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All Journal Infotekmesin Journal of Innovation Information Technology and Application (JINITA) Jurnal Pengabdian Teknologi Tepat Guna
Muhammad Nur Faiz
Unknown Affiliation
Religion Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Public Health

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Pengembangan Perangkat Lunak Untuk Deteksi DDoS Berbasis Neural Network Arif Wirawan Muhammad; Muhammad Nur Faiz; Ummi Athiyah
Infotekmesin Vol 13 No 2 (2022): Infotekmesin: Juli, 2022
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v13i2.1544

Abstract

System security issues are a vital factor that needs to be considered in the operation of systems and networks, which will later be used for disaster mitigation and preventing attacks on the network. Distributed Denial of Services (DDoS) is a form of attack carried out by individuals or groups to damage data through servers or malware in the form of flooding packets, therefore it can paralyze the network system used. Network security is a factor that must be maintained and considered in an information system. DDoS can take the form of Ping of Death, flood, Remote control attack, User Data Protocol (UDP) flood, and Smurf Attack. This study aims to develop software to detect DDoS attacks based on network traffic logs. The software has been tested and run according to the neural network algorithm. This software was developed with an interface that makes it easier for users to detect the source IP whether the IP is carrying out a DDoS attack or normal.
Pengembangan Desa Digital Dengan Penerapan Sistem Informasi Kearsipan Untuk Meningkatkan Pelayanan Publik Pada Pemerintah Desa Banjarwaru Kecamatan Nusawungu Kabupaten Cilacap Santi Purwaningrum; Ratih Hafsarah Maharrani; Agus Susanto; Prih Diantono Abda'u; Muhammad Nur Faiz; Oman Somantri; Ari Kristiningsih; Khoeruddin Wittriansyah
JURNAL PENGABDIAN TEKNOLOGI TEPAT GUNA Vol 6 No 1 (2025): Teknologi Tepat Guna (TTG)
Publisher : Universitas Sahid Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47942/jpttg.v6i1.1925

Abstract

Pelayanan Publik yang efektif dan efisien menjadi salah satu tolak ukur masyarakat dalam menilai kinerja penemrintah daerah secara kasat mata. Pelayanan publik seperti pembuatan surat dan pencarian data arsip sangat berpengaruh terhadap kualitas layanan pada Kantor Desa Banjarwaru. Proses pengarsipan surat dan administrasi lainnya di Desa Banjarwaru saat ini belum terdigitalisasi dan terdokumensi dengan baik. Hal tersebut sering membuat terjadinya kesalahan dalam penyimpanan data surat masuk dan membutuhkan ruang yang cukup luas untuk menyimpannya, selain itu juga seringnya terjadi kesalahan dalam penulisan nomor surat keluar karena pencarian nomor surat terakhir masih dicari manual pada buku besar. Guna untuk mewujudkan visi dan misi Desa Banjarwaru, maka sangat diperlukan Penerapan Sistem Informasi Kearsipan untuk pengembangan Desa Digital. Sistem informasi arsip persuratan mempunyai tujuan mengubah metode penyimpanan surat atau administrasi lainnya dengan proses pengarsapan secara digital sehingga mengurangi penggunaan kertas dan lebih efektif dan akurat.
A Reproducible Explainable NLP Workflow for Workplace Sexism Detection: Classification Performance, Rationale Faithfulness, and Sanity Checks Annisa Romadloni; Linda Perdana Wanti; Laura Sari; Muhammad Nur Faiz; Qisthi Alhazmi Hidayaturrohman
Journal of Innovation Information Technology and Application (JINITA) Vol 8 No 1 (2026): JINITA, June 2026
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v8i1.3222

Abstract

Workplace sexism often appears as indirect, deniable language (e.g., patronizing compliments, competence-doubting questions), making automated detection and organizational response difficult. This study evaluates a transparent, explanation-ready NLP pipeline on the Sexist Workplace Statements (SWS) dataset (1,137 items) with its binary labels: certain sexism vs. ambiguous/neutral. Using the provided fixed stratified split (1,023 train; 114 test), we train a TF–IDF (word 1–2, character 3–5 n-grams) logistic regression baseline and report performance stability across five random seeds. To audit model evidence, sparse token rationales are extracted from linear feature contributions and quantify faithfulness with ERASER-style comprehensiveness (logit drop when rationales are removed) and sufficiency (logit change when only rationales are kept), benchmarked against random-token rationales. The baseline achieves 0.768 ± 0.006 accuracy and 0.759 ± 0.007 macro-F1, with errors concentrated in the ambiguous/neutral class. Faithfulness tests show that model-selected rationales substantially affect the sexism logit (comprehensiveness 1.335 ± 0.001), while remaining insufficient in isolation (|sufficiency| 1.075 ± 0.006). Sanity checks reveal modest sensitivity to gender-term swaps and reduced rationale overlap underweight randomization. Overall, results motivate cautious deployment: explanation-driven auditing can surface shortcut risks and clarify where binary labels blur neutral language and deniable sexism, pointing to future work on finer-grained annotation and human rationale collection.
Co-Authors Agus Susanto Ahmad Khairul Shiddiq Amirah Putri Annisa Romadloni Ari Kristiningsih Arif Wirawan Muhammad Awaluddin Insyira Syahwa Naswari Irene Boli Khoeruddin Wittriansyah Laura Sari Linda Perdana Wanti Muh. Kahlil Muh. Kahlil Gibran Muhammad Fadhil Mu’min Nurhalisa Oman Somantri Paula Vebrianti Kewa Payon Riantobi Prih Diantono Abda'u Qisthi Alhazmi Hidayaturrohman Ratih Hafsarah Maharrani Riandy Santi Purwaningrum Syahril Ramadhan Ummi Athiyah