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All Journal Jurnal Transformatika Mimbar Agribisnis: Jurnal Pemikiran Masyarakat Ilmiah Berwawasan Agribisnis Jurnal Pengabdian Ilung (Inovasi Lahan Basah Unggul) Hippocampus: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknologi Informasi Prosiding Seminar Hasil Penelitian dan Pengabdian Kepada Masyarakat Jurnal Sistem Informasi (JASISFO) Julia Jurnal
Astuti, Theresia Widji
Politeknik Negeri Sambas
Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Dentistry Economics, Econometrics & Finance Education Energy Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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PORTAL INFORMASI PELAYANAN CALON JAMAAH HAJI BERBASIS WEB PADA KEMENTERIAN AGAMA KABUPATEN SAMBAS Nurbaiti; Widji Astuti, Theresia; Lena, Sonty
Jurnal Sistem Informasi (JASISFO) Vol. 3 No. 2 (2022): September 2022
Publisher : Politeknik Negeri Sriwijaya

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

Abstract

The Ministry of Religion of the Sambas Regency is a Vertical Agency of the Ministry of Religion domiciled in the Regency. One of the tasks of the Ministry of Religion of Sambas Regency is to provide services, guidance and guidance in the field of Hajj and Umrah. For services at the Ministry of Religion of Sambas Regency to prospective pilgrims, it is still not effective and efficient. The method used is Prototype with the stages of collecting requirements, building prototyping, evaluating prototyping, coding the system, testing the system, evaluating the system, and using the system. The Web-Based Information Portal for Prospective Hajj Pilgrims Services at the Ministry of Religion of Sambas Regency is built with functionalities according to user needs, namely: information on the schedule of Hajj rituals, information on Hajj travel schedules, information on estimated Hajj departures, information on material for Hajj rituals, information on data for prospective pilgrims, information health data of prospective pilgrims, message information and report information.
Artificial Intelligence-Based Automatic Text Detection System Using Multi-Layer Pattern Recognition Kartika Imam Santoso; Santoso, Kartika; Edi Widodo; Theresia Widji Astuti
Jurnal Transformatika Vol. 23 No. 2 (2026): January 2026
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v23i2.13256

Abstract

The rapid advancement of generative AI models such as ChatGPT, Claude, and Gemini raises serious concerns about the authenticity of academic and professional documents. This study develops a detection system that uses a combination of linguistic, structural, and statistical pattern analysis to identify AI-generated text and classify the responsible AI model. The system analyzes more than 12 different parameters from uploaded documents (PDF, DOCX, TXT formats). The detection engine operates through seven analytical layers: signature detection, linguistic analysis, word pattern analysis, structural analysis, feature pattern analysis, vocabulary and grammar assessment, and AI fingerprinting. The scoring mechanism provides a general AI probability score (0-100%) and individual probability scores for 10 different AI models. In testing with 100 documents, the system achieved 76.8% accuracy in identifying AI-generated text and 87.3% accuracy in classifying the source AI model. Sentence entropy analysis, paragraph uniformity assessment, and distinctive linguistic markers proved most effective. This study demonstrates that multi-layer pattern recognition is a viable approach for detecting and classifying AI-generated text, with implications for academic integrity, content verification, and digital forensics.
Membangun Network Video Recorder (NVR) MenggunakanSet Top Box (STB) Pada Rusunawa Poltesa Berbasis Wireless Yudistira; Theresia Widji Astuti; Muhammad Usman; Ellys Mey Sundari; Fiqih Akbari
Julia: Jurnal Ilmu Komputer An Nuur Vol 6 No 1 (2026): juliajournal
Publisher : LPPM Universitas An Nuur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35720/julia.v6i1.57

Abstract

This research proposes an innovative solution for recording and storing surveillance video data in the parking environment of Rusunawa Poltesa using a Set Top Box (STB)-based Network Video Recorder (NVR) with Armbian Linux operating system. STBs, typically used for television signal reception, are adapted into intelligent devices to efficiently control and manage surveillance cameras (IP Camera) at a lower cost compared to conventional NVRs. The use of wireless technology increases the flexibility of camera placement without the limitations of cables, simplifies installation, and allows for the adjustment of camera positions according to surveillance needs. The STB-based NVR implementation uses the open-source Shinobi Community Edition (Shinobi CE) software written in Node.js, enabling video recording from IP cameras in H.264 and H.265 formats. This research aims to find an integrated and innovative solution to improve the surveillance system in Rusunawa Poltesa in a modern, efficient, and cost-effective manner. The research results show that the STB-based NVR system can record video at frame rates up to 15 FPS at HD resolution and 5 FPS at SD resolution, with memory consumption of approximately 4.02 MB per minute for HD resolution (1920x1080) and 1.98 MB per minute for SD resolution (1280x720).
Penerapan Small Area Estimation Berbasis Hierarchical Bayes untuk Estimasi Anak Tidak Sekolah di Provinsi Kalimantan Barat Muhammad Usman; Ria Hayatun Nur; Ana Uluwiyah; Eni Lestariningsih; Theresia Widji Astuti; Fathushahib Fathushahib; Heldi Hastriyandi; Sanusi Sanusi
Jurnal Teknologi Informasi Vol 5, No 1 (2026): Mei
Publisher : Universitas Teuku Umar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35308/jti.v5i1.15261

Abstract

Penelitian ini bertujuan untuk mengestimasi persentase anak berusia 7–17 tahun yang tidak bersekolah pada tingkat kabupaten/kota di Provinsi Kalimantan Barat dengan menggunakan pendekatan Small Area Estimation (SAE). Relative Standard Error (RSE) di atas 25% sering dihasilkan dari estimasi langsung data Susenas, sehingga kurang reliabel untuk dasar pengambilan kebijakan. Untuk mengatasi hal tersebut, penelitian ini membandingkan dua metode estimasi tidak langsung, yaitu Empirical Best Linear Unbiased Prediction (EBLUP) dan Hierarchical Bayes Beta (HB Beta). Data utama bersumber dari Susenas Maret 2023, sedangkan variabel penyerta diambil dari Podes 2024, publikasi BPS, serta data APBD pendidikan dan infrastruktur pendidikan. Hasil analisis menunjukkan bahwa model EBLUP masih menghasilkan dua wilayah dengan RSE di atas 25%, sedangkan model HB Beta mampu menurunkan seluruh nilai RSE menjadi di bawah 25% (rata-rata 6,45%). Selain itu, model HB Beta terbukti konvergen berdasarkan trace plot, density plot, dan autocorrelation plot. Kabupaten Kubu Raya memiliki persentase anak tidak sekolah terendah (5,63%), sedangkan Kabupaten Sanggau tertinggi (11,98%). Temuan ini menunjukkan bahwa penerapan metode SAE HB Beta efektif dalam meningkatkan reliabilitas estimasi anak tidak sekolah pada level kabupaten/kota di Kalimantan Barat dan dapat menjadi dasar perumusan kebijakan pendidikan berbasis data yang lebih presisi.
Co-Authors Agam, Beryaldi Ahmad Ridho Ana Uluwiyah Dian Sari Edi Widodo Ellys Mey Sundari Eni Lestariningsih Fachruddin Fachruddin Fathushahib fathushahib fathushahib fathushahib, fathushahib Fiqih Akbari Heldi Hastriyandi Heldi Hastriyandi Iklas Sanubary Kartika Imam Santoso Kristiandi, Kiki Laipaka, Robertus Lang Jagat Lena, Sonty Marselina, Maya Muhammad Usman Muhammad Usman, Muhammad Nur, Ria Hayatun Nurbaiti Nurul Fatimah Yunita Ria Hayatun Nur Rini Fertiasari Santoso, Kartika Santoso, Pande Putu Agus Sanusi Sanusi Sanusi Soni Soni, Soni Sri Wahyuni Suhendra Vanie Wijaya Yudistira