Article Per Year (5 Year)
p-Index From 2021 - 2026
3.244
P-Index
This Author published in this journals
All Journal JSI: Jurnal Sistem Informasi (E-Journal) PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Jurnal Ilmiah Media Sisfo Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JURTEKSI JPM: JURNAL PENGABDIAN MASYARAKAT Jurnal Informatika dan Rekayasa Komputer Jurnal Manajemen Teknologi dan Sistem Informasi Jurnal Pengabdian Masyarakat Unama
Kurniabudi
Unknown Affiliation
Aerospace Engineering Humanities Astronomy Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Medicine & Pharmacology Public Health Social Sciences Transportation Other

Published : 21 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 21 Documents
Search

 1   2   3 
WORKSHOP NETIKET DAN KEAMANAN DIGITAL BAGI SISWA/I SMA NEGERI 8 KOTA JAMBI Riyadi, Willy; Fachruddin; Kurniabudi
Jurnal Pengabdian Masyarakat UNAMA Vol 4 No 1 (2025): JPMU Volume 4 Nomor 1 April 2025
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jpmu.2025.4.1.2015

Abstract

Internet telah menyatu erat dengan gaya hidup modern, khususnya bagi kaum muda, Sebagai media yang kaya akan informasi, hiburan, dan sarana komunikasi, internet telah merubah cara kita belajar, bekerja, dan berinteraksi. Di Indonesia berdasarkan Asosiasi Penyelenggara Jasa Internet Indonesia (APJII), penetrasi internet terus meningkat secara signifikan, Fakta ini memperlihatkan adanya ketergantungan yang semakin meningkat pada teknologi digital di tengah masyarakat. Dalam era digital yang semakin kompleks, keamanan digital dan netiket (net etiquette) menjadi isu yang sangat relevan. Hal ini juga sejalan dengan beberapa regulasi yang berlaku di Indonesia, di antaranya Undang-Undang Nomor 11 Tahun 2008 tentang Informasi dan Transaksi Elektronik (UU ITE) serta Undang-Undang Nomor 27 Tahun 2022 tentang Perlindungan Data Pribadi (UU PDP). SMA Negeri 8 Kota Jambi bertempat di Jl. Marsda Surya Dharma Km. 8, Kenali Asam Bawah, Kec. Kota Baru, Kota Jambi, menghadapi tantangan dalam hal kurangnya sosialisasi netiket (net etiquette) berupa aturan sopan santun, etika dan tata krama dalam penggunaan media sosial serta teknik melindungi serta menghindari penyalahgunaan data pribadi saat terhubung ke dunia maya. Workshop ini menjadi upaya konkret dalam mewujudkan siswa menjadi warga digital yang bertanggung jawab dan mampu memanfaatkan teknologi secara bijak.
EDUKASI PENGAMANAN DATA PRIBADI BAGI KALANGAN SANTRI DI PONPES NURUL IMAN MUARO SEBAPO Purnama, Benni; Kurniabudi; Sharipuddin; Husaein, Ahmad
Jurnal Pengabdian Masyarakat UNAMA Vol 4 No 1 (2025): JPMU Volume 4 Nomor 1 April 2025
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jpmu.2025.4.1.2182

Abstract

Revolusi industri 4.0 merupakan era disrupsi dimana terjadi transformasi cara kerja konvensional menjadi modern dengan pemanfaatan teknologi informasi. Salah satu teknologi informasi yang banyak digunakan adalah media sosial. Media sosial yang populer dikalangan para kalangan masyarakat adalah facebook. Facebook menawarkan sejumlah fasilitas, selain untuk jejaring pertemanan, sarana komunikasi, hiburan, dan berbagi informasi, facebook dapat digunakan untuk bisnis. Namun disisi lain ada isu keamanan, facebook dan media sosial lainnya, dapat menjadi platform kejahatan berinternet dengan memanfaatkan data pribadi yang ada pada pemilik perangkat atau media sosial. Penyalahgunaan data pribadi terjadi karena kurangnya pemahaman tentang data pribadi dan pengamanan data pribadi. Tujuan kegiatan pengabdian masyarakat yang dilakukan untuk memberikan wawasan tentang pentingnya pengamanan data pribadi kepada para santri di Ponpes Nurul Iman Muaro Sebapo. Metode yang disampaikan dalam sosialiasi ini melalui pemaparan materi, diskusi dan tanya jawab serta evaluasi dilakukan dengan cara pre test dan post test. Dari hasil post test yang diperoleh didapat bahwa pemahaman para santri mampu mengetahui apa itu data pribadi, bagaimana mengecek kebocoran data pribadi dan bagaimana cara mengatasinya dengan baik.
Analisis Kepuasan Pengguna PMM Menggunakan Metode UTAUT Berdasarkan Perspektif Guru SMK Negeri Kota Jambi Tarigan, Wina Agustina; Sharipudin; Kurniabudi
Jurnal Informatika Dan Rekayasa Komputer(JAKAKOM) Vol 5 No 2 (2025): JAKAKOM Vol 5 No 2 SEPTEMBER 2025
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jakakom.2025.5.2.2286

Abstract

The utilization of technology and competency development in the current era serve as a foundation for the development of the Merdeka Curriculum. Schools and teachers need to prepare themselves thoroughly, starting from understanding the structure of independent study programs, assessment, learning outcomes, and learning objectives, to the implementation of projects and other aspects. This can be achieved through participation in teacher or school mobilization activities.The government supports the implementation of the Merdeka Curriculum in Vocational High Schools (Sekolah Menengah Kejuruan - SMK) by providing teaching materials such as textbooks and supplementary resources, training, and learning sources for educators through the Platform Merdeka Mengajar (PMM) application, which can be accessed via laptops or mobile phones.The implementation of the Merdeka Curriculum, promoted by the Indonesian government, encourages innovation in the learning process, particularly through the use of information and communication technology. The Platform Merdeka Mengajar serves as a solution to support a more flexible and student-centered educational transformation.State Vocational High Schools (SMK Negeri) in Kota Jambi, as vocational education institutions, have adopted this platform in an effort to improve the quality of learning. This study aims to analyze the level of user satisfaction with the Platform Merdeka Mengajar application in SMK Negeri in Kota Jambi using the UTAUT model. Specifically, this research will identify the factors influencing teachers' intention to use the application and measure their satisfaction with the available features.Based on the analysis conducted, it can be concluded that out of the five hypotheses developed, the accepted hypotheses are Performance Expectancy (H1), Effort Expectancy (H2), and Behavioral Intention (H5). Meanwhile, the rejected hypotheses are Social Influence (H3) and Facilitating Conditions (H4).
Perbandingan Algoritma C4.5 Dan Naive Bayes Untuk Peminatan Penjurusan Pada SMK Negeri 6 Batanghari amrullah, Wahyu; Kurniabudi; Joni Devitra
Jurnal Informatika Dan Rekayasa Komputer(JAKAKOM) Vol 5 No 2 (2025): JAKAKOM Vol 5 No 2 SEPTEMBER 2025
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jakakom.2025.5.2.2287

Abstract

This study aims to analyze the comparison of the C4.5 and Naive Bayes algorithms in the selection of majors at SMK Negeri 6 Batanghari. The comparison between the C4.5 and Naive Bayes algorithms is carried out because of the effectiveness and accuracy in decision making. The C4.5 method as a decision tree algorithm provides a clear and easy-to-understand interpretation of the decisions taken, while Naive Bayes with its probabilistic approach is often faster and more efficient in handling large datasets. From the results of the analysis carried out, this study revealed that the two algorithms have different characteristics and performance in classifying student interest data. The C4.5 algorithm based on decision trees tends to be easier to interpret because it produces clear decision rules, while Naive Bayes based on probability has advantages in handling data uncertainty
Analisis Perbandingan Algoritma K-Means Dan K-Medoids Dalam Mengukur Tingkat Kepuasan Mahasiswa Terhadap Pelayanan Akademik Saputra, Sahril; Kurniabudi; Jasmir
Jurnal Informatika Dan Rekayasa Komputer(JAKAKOM) Vol 5 No 2 (2025): JAKAKOM Vol 5 No 2 SEPTEMBER 2025
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jakakom.2025.5.2.2292

Abstract

This study aims to analyze the comparison of K-Means and K-Medoids algorithms in measuring the level of student satisfaction with academic services at the Islamic Institute of Mamba'ul Ulum Jambi. Student satisfaction data were collected through questionnaires and analyzed using both algorithms with the help of RapidMiner tools. Clustering results were evaluated using the Davies Bouldin Index (DBI) to determine the most optimal algorithm. The results showed that most students at the Islamic Institute of Mamba'ul Ulum Jambi were very satisfied with the academic services provided. Clustering with K-Means and K-Medoids successfully grouped students into three clusters: "Very Satisfied", "Satisfied", and "Unsatisfied". The K-Means algorithm produced clusters with 450 members ("Very Satisfied"), 351 members ("Satisfied"), and 218 members ("Unsatisfied"). Meanwhile, K-Medoids produced clusters with 638 members ("Very Satisfied"), 270 members ("Satisfied"), and 111 members ("Unsatisfied"). Based on the DBI value, the K-Medoids algorithm (0.222) showed better performance than K-Means (0.396) in clustering student satisfaction data. This study has important implications for the Islamic Institute of Mamba'ul Ulum Jambi in evaluating and improving academic services
COMPARISON OF K-MEANS AND K-MEDOIDS FOR DRUG DATA CLUSTERING Andika, Tripa; Kurniabudi; Sharipuddin
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 4 (2025): September 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i4.4140

Abstract

Abstract: Ineffective drug demand management can lead to problems such as imbalanced drug distribution, excess stock, or shortages in community health centers. To address this, data mining can be utilized to support the planning and control process of drug inventory. Clustering techniques were chosen because they are able to group drug data based on certain characteristics, thus identifying stable and unstable drug supply patterns. This study aims to group drug data at Simpang Kawat Community Health Center in Jambi City, which can be used as a reference in planning drug needs in the next period. Data grouping is divided into three categories: slow-moving, medium-moving, and fast-moving. The research data includes attributes of drug name, initial stock, receipt, inventory, usage, and final stock, with a total of 1758 data sets, which were processed using the CRISP-DM framework through the RapidMiner application. Cluster quality evaluation was carried out using the Davies-Bouldin Index (DBI). The results showed that the K-Means algorithm obtained a DBI value of 0.175, smaller than K-Medoids which obtained a value of 0.354. Because a smaller DBI value indicates better cluster quality, K-Means provides more optimal clustering results than K-Medoids. Through these clustering results, community health centers can utilize drug cluster information to support more efficient drug procurement planning, as well as reduce the risk of excess or shortage of stock. Keywords: data mining; clustering; k-means; k-medoids; davies-bouldin index
Analisis Kinerja Algoritma K-Nearest Neighbor Dan Random Forest Untuk Deteksi Serangan Pada Jaringan Perangkat IoT Mansis, Muhammad Ilham; Siregar, Mulia Rohmayati; Putri, Ferika Syavina; Kurniabudi
Jurnal PROCESSOR Vol 20 No 2 (2025): Jurnal Processor
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/processor.2025.20.2.2549

Abstract

Deteksi serangan pada jaringan perangkat Internet of Things (IoT) menjadi tantangan penting dalam menjaga keamanan sistem yang semakin kompleks dan rentan terhadap ancaman siber. Sebagai upaya dalam mengatasi permasalahan tersebut, penelitian ini bertujuan untuk mengevaluasi kinerja algoritma K-Nearest Neighbor (KNN) dan Random Forest dalam mendeteksi berbagai jenis serangan pada jaringan perangkat IoT. Dataset yang digunakan adalah Aposemat IoT-23, yang berisi 1.446.599 entri data lalu lintas jaringan dari berbagai jenis serangan seperti Benign, DDoS, Attack, dan lainnya. Tahapan metode meliputi data preprocessing, data cleaning, label encoding, setelah itu dilakukan pelatihan model dan evaluasi menggunakan metrik accuracy, precision, recall, f1-score, ROC-AUC, serta validasi silang 5-Fold Cross-Validation. Hasil penelitian menunjukkan bahwa algoritma Random Forest memiliki kinerja lebih baik dibandingkan KNN, dengan F1-Macro Score sebesar 0,9396, ROC-AUC 0,9955, serta accuracy sebesar 92,20%. Sementara itu, KNN mencatatkan F1-Macro Score sebesar 0,9256, ROC-AUC 0,9867, dan accuracy sebesar 92,51%. Random Forest juga menunjukkan performa yang lebih stabil pada semua lipatan validasi silang. Berdasarkan temuan ini, Random Forest dinilai lebih efektif dalam mendeteksi serangan pada jaringan IoT.
Deteksi Serangan DDoS SYN Flood Pada Jaringan Internet of Things (IoT) Menggunakan Metode Deep Neural Network (DNN) Syifa Munawarah, Syifa Munawarah; Kurniabudi; Eko Arip Winanto
Jurnal Informatika Dan Rekayasa Komputer(JAKAKOM) Vol 4 No 1 (2024): JAKAKOM Vol 4 No 1 APRIL 2024
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jakakom.2024.4.1.1710

Abstract

The implementation of Internet of Things (IoT) systems and applications is increasingly widespread across various fields. This makes IoT an attractive target for cyber crime, especially Distributed Denial of Service (DDoS) attacks such as SYN Flood. This type of attack disrupts service availability and floods servers, causing them to lose resources. One method for detecting DDoS attacks is through an Intrusion Detection System (IDS). A novel technique in IDS implementation is Deep Learning, specifically the Deep Neural Network (DNN) method, capable of identifying precise mathematical manipulations to transform input into output. Therefore, this research proposes the use of the DNN method to detect SYN Flood DDoS attacks in IoT networks. Testing results from the study, which utilized the CICIoT2023 dataset consisting of 14 files with two labels, DDoS-SYN_Flood and BenignTraffic, provided satisfactory outcomes. Evaluation using epochs with values of 10, 50, and 100 showed that epoch 100 yielded the highest performance. This is evident from the average accuracy rate of 99.36%, precision of 99.44%, recall of 99.75%, and an f1-score of 99.59%.
Optimalisasi Jaringan Wifi dan Pemanfaatan Sumber Belajar berbasis Internet untuk Pembelajaran di SMA Kurniabudi; Abdul Rahim; Syilvia Wenny J; Ayu Ferenika; Dodi Sandra; Abdul Harris; Lola Yorita Astri; Cahyana Putra Pratama; Nida Afifah Rahma; Ferdha Nayoan; Aldrian
JPM: Jurnal Pengabdian Masyarakat Vol. 5 No. 3 (2025): Januari 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jpm.v5i3.2230

Abstract

Utilization of online learning resources is one alternative to overcome the limitations of conventional learning resources. By utilizing online learning resources, the atmosphere is more interactive and not boring. However, on the one hand, SMA Negeri 2 Batang Hari still has limitations in terms of access capacity to learning resources on the Internet. Support for adequate data communication network infrastructure is expected to overcome the problem of access to online resources. By developing a data communication network at SMA Negeri 2 Batang Hari, it can overcome obstacles in accessing learning resources and online learning for students and teachers. However, on the other hand, the knowledge and skills of students and teachers need to be improved, so that they can utilize online resources as learning resources and learning materials. The purpose of this community service activity is to optimize the use of data communication networks at SMA Negeri 2 Batang Hari by providing internet access points via a wifi network in the SMA Negeri 2 Batang Hari environment. This activity also increased the competence of students and teachers in utilizing learning resources and online learning. This activity was able to increase the capacity of internet access, especially in terms of the coverage area of ??wifi network access at SMA Negeri 2 Batang Hari which increased by 80%. In addition, this activity has increased student knowledge by 88% and teachers by 90% in utilizing learning resources and online learning.
Perbandingan Algoritma K-Means dan Fuzzy C-Means Clustering Pada Penilaian Kelurahan Berprestasi Kota Jambi: Studi Kasus pada Bagian Tata Pemerintahan Sekretariat Daerah Kota Jambi Pramudya, Yuga; Jasmir; Kurniabudi
Jurnal Manajemen Teknologi Dan Sistem Informasi (JMS) Vol 5 No 2 (2025): JMS Vol 5 No 2 September 2025
Publisher : LPPM STIKOM Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jms.2025.5.2.2298

Abstract

Abstract−The assessment of outstanding urban villages at the city level in Jambi faces challenges in defining categories for coaching groups and selecting the appropriate algorithm to handle heterogeneous data. To address this issue, clustering techniques using K-Means and Fuzzy C-Means algorithms were applied to segment coaching needs based on homogeneous value proximity. This study analyzed 204 sub-district assessment data using Python, producing clustering results with nearly equivalent cluster separation quality. The K-Means algorithm achieved a silhouette score of 0.3854, slightly higher than Fuzzy C-Means at 0.3831. Both algorithms formed consistent cluster patterns with average values of 82, 72, and 61, classified into three clusters: (1) Cluster 0 receives awards and career development promotions, (2) Cluster 1 focuses on management training and bureaucratic reform, and (3) Cluster 2 requires coaching clinics and technical guidance. The findings indicate that K-Means is more advantageous due to its simplicity, effectiveness in handling linear datasets, and clear data distribution. This clustering approach supports the Jambi City Government, particularly the Regional Secretariat Governance Section, in designing data-driven coaching strategies to enhance the quality of sub-district development.
Co-Authors Abdul Harris Abdul Rahim Afrizal Nehemia Toscany Akbar Aldino Wijaya Aldrian Amrullah, Wahyu Andika, Tripa Ayu Ferenika Cahyana Putra Pratama Chindra Saputra Dodi Sandra Dodi Sandra Eko Arip Winanto ENDRI ENDRI Fachruddin Ferdha Nayoan Hakim, Muhammad Furqan Husaein, Ahmad Jasmir Joni Devitra Kurniabudi, Kurniabudi Lola Yorita Astri, Lola Yorita Mansis, Muhammad Ilham MULYADI Nida Afifah Rahma Nika, Naria NURHADI Pramudya, Yuga Prasetio, Luky Purnama, Benni Putri, Ferika Syavina Rizal, Nadila ROBY SETIAWAN Rofi'i, Imam Saloma saputra, sahril Setiawan Assegaf Sharipuddin Sharipudin Siregar, Mulia Rohmayati Syifa Munawarah, Syifa Munawarah Syilvia Wenny J Tarigan, Wina Agustina WIJAYA, IBNU SANI WILLY RIYADI Yulita, Fitri