabdian SAINTEK Joong-Ki JPMAS : Jurnal Pengabdian Masyarakat Dedikasi : Jurnal Pengabdian Lentera RECORD Journal of Loyality and Community Development Cahaya Pengabdian Jurnal ilmiah teknologi informasi Asia Joong-Ki Smatika Jurnal : STIKI Informatika Jurnal
Agung Nugroho
Universitas Pelita Bangsa
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry 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 Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Social Sciences Other

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Pengembangan Sistem Interaksi Robotik berbasis Speech Recognition untuk Layanan Publik di Kampus Alviyan, Eric; Nugroho, Agung; Fauzi, Ahmad
Dinamik Vol 30 No 2 (2025)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v30i2.10242

Abstract

ABSTRACT Information services on campus are often delayed due to reliance on staff, resulting in long queues and inefficient waiting times. This study aims to design and develop a robotic interaction system based on speech recognition and Natural Language Processing (NLP), equipped with a virtual button as an alternative activation method. The system allows users to interact with the robot using voice, while the virtual button provides an additional option for users who are more comfortable with touch-based interaction. The research method employed is prototype development, which includes the design, implementation, and evaluation of the system. Testing was conducted to assess the effectiveness of the system in delivering information services quickly and accurately. The results show that the developed system can enhance service efficiency, reduce dependence on staff, and facilitate faster and more practical interactions between users and the robot. This study is expected to contribute to the development of technology-based public service systems, especially in the campus environment. Keywords: robotic interaction, speech recognition, NLP, virtual button, public service
Penerapan Machine Learning untuk Prediksi Kenaikan Harga Beras Premium Menggunakan Algoritma Regresi Linier: Application of Machine Learning for Premium Rice Price Increase Prediction Using Linear Regression Algorithm Widiyatmoko, Arif Tri; Butsianto, Sufajar; Nugroho, Agung
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 5 No. 3 (2025): MALCOM July 2025
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v5i3.2123

Abstract

Ketidakstabilan harga beras premium sebagai komoditas pangan pokok memerlukan solusi prediksi yang akurat untuk membantu perencanaan ekonomi. Penelitian ini menerapkan algoritma Machine Learning, yaitu Regresi Linier, untuk memprediksi kenaikan harga beras premium. Model dilatih menggunakan data historis harga dan dievaluasi kinerjanya dengan metrik MAE (0.244), MSE (0.092), dan R-squared (0.893), menunjukkan tingkat akurasi yang cukup baik dalam memprediksi harga. Selanjutnya, model yang berhasil dikembangkan diimplementasikan ke dalam aplikasi web interaktif berbasis Streamlit. Aplikasi ini memungkinkan pengguna untuk memasukkan tanggal dan secara langsung mendapatkan prediksi harga beras premium. Hasil penelitian menunjukkan bahwa Regresi Linier efektif dalam memprediksi harga beras premium, dan implementasi ke dalam aplikasi Streamlit berhasil menyediakan alat prediksi yang mudah diakses. Meskipun demikian, penelitian lanjutan dapat berfokus pada peningkatan akurasi model dan eksplorasi algoritma Machine Learning lainnya untuk prediksi harga komoditas
Development of A We-Based Clinic Information Service System Application Using PHP And MySQL Ilyas, Abdi; Sasongko, Ananto Tri; Nugroho, Agung
Riwayat: Educational Journal of History and Humanities Vol 8, No 4 (2025): October
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jr.v8i4.50002

Abstract

This research, titled "DEVELOPMENT OF A WEB-BASED CLINIC INFORMATION SERVICE SYSTEM APPLICATION USING PHP AND MySQL" aims to optimize efficiency and service quality at Atlantic Clinic through the implementation of a web-based information system. Analysis and testing indicate that the current conventional service method is no longer adequate, leading to inefficiencies in service processes. The newly designed system enhances administrative efficiency by accelerating patient data recording and retrieval. Additionally, the queue system provides better time estimates for patients, while the medical record system ensures the security and accuracy of patient data. The integrated cashier system improves payment transaction efficiency, reducing billing errors. Master data management, which includes medication, medical procedures, doctors, and users, becomes more structured and accurate. The implementation of this system is expected to bring significant improvements to the quality of service at Atlantic Clinic, making it more modern, effective, and efficient.
COMPARATIVE ANALYSIS OF CLASSIFICATION ALGORITHMS IN HANDLING IMBALANCED DATA WITH SMOTE OVERSAMPLING APPROACH Nugroho, Agung; Wiyanto; Maulana, Donny
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 2 (2025): JITK Issue November 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i2.6956

Abstract

Most machine learning algorithms tend to yield optimal results when trained on datasets with balanced class proportions. However, their performance usually declines when applied to data with significant class imbalance. To address this issue, this study utilizes the Synthetic Minority Oversampling Technique (SMOTE) to improve class distribution before model training. Several classification algorithms were employed, including Decision Tree, K-Nearest Neighbors, Logistic Regression, Support Vector Machine, and Random Forest. Experimental results reveal that the Random Forest model produced the highest accuracy (95.70%) and the best F1-score, demonstrating a well-balanced trade-off between precision and recall. In contrast, the Logistic Regression algorithm achieved the highest recall (74.20%), indicating better sensitivity in identifying positive instances despite a lower F1-score. These outcomes highlight the importance of choosing appropriate classification methods based on the specific evaluation goals whether prioritizing accuracy, recall, or overall model balance.
Perancangan Sistem Informasi Monitoring Produksi pada PT. NOK Indonesia Metode Rapid Application Development (RAD) Tiaraningsih; Agung Nugroho; Karsito
REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer Vol. 9 No. 3 (2025): Volume 9 Nomor 3 Agustus 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/remik.v9i3.15196

Abstract

PT. NOK mengalami kendala karena proses pengelolaan data dan informasi masih dilakukan secara manual, sehingga sering terjadi keterlambatan, duplikasi data, dan kesalahan pencatatan. Kondisi ini menghambat efisiensi kerja serta mengurangi ketepatan informasi yang dibutuhkan oleh manajemen. Untuk mengatasi permasalahan tersebut, Penelitian ini menerapkan metode Rapid Application Development (RAD), yang memungkinkan proses pengembangan sistem berlangsung lebih cepat dengan melibatkan pengguna secara intensif pada setiap tahap pengembangannya. Proses perancangan meliputi analisis kebutuhan, pemodelan sistem menggunakan use case, activity diagram, dan sequence diagram, pembuatan antarmuka, serta pengujian sistem dilakukan dengan metode blackbox testing guna memverifikasi bahwa seluruh fungsi beroperasi sesuai dengan spesifikasi yang telah ditetapkan. Hasil dari penelitian menunjukkan bahwa penerapan metode RAD mampu menghasilkan sistem informasi yang efektif, user-friendly, dan sesuai dengan kebutuhan operasional PT. NOK, dengan waktu pengembangan yang relatif singkat dibandingkan metode tradisional.
Model SIGAP: Sistem Identifikasi Gejala Kantuk Pengemudi Menggunakan YOLO 11 Mu'ammar Kadafi; Furkhon Nurdiyanto; Daffa Albani Hakim; Agung Nugroho
Prosiding Sains dan Teknologi Vol. 5 No. 1 (2026): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 5 - Februari 2026
Publisher : DPPM Universitas Pelita Bangsa

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

Abstract

Kantuk pengemudi merupakan salah satu faktor utama penyebab kecelakaan lalu lintas yang sering tidak terdeteksi secara dini, khususnya pada kendaraan operasional dan komersial. Kondisi ini menyebabkan penurunan kewaspadaan, waktu reaksi, serta kemampuan pengambilan keputusan pengemudi, sehingga meningkatkan risiko kecelakaan dengan tingkat keparahan tinggi. Penelitian ini mengembangkan SIGAP (Sistem Identifikasi Gejala Kantuk Pengemudi) sebagai sistem berbasis visi komputer yang bertujuan mengidentifikasi gejala kantuk pengemudi menggunakan algoritma deteksi objek YOLOv11. Sistem SIGAP dirancang untuk memberikan peringatan berbasis durasi, yaitu alarm ringan ketika kondisi kantuk terdeteksi selama 1,5 detik dan alarm berulang apabila durasi deteksi melebihi 3 detik. Dataset yang digunakan terdiri dari tiga kelas, yaitu Normal, Mengantuk, dan Microsleep, dengan total 2.052 citra hasil augmentasi. Untuk meningkatkan keandalan evaluasi model, dataset dibagi ulang dengan proporsi 70% data latih (1.436 citra), 20% data validasi (410 citra), dan 10% data uji (206 citra). Proses pelatihan dilakukan menggunakan arsitektur YOLOv11n dengan ukuran input 640×640 piksel. Hasil pengujian pada data validasi menunjukkan performa deteksi yang baik dengan nilai precision sebesar 0,958, recall 0,934, mAP@50 sebesar 0,972, dan mAP@50–95 sebesar 0,708, yang menunjukkan kemampuan model dalam mengidentifikasi gejala kantuk pengemudi secara akurat dan konsisten. Berdasarkan hasil tersebut, sistem SIGAP berpotensi digunakan sebagai sistem pendukung keselamatan berkendara untuk membantu mendeteksi gejala awal kantuk pengemudi secara real-time. Pengembangan lanjutan disarankan untuk pengujian lapangan yang lebih luas serta integrasi dengan perangkat peringatan dan sistem kendaraan guna meningkatkan efektivitas pencegahan kecelakaan lalu lintas.
COMPARATIVE ANALYSIS OF CLASSIFICATION ALGORITHMS IN HANDLING IMBALANCED DATA WITH SMOTE OVERSAMPLING APPROACH Agung Nugroho; Wiyanto; Donny Maulana
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 2 (2025): JITK Issue November 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i2.6956

Abstract

Most machine learning algorithms tend to yield optimal results when trained on datasets with balanced class proportions. However, their performance usually declines when applied to data with significant class imbalance. To address this issue, this study utilizes the Synthetic Minority Oversampling Technique (SMOTE) to improve class distribution before model training. Several classification algorithms were employed, including Decision Tree, K-Nearest Neighbors, Logistic Regression, Support Vector Machine, and Random Forest. Experimental results reveal that the Random Forest model produced the highest accuracy (95.70%) and the best F1-score, demonstrating a well-balanced trade-off between precision and recall. In contrast, the Logistic Regression algorithm achieved the highest recall (74.20%), indicating better sensitivity in identifying positive instances despite a lower F1-score. These outcomes highlight the importance of choosing appropriate classification methods based on the specific evaluation goals whether prioritizing accuracy, recall, or overall model balance.
IMPLEMENTASI METODE FIFO DALAM PENGELOLAAN BAHAN BAKU UNTUK MEMINIMALISIR MATERIAL REJECT DI UMKM GRILLSA Nur Aisyah Shinta Balqis; Susan Kustiawan; Agung Nugroho
ACADEMIA: Jurnal Inovasi Riset Akademik Vol. 6 No. 3 (2026)
Publisher : Pusat Pengembangan Pendidikan dan Penelitian Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51878/academia.v6i3.12811

Abstract

ABSTRACT Grillsa MSME is a culinary business facing problems in its raw material storage system due to the suboptimal implementation of the First In First Out (FIFO) method, which potentially increases the risk of material reject caused by the deterioration of raw material quality during storage. This study aims to identify the condition of the raw material storage system, analyze the factors causing material reject, and implement the FIFO method as an effort to minimize material reject at Grillsa MSME. The research employed a descriptive quantitative method with a Plan-Do-Check-Action (PDCA) approach. Data were collected through observation, interviews, and documentation, while Pareto Diagram and Fishbone Diagram analyses were used to identify the dominant types and root causes of rejects. The Pareto analysis revealed that the highest reject rate was caused by meat discoloration, accounting for 71% of total rejects. Fishbone analysis indicated that the main causes were the lack of optimal FIFO implementation, the absence of shelf-life identification, and disorganized storage conditions. Improvement actions were carried out through raw material grouping based on type, storage layout rearrangement, color labeling for shelf-life identification, and the development of standard operating procedures (SOPs) for raw material storage. The implementation of FIFO resulted in a more organized storage system, easier identification and retrieval of materials according to their arrival sequence, and a reduced risk of material reject. Therefore, the FIFO method proved effective in improving raw material inventory management and maintaining raw material quality during storage. ABSTRAK UMKM Grillsa merupakan usaha kuliner yang menghadapi permasalahan pada sistem penyimpanan bahan baku yang belum menerapkan metode First In First Out (FIFO) secara optimal sehingga berpotensi meningkatkan risiko material reject akibat penurunan kualitas bahan baku selama penyimpanan. Penelitian ini bertujuan untuk mengidentifikasi kondisi sistem penyimpanan bahan baku, menganalisis faktor-faktor penyebab material reject, serta menerapkan metode FIFO sebagai upaya meminimalisir material reject di UMKM Grillsa. Penelitian menggunakan metode kuantitatif deskriptif dengan pendekatan Plan-Do-Check-Action (PDCA). Pengumpulan data dilakukan melalui observasi, wawancara, dan dokumentasi, sedangkan analisis data menggunakan Diagram Pareto dan Diagram Fishbone untuk mengidentifikasi jenis serta akar penyebab reject yang dominan. Hasil analisis Pareto menunjukkan bahwa reject tertinggi terjadi pada daging yang mengalami perubahan warna dengan persentase sebesar 71%. Analisis Fishbone menunjukkan bahwa penyebab utama material reject meliputi belum diterapkannya FIFO secara optimal, tidak adanya identifikasi masa simpan bahan baku, serta kondisi penyimpanan yang belum teratur. Tindakan perbaikan dilakukan melalui pengelompokan bahan baku berdasarkan jenis, penataan ulang layout penyimpanan, penggunaan label warna sebagai identifikasi masa simpan, dan penyusunan standar operasional prosedur (SOP) penyimpanan bahan baku. Hasil penerapan FIFO menunjukkan peningkatan keteraturan sistem penyimpanan, kemudahan dalam identifikasi dan pengambilan bahan baku sesuai urutan kedatangan, serta berkurangnya risiko material reject. Dengan demikian, metode FIFO terbukti efektif dalam mendukung pengelolaan persediaan bahan baku dan menjaga kualitas bahan baku selama proses penyimpanan.  
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.
Analisis Sentimen Opini Publik Platform X Terhadap Bencana Banjir Bandang Di Sumatra Menggunakan Algoritma SVM Hilman Ihza Amrullah; Agung Nugroho; Asep Suprianto
Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Vol 17, No 1 (2026): Juni
Publisher : Universitas Bandar Lampung (UBL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36448/jsit.v17i1.4832

Abstract

Bencana banjir bandang yang terjadi di Pulau Sumatra memberikan dampak yang besar dan menjadi sorotan masyarakat. Kejadian ini telah munculnya berbagai opini dan respons publik yang dibagikan melalui platform media sosial, khususnya Platform X. Namun, banyaknya opini yang berbentuk teks dan tidak terstruktur membuat analisis secara manual menjadi sulit. Oleh karena itu, penelitian ini bertujuan untuk menganalisis sentimen publik di Platform X terkait bencana banjir bandang di Pulau Sumatra dengan menggunakan metode analisis sentimen berbasis machine learning. Data yang digunakan dalam penelitian diambil dari unggahan masyarakat di Platform X melalui proses crawling data. Setelah itu, data akan melalui tahap preprocessing, pelabelan sentimen dengan pendekatan berbasis lexicon, serta pembobotan fitur dengan metode Term Frequency–Inverse Document Frequency (TF-IDF). Klasifikasi sentimen dilakukan dengan menggunakan algoritma Support Vector Machine (SVM), sementara evaluasi model direncanakan dilakukan dengan confusion matrix. Penelitian ini diharapkan dapat memberikan pemahaman mengenai kecenderungan opini publik terhadap bencana banjir hebat di Pulau Sumatra melalui analisis data media sosial.
Co-Authors Abdul Halim Anshor Adi Kusuma Adi Kusuma Afrizal Ardiansyah Agus Suwarno Agus Suwarno, Agus Ahmad Alfian Chandra Ahmad Rivaldi Ahmad Santoso Ahmad Turmudi Zy Ahmad Turmudi Zy Ahmad Turmudi Zy Al Abdilah, M. Akmal Alfatan Dzulatkha Alviyan, Eric Amali Amali Ananto Tri Sasongko Andri Firmansyah Angga Kurniadi Hermawan Ansor, Abdul Halim Antika Zahrotul Kamalia Ari Maulana Arief Susilo Arif Siswandi Arif Susilo Arif Tri Widiyatmoko Asep Suprianto Aswan S Sunge Aswan Supriyadi Sunge Ayu Indriyanti Bima Randy Gumilang Butsianto, Sufajar Caswita Caswita Chaerul Hidayat Daffa Albani Hakim Donny Maulana Edora Elkin Rilvani Endrik Fauzi Ahmad Muda Fitri, Retno Furkhon Nurdiyanto Hilman Ihza Amrullah Ike Yunia Pasa Ikhsan Romli Ilyas, Abdi Irfan Afriantoro Isarianto Isarianto Jamaludin Jamaludin Karsito Londong, Riko Reky Maulana, Donny Miftah Wangsadanureja Mu'ammar Kadafi Muhammad Abdul Rahman Wahid Muhammad Iqbal Muhammad Reza Maulana Muhammad Rizki Sani Muhtajuddin Danny Nisa, Khilyatun Nur Aisyah Shinta Balqis Nur Hidayati Nur Hidayati Nurjeli Nurjeli Priatna , Wowon Purnama Sakhrial Pradini Rusdi, Adi Salman Alfaridzi Sasongko, Ananto Tri Septiawan Dwi Pramukti Sunita Dasman Supriadi, Asmadi Susan Kustiawan Sutrisno Aji Prasetyo Tiaraningsih Wahyono Wahyono Wahyu Hadikristanto Wiyanto Wiyanto Wiyanto Wiyanto - Wiyanto Wiyanto Wiyanto, Wiyanto Yoga Religia