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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Jurnal Edukasi dan Penelitian Informatika (JEPIN) Proceeding of the Electrical Engineering Computer Science and Informatics PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Jurnal Ilmiah Media Sisfo JOURNAL V-TECH (VISION TECHNOLOGY) JATI (Jurnal Mahasiswa Teknik Informatika) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Manajemen Pendidikan dan Ilmu Sosial (JMPIS) Jurnal Teknik Informatika (JUTIF) RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI Journal of Trends Economics and Accounting Research Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Komunikasi, Sains dan Teknologi (JKST) Jurnal Informatika dan Rekayasa Komputer Jurnal Manajemen Teknologi dan Sistem Informasi Jurnal Manajemen Sistem Informasi Jurnal of Information Technology and Society (JITS) Jurnal Pengabdian Masyarakat Unama Akademika Prosiding Seminar Nasional Ilmu Teknik
Purnama, Benni
Universitas Dinamika Bangsa
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Decision Support System for Selecting Outstanding Religious Counselors in Jambi Province Using Analytical Hierarchy Process and Technique for Order Preference by Similarity to Ideal Solution Suryani, Suryani; Zaenal Abidin, Dodo; Purnama, Benni; Gunardi, Gunardi
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.5385

Abstract

Religious counselors play an essential role in fostering religious moderation, strengthening community cohesion, and promoting social harmony. However, the evaluation of their performance remains largely manual, leading to subjectivity, inconsistency, and limited accountability. This study develops a web-based Decision Support System that integrates the Analytical Hierarchy Process and the Technique for Order Preference by Similarity to Ideal Solution to enhance objectivity, transparency, and data-driven evaluation. The Analytical Hierarchy Process was applied to determine the importance of five criteria—portfolio, scientific paper, program video, presentation or interview, and absenteeism—through expert pairwise comparisons. The Technique for Order Preference by Similarity to Ideal Solution was then used to rank twenty-four religious counselors from the Regional Office of the Ministry of Religious Affairs in Jambi Province. The results show that portfolio (47.4%) and presentation or interview (24.4%) were the most influential criteria, while the others served as complementary factors. Counselors with comprehensive documentation and strong communication skills consistently ranked higher, validating the system’s analytical reliability. This study’s novelty lies in applying a multi-criteria decision-making framework within the religious sector, directly aligned with the 2024 Technical Guidelines for the Islamic Religious Counselor Award (Keputusan Dirjen Bimas Islam No. 352/2024). Furthermore, this research supports the Ministry of Religious Affairs’ Eight Priority Transformation Programs (Asta Protas), particularly in digitalizing governance and promoting transparent, accountable, and data-driven management. From an informatics perspective, this system demonstrates the effective implementation of decision-support algorithms in a web-based environment, highlighting the contribution of information technology to evidence-based performance evaluation.
PENERAPAN DATA MINING DALAM MENGELOMPOKKAN JUMLAH UMKM KOTA JAMBI MENGGUNAKAN K-MEANS CLUSTERING: Objek Penelitian Muhammad Aji Triatama; Jasmir; Benni Purnama
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.2025.5.2.2316

Abstract

Abstrak−Usaha Mikro, Kecil, dan Menengah (UMKM) memiliki kontribusi yang signifikan dalam mendukung perkembangan ekonomi di tingkat lokal, termasuk di Kota Jambi. Namun, banyak UMKM menghadapi kendala dalam pengelolaan data dan perumusan strategi bisnis yang efektif. Penelitian ini bertujuan untuk mengelompokkan UMKM di Kota Jambi dengan memanfaatkan metode K-Means Clustering sebagai bagian dari teknik data mining. Data penelitian mencakup 1.331 UMKM di bidang fashion, dengan variabel karakteristik seperti kepemilikan, modal awal, penghasilan per bulan dan per tahun, jumlah karyawan, serta aset. Hasil penelitian menunjukkan bahwa perhitungan manual menghasilkan tiga kelompok: 627 UMKM (Cluster 1) direkomendasikan menerima bantuan peralatan, 358 UMKM (Cluster 2) mendapatkan fasilitas kelembagaan, dan 346 UMKM (Cluster 3) diarahkan untuk pelatihan. Sementara itu, perhitungan dengan tools Rapid Miner menghasilkan pembagian berbeda akibat variasi pengambilan centroid. Cluster 0 berisi 840 UMKM, Cluster 1 berisi 9 UMKM, dan Cluster 2 berisi 482 UMKM. Penelitian ini membuktikan bahwa K-Means Clustering dapat memberikan wawasan berharga tentang distribusi dan kebutuhan UMKM, sehingga membantu pengambil kebijakan dalam merancang program yang lebih tepat sasaran. Dengan demikian, metode ini diharapkan dapat berkontribusi pada pengembangan UMKM secara lebih terarah dan berkelanjutan di Kota Jambi.
Web-Based E-Learning System Design with Integrated Webinar Features at STIT Al-Falah Rimbo Bujang Habibi Ul Akbar; Benni Purnama; Dodo Zaenal Abidin
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 6 No. 1 (2026): MALCOM January 2026
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v6i1.2545

Abstract

This study examines challenges faced by STIT Al-Falah Rimbo Bujang in implementing online learning that is not yet optimally integrated. Students and lecturers currently rely on multiple platforms such as WhatsApp, Zoom, email, and Google Drive to manage schedules, learning materials, assignments, and communication. This platform fragmentation leads to operational inefficiencies, coordination difficulties, limited monitoring, and decreased student engagement. Observations and interviews with academic administrators identified three main problems: the need to access multiple applications for a single course, the lack of automated attendance recording during webinar sessions, and inefficient assignment submission and grading via private messaging, which increases administrative workload and the risk of data loss. A student satisfaction survey conducted in the even semester of the 2023/2024 academic year showed that these issues reduced the effectiveness of online learning by up to 40%. To overcome these problems, this study proposes the design of a web-based e-learning system with integrated webinar features that centralizes learning activities into a single platform. The system is developed using the waterfall model, including requirement analysis, system design, implementation, testing, and maintenance. UML is applied for system modeling, while PHP, MySQL, and Bootstrap are used for implementation
Analisis Kepuasan Pengguna Aplikasi WPS Office Menggunakan Metode End User Computing Satisfaction (EUCS) Fournia Nova; Setiawan Assegaff; Benni Purnama
Prosiding Seminar Nasional Ilmu Teknik Vol. 2 No. 2 (2025): Desember: Prosiding Seminar Nasional Ilmu Teknik
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/prosemnasproit.v2i2.68

Abstract

WPS Office stands for Writer, Presentation, and Spreadsheets—a software suite offering diverse office functions, including document processing, spreadsheet creation, and presentation tools. This study analyzes user satisfaction levels and the influence of the variables Content, Accuracy, Format, Ease of Use, and Timeliness on WPS Office application users in Jambi City, using the End User Computing Satisfaction method. Data were gathered through an online questionnaire distributed to students in Jambi City who had used the application; created via Google Forms, it garnered 385 responses. Post-collection, analysis was conducted using Structural Equation Modeling in SmartPLS software version 4. Of the five hypotheses tested, four were accepted. The results reveal that accuracy, format, ease of use, and timeliness positively and significantly influence user satisfaction, while content shows no significant effect.
Analisis Kelayakan Pemberian Kredit dengan Algoritma Naïve Bayes untuk Antisipasi Risiko Kredit Bermasalah Pada BPR Ukabima Lestari Cabang Jambi Anggi Saputra; Setiawan Assegaff; Benni Purnama
Prosiding Seminar Nasional Ilmu Teknik Vol. 2 No. 2 (2025): Desember: Prosiding Seminar Nasional Ilmu Teknik
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/prosemnasproit.v2i2.96

Abstract

This study analyzes creditworthiness assessment and predicts non-performing loan (NPL) risk using the Naïve Bayes algorithm at BPR Ukabima Lestari, Jambi Branch. A quantitative data mining approach with probabilistic classification is applied. The dataset includes borrower attributes such as age, occupation, income, loan amount, tenor, collateral, and repayment history. Research stages comprise data preprocessing, model development, and performance evaluation using accuracy, precision, recall, and F1-score implemented in RapidMiner. The results indicate that the Naïve Bayes model achieves 99.58% accuracy, demonstrating strong capability to predict potential problem loans accurately and efficiently, supporting data-driven credit decisions and strengthening credit risk management in microbanking institutions.
Analisis Kepuasan Pengguna Aplikasi VSCO di Kota Jambi dengan Menggunakan Metode EUCS Fitria, Choryn; Benni Purnama; Suyanti Suyanti; Dwi Junita
Prosiding Seminar Nasional Ilmu Teknik Vol. 2 No. 2 (2025): Desember: Prosiding Seminar Nasional Ilmu Teknik
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/prosemnasproit.v2i2.99

Abstract

The use of the VSCO application continues to face technical issues, including errors during editing, limited feature access, and login problems that affect user satisfaction. This study analyzes user satisfaction with the VSCO application using the End User Computing Satisfaction (EUCS) method. The study involved 385 VSCO users as respondents, with data collected through questionnaires and analyzed using SmartPLS 3.0. In this research, Accuracy variable does not affect user satisfaction, whereas the Content, Format, Ease of Use, and Timeliness variables have a significant effect on user satisfaction. The study shows that content quality, interface design, ease of use, and system timeliness are the main factors influencing user satisfaction with the VSCO application.
Penerapan Algoritma K-Means Untuk Klasterisasi Balita Rentan Stunting dan Wasting Berdasarkan Indikator Antropometri Rizky Khairun’nisa; Benni Purnama; Sharipuddin Sharipuddin
Prosiding Seminar Nasional Ilmu Teknik Vol. 2 No. 2 (2025): Desember: Prosiding Seminar Nasional Ilmu Teknik
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/prosemnasproit.v2i2.155

Abstract

Stunting and wasting are nutritional problems in toddlers that remain a double burden of malnutrition in Indonesia and have an impact on the quality of health and future human resource development. Monitoring the nutritional status of toddlers is generally carried out using anthropometric indicators, but the use of this data is still limited to descriptive analysis. This study aims to apply the K-Means algorithm in clustering infants vulnerable to stunting and wasting based on anthropometric indicators, so that groups of infants with different levels of nutritional vulnerability can be identified. The dataset used consists of infant data with variables of gender, age (months), height (cm), and weight (kg). The research stages included data preprocessing, encoding categorical variables, data normalization, determining the optimal number of clusters using the Elbow and Silhouette Score methods, and analyzing the characteristics of each cluster. The evaluation results showed that the optimal number of clusters was four. Each cluster has different anthropometric characteristics and distributions of stunting and wasting status, ranging from groups with relatively normal nutritional conditions, groups with a tendency toward overnutrition, to groups that are vulnerable to acute and chronic malnutrition. These clustering results provide a more comprehensive and segmented mapping of toddlers, which can be used as a basis for formulating more targeted and data-driven nutrition policies and interventions.
Komparasi Algoritma SVM dan Random Forest Dalam Sentimen Analisis Review Shopee di Google Play Store Dengan Anova Eko Susanto; Sharipuddin Sharipuddin; Benni Purnama
Prosiding Seminar Nasional Ilmu Teknik Vol. 2 No. 2 (2025): Desember: Prosiding Seminar Nasional Ilmu Teknik
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/prosemnasproit.v2i2.177

Abstract

The rapid growth of e-commerce in Indonesia, particularly the Shopee platform, has generated a large volume of user reviews on the Google Play Store, which can be analyzed to understand consumer sentiment. This study aims to compare the performance of the Support Vector Machine (SVM) and Random Forest (RF) algorithms in binary sentiment classification (positive and negative) on Shopee reviews, as well as to statistically test the significance of their differences using One-Way ANOVA. A total of 400,498 reviews were collected via web scraping, preprocessed through text normalization, tokenization, and Indonesian language stemming, and then feature-extracted using TF-IDF and Count Vectorizer. Evaluation results show that SVM achieved an accuracy of 91.77%, precision of 91.49%, recall of 91.77%, and F1-Score of 91.56%, while RF achieved an accuracy of 90.07%, precision of 91.68%, recall of 90.07%, and F1-Score of 90.55%. ANOVA confirmed that the performance difference between the two algorithms is statistically significant (p-value = 0.0007) with a large effect size (η² = 0.1815). Therefore, SVM is recommended as a more optimal and consistent algorithm for automated sentiment analysis of Indonesian e-commerce reviews, while also providing a replicable methodological framework for similar future research.
Transformer-Based Multi-Class Intrusion Detection Using CICIoMT2024 Dataset for Secure IoMT Networks Winanto, Eko Arip; Sharipuddin, Sharipuddin; Purnama, Benni; Nurhadi, Nurhadi; Afuan, Lasmedi
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 3 (2026): JUTIF Volume 7, Number 3, June 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.3.5512

Abstract

Internet of Medical Things (IoMT) ecosystems significantly enhance healthcare services but simultaneously expand the attack surface, exposing medical networks to diverse cyber threats such as distributed denial-of-service and spoofing attacks. Existing intrusion detection systems for IoMT are often limited to binary classification and struggle to capture complex multi-class attack behaviors, particularly under highly imbalanced data distributions. This study proposes a deep Transformer-based intrusion detection model as a reproducible baseline for multi-class intrusion detection in IoMT environments. The model is evaluated on the CICIoMT2024 dataset, which comprises 19 traffic classes including benign and multiple attack categories. Data preprocessing involves stratified data splitting, feature normalization, and label encoding to ensure fair evaluation. The proposed baseline employs a six-layer Transformer encoder with eight attention heads and is trained using the AdamW optimizer. Experimental results demonstrate an overall accuracy of 98.76% and a macro F1-score of 0.92, indicating strong detection capability across most attack classes. The model achieves excellent performance on benign traffic and high-volume attacks such as DDoS and DoS, while performance degradation is observed on minority classes, including ARP spoofing, highlighting the impact of class imbalance. These findings establish the proposed Transformer model as a transparent and robust baseline for IoMT intrusion detection research. By providing reproducible performance benchmarks, this work supports future development of hybrid and imbalance-aware detection mechanisms aimed at enhancing real-time security in medical cyber-physical systems.
Kompetensi Digital di Era Disrupsi melalui Pelatihan Pengoperasian Kamera dan Live Streaming Profesional untuk Pelajar Husaein, Ahmad; Yudha Pradana, Lazuardi; Gunardi; Purnama, Benni
Jurnal Pengabdian Masyarakat UNAMA Vol 5 No 1 (2026): JPMU Volume 5 Nomor 1 April 2026
Publisher : LPPM Universitas Dinamika Bangsa

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

Abstract

Pelatihan "Peningkatan Kompetensi Digital Siswa melalui Pelatihan Teknis Penyetelan dan Penggunaan Kamera untuk Produksi Siaran Langsung Profesional di Platform YouTube" bertujuan untuk meningkatkan keterampilan siswa dalam pengoperasian perangkat kamera dan penyiaran langsung profesional. Dalam era digital yang semakin berkembang, kemampuan ini menjadi krusial untuk mempersiapkan siswa menghadapi tantangan di dunia industri. Dengan metode pelatihan yang terstruktur, siswa menerima materi teori dan praktik tentang teknologi penyiaran, serta dipandu dalam menghasilkan konten berkualitas tinggi di platform media sosial. Setiap siswa terlibat secara aktif, dan pelatihan ini juga bertujuan untuk membangun rasa percaya diri serta mendukung pengembangan kreativitas mereka. Hasil dari kegiatan ini menunjukkan peningkatan signifikan pada kompetensi digital siswa, terbentuknya kelompok kerja yang produktif, dan kesiapan siswa menjadi produser konten digital. Luaran dari kegiatan ini diharapkan dapat berkontribusi terhadap pengembangan ilmu pengetahuan di bidang pendidikan vokasi serta menjadi referensi bagi institusi lain dalam mengimplementasikan pelatihan serupa
Co-Authors Afriany, Renny Ahmad Heryanto anggi saputra Apriyani Bedine Kerim Benediktus Rolando Beni Irawan Darmawijoyo, Darmawijoyo Deris Stiawan Dodi Sandra Dodo Zaenal Abidin Dwi Junita Dwi Putri, Salsabila An-nisa Eko Arip Winanto Eko Susanto Etriyanti, Siska Falencia, Feiren Firmansyah Fitria, Choryn Fournia Nova Gunardi Gunardi Gunardi Habibi Ul Akbar Herry Mulyono Hetty Rohayani Husaein, Ahmad Ibnu Sani Wijaya Idris, Mohd. Yazid Jasmir Jasmir, Jasmir Jefri, Antonius Joni Devitra, Joni Jumairi, Nopri Khairuldi Kurniabudi Kurniabudi, Kurniabudi Lasmedi Afuan Lazuardi Yudha Pradana Lola Yorita Astri, Lola Yorita M Riza Pahlevi Meisak, Despita Mohd Yazid bin Idris Mohd. Yazid Idris Mohd. Yazid Idris Mohd. Yazid Idris Muhammad Aji Triatama NAIBAHO, RONALD Nita Christine Nuraini, Ike Nurhadi Nurhadi Nurhadi Nurul Marwiyah, Siska Puri, Fathia Putri, Azhiah Rahmaningtyas, Anindya Rahmat Budiarto Riska Pertiwi Ningrum Rizky Khairun’nisa Rohaini, Eni Samsuryadi Samsuryadi Setiawan Assegaf SETIAWAN, HANIF Shairuppdin, Shairuppdin Sharipuddin Sharipuddin, Sharipuddin Sharipuddin, Sharipuddin Suroto Suroto Suyanti Suyanti Syaifudin Syaifudin, Syaifudin Tanuwijaya, Michael Valencia, Valencia Widiyanto, Dimas Akhbar Widyawati, Nilu Gede WIJAYA, IBNU SANI Winanto, Eko Arif Winarto, Eko Arip Yaticha, Ni Luh Ayu Yudha Pradana, Lazuardi Yulandari, Restika Yundari, Yundari Zaenal Abidin, Dodo