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All Journal IJITEE (International Journal of Information Technology and Electrical Engineering) Jatilima : Jurnal Multimedia Dan Teknologi Informasi International Journal of Engineering, Technology and Natural Sciences (IJETS) Jurnal Teknimedia: Teknologi Informasi dan Multimedia Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Emerging Information Science and Technology Academic Journal of Computer Science Research (AJCSR) Blend Sains Jurnal Teknik Wahana Duta Abdimas: Jurnal Pengabdian Masyarakat Jurnal Ilmu Komputer dan Sistem Informasi jabdimasunipem JKTi - Jurnal Keilmuan Teknologi Informasi Jurnal Pengabdian Masyarakat Terapan
Krisna Nuresa Qodri
Politeknik Negeri Cilacap
Agriculture, Biological Sciences & Forestry Humanities 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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Public Health Social Sciences Other

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Implementasi Metode Goal-Directed Design Dalam Perancangan Antarmuka Website MDMC Kabupaten Klaten Berbasis Kebutuhan Pengguna Adika Sri Widagdo; Fachruddin Edi Nugroho Saputro; Krisna Nuresa Qodri; Nisrina Akbar Rizky Putri; Rizal Adimas Ronaldo
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 5 No. 2 (2025): Mei 2026
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v5i2.355

Abstract

This research is driven by the need for structured information media, specifically a website, to support disaster response reporting at MDMC Klaten Regency. Previously, information remained fragmented on social media, necessitating a more comprehensive platform. This study aims to design the MDMC Klaten Regency website interface based on user needs to ensure effective information delivery. The method employed is Goal-Directed Design (GDD), consisting of Research, Modeling, Requirement, Framework, Refinement, and Support stages. Data were collected through observations, interviews, and document studies, then transformed into Volunteer and General Public personas. The result is a website interface prototype featuring report publication workflows and location mapping visualization as primary features. Usability evaluation using the System Usability Scale (SUS) instrument with 59 respondents yielded an average score of 87.97. These results place the system in the "Acceptable" category with a "Grade A" rating and an "Excellent" Adjective Rating. In conclusion, the GDD approach is effective in producing interface designs aligned with user goals, characterized by high levels of navigation ease and information clarity. This study recommends further development of map interactivity to continuously optimize the user experience.
Peningkatan Kapasitas UMKM Kabupaten Cilacap Melalui Kecerdasan Buatan dan Keamanan Transaksi Digital Bella Adinda Putri; Linda Perdana Wanti; Satriawan Desmana; Krisna Nuresa Qodri; Ratih Ratih; Abdul Rohman Supriyono; Muhammad Nur Faiz; Oman Somantri; Ratih Hafsarah Maharrani
Wahana Jurnal Pengabdian kepada Masyarakat Vol. 5 No. 1 (2026): Edisi Juni
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/wahana.v5i1.1778

Abstract

UMKM di era digital menghadapi tantangan karena kurangnya pemahaman tentang literasi digital dan kesadaran akan ancaman siber. Kegiatan ini bertujuan untuk meningkatkan pemahaman pelaku UMKM–yang didukung oleh BAZNAS Kabupaten Cilacap–dalam memanfaatkan teknologi AI dan aplikasi keamanan digital. Metode pelaksanaannya menggunakan pelatihan praktik langsung, diskusi interaktif, dan pendampingan langsung melalui dua tahap: (1) pengenalan konsep AI untuk keamanan transaksi digital; dan (2) pelatihan tentang aplikasi pendukung keamanan digital (GetContact, Kredibel, dan VirusTotal). Kegiatan ini melibatkan 100 pelaku UMKM dari berbagai sektor usaha. Evaluasi yang dilakukan melalui pre-test dan post-test menggunakan 10 pertanyaan terkait materi pelatihan menunjukkan peningkatan yang signifikan dengan rata-rata skor peserta meningkat dari 78,09 (pre-test) menjadi 97,50 (post-test), yang menggambarkan peningkatan sebesar 19,41 poin atau 28,98%. Hal ini menunjukkan bahwa pelatihan tersebut efektif meningkatkan literasi keamanan digital dan memberdayakan pelaku UMKM untuk melindungi bisnis mereka dari ancaman kejahatan siber dan penipuan online.
Analisis Performa ModSecurity Core Rule Set Menggunakan GoTestWAF untuk Mengidentifikasi Serangan dan Teknik Bypass pada Aplikasi Web Satriawan Desmana; Krisna Nuresa Qodri; Ratih Ratih; Bella Adinda Putri; Muhammad Abdul Muin
Academic Journal of Computer Science Research Vol 8, No 1 (2026): Academic Journal of Computer Science Research (AJCSR)
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/ajcsr.v8i1.16107

Abstract

Keamanan aplikasi web menghadapi tantangan yang semakin kompleks dengan meningkatnya serangan siber seperti SQL Injection, Cross-Site Scripting (XSS), Command Injection, serta berbagai teknik evasion yang dirancang khusus untuk menghindari mekanisme deteksi konvensional. ModSecurity sebagai Web Application Firewall (WAF) open-source telah banyak digunakan karena fleksibilitas dan integrasinya dengan OWASP Core Rule Set (CRS). Namun demikian, efektivitas ModSecurity sangat bergantung pada kualitas dan pembaruan rule set yang diimplementasikan. Penelitian ini bertujuan mengevaluasi performa ModSecurity versi 3 dengan CRS 4.19.0 dalam mendeteksi serangan modern menggunakan framework pengujian otomatis GoTestWAF. Pengujian dilaksanakan pada lingkungan terkontrol melalui analisis true-positive, true-negative, dan false-negative terhadap 816 payload berbahaya maupun legitimate. Hasil penelitian menunjukkan ModSecurity hanya mampu memblokir 45,44% dari total payload berbahaya, sementara 54,56% berhasil melewati perlindungan. Selain itu, 17,73% traffic aman salah diblokir (false positive), yang berpotensi mengganggu operasional aplikasi. Kelemahan terutama ditemukan pada payload berukuran besar, teknik obfuscation, encoding kompleks, dan struktur request non-standar. Secara keseluruhan, konfigurasi default CRS 4.19.0 pada paranoia level 1 belum memadai menghadapi serangan kontemporer. Optimalisasi diperlukan melalui peningkatan paranoia level, aktivasi optional rules, tuning aturan, dan penambahan custom rules. Penelitian ini memberikan kontribusi empiris bagi peningkatan implementasi WAF open-source pada aplikasi web masa kini.
Pembelajaran Berbasis Kasus untuk Pendidikan Keamanan Siber: Tinjauan Literatur Sistematis dan Agenda Penelitian Vokasi Bella Adinda Putri; Ratih Ratih; Krisna Nuresa Qodri; Satriawan Desmana; Abdul Rohman Supriyono
Blend Sains Jurnal Teknik Vol. 5 No. 1 (2026): Edisi Juli
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/blendsains.v5i1.1833

Abstract

Pembelajaran Berbasis Kasus (Case-Based Learning/CBL) telah terbukti efektif dalam pendidikan profesi seperti kedokteran, hukum, dan bisnis. Namun, penerapan dan kajian sistematisnya dalam bidang keamanan siber khususnya di pendidikan tinggi vokasi di negara berkembang masih sangat terbatas. Belum ada sintesis komprehensif yang memetakan pendekatan CBL, luaran kompetensi, instrumen pengukuran, maupun tantangan implementasi yang spesifik pada bidang ini. Tinjauan Literatur Sistematis (TLS) ini bertujuan memetakan pendekatan CBL dalam pendidikan keamanan siber (2014–2025), mengidentifikasi kompetensi yang dikembangkan, mensintesis instrumen pengukuran efektivitas, mengarakterisasi tantangan implementasi, dan menyusun agenda penelitian untuk pendidikan tinggi vokasi di negara berkembang dengan rujukan konteks Indonesia. Mengikuti panduan PRISMA 2020, pencarian sistematis dilakukan pada enam basis data elektronik (Scopus, Web of Science, IEEE Xplore, ACM Digital Library, ERIC, dan Google Scholar). Kriteria inklusi mengikuti kerangka PICOS. Dua peninjau independen melakukan penyaringan; penilaian kualitas menggunakan Mixed Methods Appraisal Tool (MMAT) yang diadaptasi. Sintesis menggunakan pendekatan naratif, tematik, dan pemetaan frekuensi. Terdapat sekitar 40–70 studi primer yang akan diinklusikan. Temuan yang diantisipasi mencakup dominasi kasus diskusi dan laboratorium; luaran kompetensi yang terkonsentrasi pada domain Serangan & Pertahanan serta Keamanan Sistem dari CyBOK; dan konteks vokasi negara berkembang yang sangat kurang terwakili. TLS ini menghasilkan peta komprehensif CBL dalam pendidikan keamanan siber, agenda penelitian berbasis bukti untuk institusi vokasi, dan rekomendasi desain modul CBL yang relevan untuk Prodi Rekayasa Keamanan Siber Politeknik Negeri Cilacap.
Analisis Komparatif Pengaruh Kedalaman Arsitektur Convolutional Neural Network untuk Deteksi Anomali Jaringan Krisna Nuresa Qodri; Satriawan Desmana; Bella Adinda Putri; Ratih Ratih; Muhammad Abdul Mu'in
Blend Sains Jurnal Teknik Vol. 5 No. 1 (2026): Edisi Juli
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/blendsains.v5i1.1841

Abstract

Tingkat kecanggihan serangan siber yang terus meningkat menjadi tantangan serius bagi sistem keamanan jaringan konvensional. Penelitian ini mengkaji efektivitas Convolutional Neural Network (CNN) dalam mendeteksi anomali jaringan menggunakan dataset UNSW-NB15. Dua arsitektur CNN dengan tingkat kompleksitas berbeda dibandingkan, yaitu CNN dasar dengan satu blok konvolusi dan CNN menengah dengan tiga blok konvolusi. Hasil eksperimen menunjukkan bahwa arsitektur CNN menengah memberikan kinerja yang lebih unggul dengan akurasi 97,91%, presisi 98,89%, dan nilai ROC-AUC 0,9979, jauh melampaui model dasar yang hanya mencapai akurasi 94,36%. Tingkat false positive yang rendah, yaitu 1,93%, serta tingkat false negative sebesar 2,18%, mengindikasikan kelayakan praktis yang kuat untuk diterapkan pada lingkungan operasional nyata. Temuan ini memberikan bukti empiris bahwa rekayasa kedalaman arsitektur yang moderat disertai regularisasi kuat memegang peranan krusial dalam menjaga stabilitas konvergensi dan mengeliminasi risiko overfitting ekstrem pada sistem deteksi intrusi jaringan.
Ensemble Deep Learning with Attention Mechanism and Explainable AI for Enhanced Brain Tumor Classification from MRI Images Krisna Nuresa Qodri; Ardiansyah Ardiansyah; Nisrina Akbar Rizky Putri; Adika Sri Widagdo; Fachruddin Edi Nugroho Saputro
Jurnal Internasional Teknik, Teknologi dan Ilmu Pengetahuan Alam Vol 8 No 1 (2026): International Journal of Engineering, Technology and Natural Sciences
Publisher : Universitas Teknologi Yogyakarta, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46923/ijets.v8i1.641

Abstract

Brain tumors represent a significant clinical challenge, with accurate classification being essential for treatment planning. Current deep learning approaches face two critical limitations: insufficient robust-ness across diverse imaging conditions and lack of clinical interpretability. Here we present an ensemble deep learning framework integrating three complementary architectures (MobileNetV2, EfficientNetB3, and DenseNet121) with spatial attention mechanisms and explainability features. Using 7,023 MRI images across four diagnostic categories (glioma, meningioma, pituitary tumor, and tumor-absent), our approach achieved 98.47% classification accuracy with balanced performance across all classes (F1-scores: 98.12% for glioma, 97.89% for meningioma, 98.76% for pituitary, 99.21% for tumor-absent cases). The ensemble demonstrated statistically significant improvement over individual models (p < 0.01, McNemar’s test), with gains of 1.24-1.75 percentage points. Integration of Gradient-weighted Class Activation Map-ping provided interpretable visual explanations with activation patterns consistently focusing on tumor regions. The findings demonstrate the potential of combining ensemble learning, attention, and visual explanation for brain tumor classification. However, the results represent internal validation on a single partition of aggregated public datasets and require confirmation through repeated validation and independent clinical evaluation.
Prediksi Analitik untuk Penyakit Ginjal Kronis: Perbandingan Metode Machine Learning Krisna Nuresa Qodri; Muhammad Rausan Fikri; Luthfi Ardi
JKTI Jurnal Keilmuan Teknologi Informasi Vol 1 No 1 (2025)
Publisher : Universitas Muhammadiyah Klaten

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61902/jkti.v1i1.1686

Abstract

Chronic kidney disease (CKD) is a progressive malady defined by reduced glomerular filtration rate, increased urinary albumin excretion or both, and is a major global public health concern with an extremely high unmet medical need. CKD is estimated to occur in 8-16% of the worldwide population and results in a substantially reduced life expectancy. Early detection and accurate prediction of CKD is crucial to reduce health complications such as hypertension, anemia, and premature death. This study aims to develop CKD prediction models using three machine learning methods: Random Forest, Naive Bayes, and Support Vector Machine, then compare the performance of each method. The dataset used is the CKD dataset from UCI Machine Learning Repository consisting of 400 instances with 24 attributes. Experimental results show that Random Forest achieved 90.50% accuracy, Naive Bayes achieved the highest accuracy of 94.21%, while SVM achieved 88.84% accuracy. The results indicate that Naive Bayes provides the best performance for chronic kidney disease prediction with superior accuracy compared to other methods. This prediction model can assist medical practitioners in early detection and appropriate clinical decision-making for CKD patient management.
Optimalisasi Keterampilan Administratif Siswa SMK Melalui Pelatihan Aplikasi Microsoft Office Krisna Nuresa Qodri; Fachruddin Edi Nugroho Saputro; Adika Sri Widagdo; Nisrina Akbar Rizky Putri; Erma Widyastuti
Jurnal Pengabdian Masyarakat Terapan Vol 2 No 3 (2025): JUPITER Desember 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jupiter.2.3.72

Abstract

Kegiatan pengabdian ini bertujuan untuk meningkatkan keterampilan administratif siswa-siswi SMK Muhammadiyah 3 Klaten Tengah melalui pelatihan intensif penggunaan aplikasi Microsoft Office, khususnya Word dan Excel. Permasalahan utama yang dihadapi sekolah adalah kurangnya penguasaan aplikasi perkantoran akibat terbatasnya kurikulum yang menekankan literasi digital. Kegiatan ini melibatkan tahapan perencanaan, pelaksanaan pelatihan, serta evaluasi berbasis pre-test dan post-test. Hasil pelatihan menunjukkan adanya peningkatan signifikan dalam pemahaman dan keterampilan siswa, terutama pada penggunaan Excel. Setelah mengikuti kegiatan ini siswa-siswi sudah mampu untuk menggunakan rumus dasar dari Excel serta sudah mampu membuat chart. Kegiatan ini berkontribusi positif dalam meningkatkan literasi digital dan kesiapan siswa menghadapi dunia kerja berbasis teknologi informasi.
The Influence of Developing an Understanding of Basic Programming Concepts Through Educational Games as A Learning Method For Elementary School Students. Kurnianti, Apriliya; Praditia, Rizky Nanda; Qodri, Krisna Nuresa
Emerging Information Science and Technology Vol. 5 No. 2 (2024): November
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v5i2.24781

Abstract

Integrating engaging learning methods into the educational landscape has become increasingly crucial for enhancing student understanding and engagement. This study investigates the impact of educational games as a learning method for improving elementary school students' comprehension of basic programming concepts. The research hypothesizes that educational games can significantly enhance the understanding of programming concepts by making abstract ideas more tangible and engaging through interactive and enjoyable learning environments. Using a quasi-experimental design, the study involved two groups of elementary school students: the experimental group, which utilized an educational game designed for teaching introductory programming concepts, and the control group, which received traditional instruction. Both groups underwent assessments of their understanding of basic programming concepts before and after the intervention through standardized tests. The results demonstrated a statistically significant improvement in the scores of students in the experimental group compared to those in the control group. This suggests that educational games not only aid in better understanding complex subjects such as programming and increase students' motivation and engagement levels. The findings of this study contribute to educational practices by illustrating how educational games can effectively support the introduction and teaching of programming at an early age within the elementary educational system. Furthermore, the study highlights the potential of integrating such tools into standard curricula to enhance student learning across various subjects. The study urges future research to explore the long-term impacts of educational games on learning outcomes and how these tools can be further integrated into the educational system
Co-Authors Abdul Rohman Supriyono Adika Sri Widagdo Adika Sri Widagdo Adika Sri Widagdo Adika Sri Widagdo Al-Baihaqi, Muhammad Zulfikhar Ardiansyah Ardiansyah Ardiansyah Banna, Dion Al Bella Adinda Putri Edi Nugroho Saputro, Fachruddin Erma Widyastuti Fachruddin Edi Nugroho Saputro Fachruddin Edi Nugroho Saputro Fachruddin Edi Nugroho Saputro Farkhani, Jodi Nur Habib Ismail Hanung Adi Nugroho Hidayani, Diesti Indah Soesanti Kumalasari, Puput Kurnianti, Apriliya Linda Perdana Wanti Luthfi Ardi Muhammad Abdul Mu'in Muhammad Abdul Muin Muhammad Nur Faiz Muhammad Rausan Fikri Nisrina Akbar Rizky Putri Nisrina Akbar Rizky Putri Nisrina Akbar Rizky Putri Oman Somantri Pandu Cahyadi, Fian Praditia, Rizky Nanda Rahmi Nurhaini Ratih Hafsarah Maharrani Ratih Ratih Reza Giga Isnanda, Reza Giga Rizal Adimas Ronaldo Romadhani, Mustofa Ronaldo, Rizal Adimas Sapurtro , Fachruddin Edi Nugroho Satriawan Desmana Sri Widagdo, Adika