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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Prosiding SNATIF JURNAL PASTI (PENELITIAN DAN APLIKASI SISTEM DAN TEKNIK INDUSTRI) Jurnal Edukasi dan Penelitian Informatika (JEPIN) Annual Research Seminar JOIN (Jurnal Online Informatika) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab BAREKENG: Jurnal Ilmu Matematika dan Terapan JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) INTECOMS: Journal of Information Technology and Computer Science Jiko (Jurnal Informatika dan komputer) KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Jurnal Kreativitas PKM JUMANJI (Jurnal Masyarakat Informatika Unjani) MIND (Multimedia Artificial Intelligent Networking Database) Journal Jurnal Manajemen Informatika Jurnal ICT : Information Communication & Technology Building of Informatics, Technology and Science JUTIS : Jurnal Teknik Informatika Jurnal Mnemonic JATI (Jurnal Mahasiswa Teknik Informatika) JOINT (Journal of Information Technology jurnal syntax admiration Tematik : Jurnal Teknologi Informasi Komunikasi Innovation in Research of Informatics (INNOVATICS) Informatics and Digital Expert (INDEX) International Journal of Global Operations Research Jurnal Sosial dan Teknologi Jurnal Ilmiah Wahana Pendidikan Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) International Journal of Quantitative Research and Modeling Jurnal Abdimas Kartika Wijayakusuma International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Journal of Informatics and Communication Technology (JICT) Jurnal Informatika Teknologi dan Sains (Jinteks) Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Jurnal Algoritma IJESPG (International Journal of Engineering, Economic, Social Politic and Government) journal Ranah Research : Journal of Multidisciplinary Research and Development Enrichment: Journal of Multidisciplinary Research and Development Journal of Informatics and Communication Technology (JICT) Malahayati International Journal of Nursing and Health Science Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika
Hadiana, Asep Id
Universitas Jenderal Achmad Yani
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Journal : Jurnal Algoritma

 1 
Eksploitasi Broken Access Control Untuk Eskalasi Hak Akses Pada LMS Universitas XYZ Muhammad, Azri; Hadiana, Asep Id; Ilyas, Ridwan
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2287

Abstract

This study aims to identify and exploit security vulnerabilities in the Learning Management System (LMS) of a university, with a primary focus on Broken Access Control (BAC) flaws resulting from misconfigurations in user access settings. With the rising threat of data breaches, this research also analyzes the extent to which security principles are applied to protect sensitive LMS user data—an increasingly critical issue in the digital era.The research approach began with the signing of a Non-Disclosure Agreement (NDA) to ensure the confidentiality of information, followed by an analysis of existing vulnerability assessment reports. Penetration testing was then conducted to identify potential unauthorized privilege escalation and further exploitation of vulnerabilities within the system. The analysis revealed a BAC vulnerability that allowed attackers to modify user roles without authorization. Additionally, it identified the use of the outdated MD5 hashing algorithm and the insecure storage of sensitive data on the client side without proper encryption. The exploitation of these vulnerabilities demonstrated that an attacker could gain administrator access simply by manipulating user roles, thereby enabling access to over 117,000 user records, including personal information and health history.This research contributes in three main aspects: first, an in-depth identification of critical vulnerabilities within the LMS, particularly concerning weak access control and inadequate data protection; second, a demonstration of how BAC exploitation can lead to the leakage of sensitive data in higher education environments; and third, the provision of mitigation recommendations based on current security best practices, such as the implementation of Role-Based Access Control (RBAC), the principle of least privilege, stricter role validation, Zero Trust Architecture, and the integration of artificial intelligence (AI) to detect threats early and provide automated responses to potential attacks.It is expected that this research can serve as a guideline for educational institutions in strengthening LMS security systems and more effectively protecting user data.
Prediksi Curah Hujan Menggunakan Metode Bi-LSTM dan GRU Berbasis Data Iklim Abdillah, Fajrul; Hadiana, Asep Id; Melina, Melina
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2305

Abstract

As a tropical country, Indonesia faces great challenges in predicting rainfall due to increasingly dynamic climate change. This study aims to predict rainfall in an urban area in West Java with tropical climate characteristics using deep learning methods, namely Bidirectional Long Short-Term Memory (Bi-LSTM) and Gated Recurrent Unit (GRU) based on climate data collected from local meteorological stations. The results show that the Bi-LSTM method provides more stable prediction performance with a Mean Absolute Error (MAE) value of 0.0108 and a Root Mean Squared Error (RMSE) of 0.0158. In contrast, the GRU method produced variable performance with higher MAE and RMSE values in some test scenarios. The main findings of this study indicate that the BiLSTM model has a higher level of accuracy, making it an effective information technology solution to support disaster mitigation and agricultural sector planning in climatically complex regions.
Pemanfaatan Open-Source Intelligence untuk Deteksi dan Penanganan Cybercrime Judi Online Berbasis Forensik Digital Ramdani, Maullidan Alfa Rizki Fikri; Hadiana, Asep Id; Ilyas, Ridwan
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2314

Abstract

The phenomenon of cybercrime related to online gambling is increasing in Indonesia, with web defacement attacks and backdoor insertion on websites that damage the psychological aspects of players and the family economy. This research aims to identify and analyze the threats posed by online gambling through Open-Source Intelligence (OSINT) and penetration testing methods. Using the Google Dorking technique, OSINT successfully identified sites involved in online gambling, while penetration testing uncovered system weaknesses that perpetrators exploit, such as SQL Injection and Cross-Site Scripting (XSS), which allow backdoor insertion. The results of this study demonstrate the effectiveness of OSINT and penetration testing in identifying sites that are vulnerable to attacks as well as loopholes that are often exploited by perpetrators. In addition, this research highlights the importance of digital forensics in handling legitimate electronic evidence for the court. As a scientific contribution, this research proposes the development of more accurate backdoor detection tools, the improvement of web security systems, as well as the implementation of rapid response in dealing with online gambling threats. This research is expected to assist the government and society in addressing cybercrime threats in Indonesia and strengthen policies and strategies to protect digital infrastructure.
Klasifikasi Penyakit Monkeypox dengan XGBoost dan SMOTE untuk Penanganan Data Tidak Seimbang Illawati, Adinda Rahma; Hadiana, Asep Id; Melina, Melina
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2349

Abstract

Monkeypox merupakan penyakit menular yang penyebarannya cepat dan memerlukan sistem deteksi dini yang akurat. Penelitian ini bertujuan mengembangkan model klasifikasi penyakit monkeypox dengan mengatasi permasalahan ketidakseimbangan data. Metode yang digunakan adalah Extreme Gradient Boosting (XGBoost) yang dikombinasikan dengan teknik Synthetic Minority Over-sampling Technique (SMOTE). Evaluasi model menggunakan Confusion Matrix dengan hasil akurasi 69%, presisi sebesar 0.69, recall sebesar 0.93, dan F1-score sebesar 0.79. Selain itu, nilai Area Under Curve - Receiver Operating Characteristic (AUC-ROC) mencapai 0.68. Penelitian ini menunjukkan bahwa kombinasi SMOTE dan XGBoost dapat mengatasi ketidakseimbangan data dan meningkatkan deteksi kelas minoritas, sehingga memberikan kontribusi dalam pengembangan sistem deteksi dini penyakit menular secara lebih akurat dan efisien.
Implementasi Algoritma Rivest Shamir Adleman (RSA) dan Zero-Knowledge Proofs (ZKP) untuk Meningkatkan Keamanan Data Rekam Medis Elektronik Lestari, Abdila; Id Hadiana, Asep; Melina
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2360

Abstract

Perkembangan teknologi komputer dan telekomunikasi meningkatkan efisiensi pengolahan data, namun menimbulkan tantangan keamanan, khususnya pada data rekam medis elektronik (RME) yang bersifat sensitif. Penelitian ini mengimplementasikan metode Zero-Knowledge Proof (ZKP) dan Revest Shamir Adleman (RSA) untuk meningkatkan keamanan dan privasi RME. ZKP memungkinkan pembuktian tanpa mengungkapkan informasi rahasia, sedangkan RSA menjaga kerahasiaan dan integritas data melalui enkripsi-dekripsi. Hasilnya, entropi data meningkat 24,53% (4,8314 menjadi 6,0165 bits/byte) setelah enkripsi RSA 2048-bit dengan padding OAEP berbasis SHA-256. Protokol ZKP metode Schnorr berhasil diimplementasikan tanpa membocorkan rahasia pengguna. Pengujian pada 100 pengguna simultan menunjukkan waktu respons rata-rata 1,8 detik dengan keberhasilan permintaan di atas 94%. Tantangan utama adalah beban komputasi autentikasi ZKP dan efisiensi saat jumlah pengguna bertambah. Integrasi RSA dan ZKP terbukti efektif meningkatkan keamanan, menjaga privasi, dan mempertahankan kinerja sistem RME.
Evaluasi Kualitas Klaster Wilayah Rawan Bencana Menggunakan K-Means dengan Silhouette dan Elbow Method Sudrajat, Risqi; Hadiana, Asep Id; Melina, Melina
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2379

Abstract

Natural disasters such as floods, earthquakes, and landslides are recurring threats in Cirebon City, West Java. This study aims to classify disaster-prone areas using the K-Means algorithm based on 1,144 incident data from Open Data Jabar. The data were grouped into three clusters, namely safe, moderate, and dangerous. Cluster quality was evaluated using the Silhouette Score and Elbow Method. The results of this study show that the model without normalization produced a score of 0.6804, reflecting good cluster separation. Conversely, the application of MinMaxScaler normalization significantly reduced the model's performance, with a score of 0.3900. The main contribution of this study is to show that data normalization can disrupt the natural pattern of risk distribution, thereby reducing the quality of clustering. Therefore, the selection of pre-processing techniques needs to be adjusted to the characteristics of local data. It is hoped that this study can be the basis for the development of a more adaptive and data-driven disaster mitigation decision support system.
Sistem Data Loss Prevention Untuk Deteksi dan Enkripsi pada Dokumen Menggunakan Regex dan Format Preserving Encryption Rahmawati, A Lusi Fitri; Hadiana, Asep Id; Melina
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2387

Abstract

In today’s digital era, the leakage of sensitive information has become a serious threat for both individuals and organizations, especially when data is not adequately protected. To address this issue, a system is required that not only detects the presence of sensitive data but also protects it effectively. This study develops a Data Loss Prevention (DLP) system that integrates sensitive data pattern detection using regular expressions (regex) with Format-Preserving Encryption (FPE) techniques to safeguard sensitive information in digital documents. The system is designed to identify data patterns such as national ID numbers (NIK), tax identification numbers (NPWP), phone numbers, email addresses, and bank account numbers using regex, and then encrypt the detected data without altering its original format. The test data used in this research consists of synthetic datasets that resemble real-world data. The encryption process employs the FF3 algorithm with a deterministic approach tailored to each data type to maintain system compatibility. The evaluation covers detection effectiveness using precision, recall, and F1-score metrics, as well as encryption efficiency and security through processing time measurements and entropy values. The evaluation results indicate a detection accuracy of 94.1%, precision of 100%, recall of 88.8%, and an F1-score of 94.1%. The average encryption time per document is only 0.15 milliseconds, while the encryption process successfully increases the document entropy by 0.0645 bits. This system demonstrates stable and reliable performance in detecting and protecting sensitive information without disrupting data structure or operational processes.
Model Prediksi Produksi Padi Berdasarkan Curah Hujan dan Suhu Menggunakan Regresi Linier Berganda Kharisma S, Moh Iqbal; Hadiana, Asep ID; Ramadhan, Edvin
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2793

Abstract

Padi merupakan komoditas pangan utama yang memiliki peran strategis dalam menjaga ketahanan pangan nasional. Produktivitas padi sangat rentan terhadap fluktuasi iklim, terutama curah hujan dan suhu udara yang kerap berubah akibat dinamika iklim global. Kondisi tersebut menimbulkan ketidakpastian hasil panen yang berdampak pada kesejahteraan petani, ketersediaan pangan, serta stabilitas sosial ekonomi. Oleh karena itu, diperlukan pendekatan berbasis data yang mampu memberikan estimasi produksi padi secara lebih akurat sebagai dasar perencanaan pertanian dan mitigasi risiko. Penelitian ini bertujuan untuk mengembangkan model prediksi produksi padi menggunakan regresi linier berganda dengan variabel curah hujan dan suhu udara sebagai prediktor utama. Data penelitian berupa data sekunder curah hujan, suhu, dan produksi padi diperoleh dari instansi resmi selama periode 2015–2024. Tahapan penelitian meliputi preprocessing data melalui normalisasi dan analisis korelasi, pembangunan model regresi linier berganda, serta evaluasi menggunakan koefisien determinasi (R²), Mean Absolute Error (MAE), dan Root Mean Square Error (RMSE) disertai uji asumsi klasik regresi. Hasil penelitian menunjukkan bahwa model regresi linier berganda mampu memprediksi produksi padi dengan tingkat kesalahan yang relatif rendah, sehingga dapat dijadikan alat bantu analitis untuk memperkirakan potensi hasil panen. Model prediktif ini diharapkan dapat dimanfaatkan oleh pemerintah daerah, penyuluh pertanian, dan petani dalam menyusun strategi tanam, pengelolaan irigasi, serta distribusi pangan secara lebih efektif dan efisien. Dengan demikian, penelitian ini berkontribusi dalam mendukung ketahanan pangan nasional melalui penerapan teknologi prediktif berbasis data.
Co-Authors Abdillah, Fajrul Abidillah, Gunawan Adelia Siti Rukoyah Adriansyah Pramana Agri Yodi Prayoga Agus Komarudin Agus Komarudin Agus Komarudin Alawiah, Siti Nurbayanti Alda Amorita Azza Ali, Moch. Dzikri Azhari Ananta Firdaus, Ahnaf Anggoro, Sigit Anggun Titah Islamiyyah Anshori, Siddiq Ahmad Anwar Fauzi, Mochammad Ardiansyah, Diki Arthur Oliviana Zabka Ashaury, Herdi Ashaury, Herdy Azhari, Moch Dzikri Azy Mushofy Anwary Badrujamaludin, Asep Chrisnanto, Yulison H. Dava Maulana, Muhammad Destiyanti, Fitri Dewi Marini Umi Atmaja Dewi Ratnasari DEWI RATNASARI Diah Tri Wahyuni Eddie Khrisna Putra Edvin Ramadhan Edvin Ramadhan Eka Purnama Rijaludin, Muhamad Engko M, Galih Yuga Pangestu Eriyadi, Maulidina Norick Fadilah, Vira Hasna Fahrezi, Rizal Febrian Faiza Renaldi Faiza Renaldi Fajar Firdaus, Fajar Fajri Rakhmat Umbara Febriansyah Istianto, Andrian Ferdiansyah Ferdian Ferina Nur Maulidya Firdaus, Syahrul Firman Alamsyah Galih Jatnika Galih Yuga Pangestu Engko M Gestavito, Rio Grace Christian M. Purba Gunawan Abdillah Gunawan Abdillah Gunawan Abdillah, Gunawan Gunawan Abidillah Hadi Apryana Hadimas Aprilian, Doni Haikal Muhammad, Husein Hanief Kuswanto, Muhammad Rafi Helsa Hawariyah Herdi Ashaury Herlina Napitupulu Hidayatulah Himawan Hovi Sohibul Wafa Hovi Hovi, Hovi Sohibul Wafa Humaira, Hana Nazla Idham Pratama Putra Illawati, Adinda Rahma Indah Putriani Fajar Sidik Insan Kamil Nurhikmat Ipan Sugiana Iqbal Dwi Nulhakim Iqbal Prayoga Willyana Irma Santikarama Irma Setiawati Ismafiaty, Ismafiaty Julianthy, Denissya Kafi, Moch. Nurul Kania Ningsih, Ade Kasyidi, Fatan Kharisma S, Moh Iqbal Komarudin, Agus Krishna Putra, Eddie Lestari, Abdila Lugina Masri M. Purba, Grace Christian Melina Melina Melina Monica, Taris Muhammad Akmal Ramadhan Muhammad Hasan Thoriq Almuwaffaq Thoriq Muhammad Sukma, Rifaz Muhammad, Azri Mulyasari, Cicik Rafka Mushofy Anwary, Azy Muthmainah, Sekar Ghaida Nabilla, Ulya Nizar Septi maulana Norizan Mohamed Nurrokhimah, Siti Nurul Sabrina, Puspita Oktaviani, Ayu Nur Oliviana Zabka, Arthur Prasetyo, Nur Faid Pryma Saputra Ginting Puspita Nurul Sabrina Puspita Nurul Sabrina Puspita Nurul Sabrina Puspita Putra, Eddie Krishna Putri Eka Prakasawati R Ramadhan Destyanto Rafli Firdaus Raflialdy Raksanagara Rahmawati, A Lusi Fitri Raihan Martin Permana Ramdani, Maullidan Alfa Rizki Fikri Rezki Yuniarti Rezky Yuniarti Ria Amelia Junandes Ridwan Ilyas Rifaldi Elpry Rizal Rizal Dwiwahyu Pribadi Rizky Bayu Oktavian Rizky Fauzi Achman Rukoyah, Adelia Siti Salsabila Fajriati Romli Salsabila Salsabila, Mira Salsabila, Salsabila Fajriati Romli Santikarama, Irma Sapari, Albi Mulyadi SETIAWAN, YOSEP Sevty Nourmantana Shisi Prayesti Singgih, Dimas Siti Rohaeni Siti Widiani Sopian, Annisa Mufidah Sudrajat, Risqi Sukono Sukono Susanti, Adisti Dwi Syamsi, Salsa Safira Nur Syechru Denny Irja Gotama Szalfa Saadiatus Sakinah Tacbir Hendro P Tacbir Hendro P Tacbir Hendro P Tacbir Hendro Pudjiantoro Tacbir Hendro Pudjiantoro Tacbir Hendro Pudjiantoro Tacbir Hendro Pudjiantoro Tacbir Pudjiantoro Hendro Tachbir Hendro Taufiq Akbar Herawan Thomas Adi Nugroho Tulus Harry Lamramot Tulus Tulus, Tulus Harry Lamramot Valentina Adimurti Kusumaningtyas Wahyuni Rodiyah Risfianti Widiyantoro, Widiyantoro Wina Witanti Wina Witanti Wina Witanti Wina Witanti Wina Witanti Wina Witanti Wina Witanti Winalia Winalia Winta Witanti Yasmina Azzahra Yudi Setiadi Permana Yulianto Dwi Saptohadi Yulison Herry Chrisnanto Yulita, Rita Fitri Yuswandi Yuswandi, Yuswandi