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TECHNOVATAR
Published by Awatara Publisher
ISSN : -     EISSN : 30258874     DOI : https://doi.org/10.61434/technovatar.v2i1
Core Subject : Science, Education, Engineering,
Computer Science & IT Control & Systems Engineering Engineering Industrial & Manufacturing Engineering Mathematics
TECHNOVATAR Jurnal Teknologi, Industri, dan Informasi adalah sebuah jurnal ilmiah yang diterbitkan oleh Awatara Publisher dengan fokus utama pada pengkajian mendalam tentang perkembangan teknologi, industri, dan informasi dalam dunia digital. Jurnal ini menyajikan informasi dan pengetahuan terkini yang menginspirasi serta memperluas pemahaman tentang kemajuan teknologi, industri, dan informasi yang memberikan dampak positif bagi perkembangan masyarakat dalam era digital. Jurnal ini terbit secara berkala sebanyak tiga kali dalam setahun pada bulan Januari, April, Juli, dan Oktober.
Arjuna Subject : Ilmu Pengambilan Keputusan (semua kategori) - Sistem Informasi dan Manajemen
Articles 26 Documents
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GIS, IOT, DAN MACHINE LEARNING UNTUK INFORMASI BANJIR DI JAWA BARAT: SCOPING REVIEW CEPAT ardiansyah yudhono, muhamad septian; indra surya permana; Dimas Dwi Rianto
TECHNOVATAR Jurnal Teknologi, Industri, dan Informasi Vol 4 No 1 (2026): JANUARI
Publisher : Awatara Publisher

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Abstract

This rapid scoping review maps geographic information systems (GIS), Internet of Things (IoT), and machine learning (ML) approaches for flood information and further research in West Java. A Population–Concept–Context framework guided targeted Consensus and publisher searches, with a literature cutoff of October 2025. Crossref metadata and DOI resolution were checked. Thirteen studies were mapped: six local studies and seven purposively selected comparators; nine were read in full and four through abstracts. GIS and ML each appeared in nine studies, and IoT in four. No mapped study reported operational integration of all three. Local evidence distinguished coastal tidal inundation, downstream river flooding, urban susceptibility, and Upper Citarum modelling. Data priorities included tidal boundaries, elevation, channel geometry, rainfall timing, and event inventories. The proposed architecture separates mapping, observation, prediction, and information delivery. Findings guide data selection without establishing operational readiness. Targeted retrieval, abstract-only records, and the absence of duplicate screening limit completeness.
KOMPARASI ZOOM, GOOGLE MEET, MICROSOFT TEAMS, DAN WEBEX UNTUK PEMBELAJARAN DARING: TINJAUAN SISTEMATIS FITUR, KEAMANAN, KEMUDAHAN, DAN AKSESIBILITAS Sutriyono, Ade; Novan Aditya Herlambang; Farrel Pratama Putra; Muhammad Fikri Ariel; Muhammad Fiqih Setiawan
TECHNOVATAR Jurnal Teknologi, Industri, dan Informasi Vol 3 No 4 (2025): OKTOBER
Publisher : Awatara Publisher

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Abstract

Universities still rely on video conferencing for synchronous classes, yet platform choice is often driven by habit or licensing rather than evidence. This study compares Zoom, Google Meet, Microsoft Teams, and Webex on features and performance, security and privacy, ease of use, and accessibility. A PRISMA 2020 systematic review of Crossref records and citation searching was combined with an analysis of official vendor documentation. Of 123 records, 13 studies reported in 14 publications (2021 to 2025) were included. All studies examined Zoom and Google Meet, seven examined Teams, and only three examined Webex. Google Meet runs entirely in the browser and was favoured under limited bandwidth. Zoom offered the richest teaching features and the best captions for disabled users, but its free tier stops group meetings at 40 minutes. Teams integrates with Microsoft 365, but its browser client shows a single stream and several functions require the desktop application. Webex includes end-to-end encryption in its free plan but no captions. On every platform, end-to-end encryption removes captions, recording, or breakout rooms, and no platform was judged fully accessible. Institutions should match platforms to learning scenarios and provide configuration guidance for lecturers
PEMANFAATAN LARGE LANGUAGE MODEL DALAM PEMBELAJARAN PEMROGRAMAN: SYSTEMATIC LITERATURE REVIEW Bambang Irawan
TECHNOVATAR Jurnal Teknologi, Industri, dan Informasi Vol 4 No 4 (2026): OKTOBER
Publisher : Awatara Publisher

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Abstract

The use of large language models (LLMs) in programming education is growing rapidly, yet evidence on its benefits, risks, and best practices has not been mapped in an integrated way. This study aimed to map the characteristics of empirical studies, synthesize benefits and risks including plagiarism and overreliance, and identify evidence-supported instructional practices. This systematic literature review followed PRISMA 2020. Searches were run through Consensus on 9 October 2026 using 14 queries, yielding 140 records. Screening, extraction, and six-item quality assessment were performed by a single AI-assisted reviewer based on abstracts. A total of 68 studies published between 2023 and 2026 were included and synthesized thematically. The most frequently reported benefit was on-demand feedback and debugging help (30 studies), followed by motivation and self-efficacy (9). Of 21 studies reporting learning outcomes, 10 were positive, 5 mixed, 5 null, and 1 negative. Main risks were overreliance (22 studies), unreliable or solution-leaking output (20), and academic integrity concerns (9). Promising practices include pedagogical scaffolding, prompt literacy training, self-regulation support, process-based assessment, human oversight, and explicit AI-use policies. Findings are preliminary because the search was limited to one aggregator and screening relied on abstracts.
SISTEM REKOMENDASI TOPIK TUGAS AKHIR MAHASISWA S1 INFORMATIKA BERBASIS CONTENT-BASED FILTERING: STUDI SIMULASI PERBANDINGAN TF-IDF, BM25, DAN LATENT SEMANTIC ANALYSIS Nur Ariesanto Ramdhan
TECHNOVATAR Jurnal Teknologi, Industri, dan Informasi Vol 4 No 3 (2026): Juli
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Abstract

Choosing a final project topic is an early decision that shapes a student's research direction. This study builds and evaluates a prototype recommender for undergraduate Informatics final project topics based on content-based filtering, using each student's interests and course track record as the query. Four methods are compared, namely TF-IDF with cosine similarity, BM25, Latent Semantic Analysis (LSA), and a hybrid of BM25 and LSA, together with a random baseline. The offline evaluation uses 20 synthetic corpora, each with 400 topics from eight Informatics areas and 150 student profiles, and reports Precision@k, MRR, and NDCG@10. Because real data were unavailable and Sentence-BERT could not be downloaded in the research environment, this is a simulation study and does not evaluate Sentence-BERT; its evaluation script is provided. BM25 obtained the highest Precision@5 (0.927), followed by the hybrid (0.914), TF-IDF (0.895), LSA (0.876), and random (0.209); all pairwise differences in Precision@5 remained significant after Holm correction. The hypothesis that latent semantic methods are more robust to term variation was not supported, because LSA declined the most as term variation increased. These findings are preliminary and bounded by the assumptions of the data generator; validation on real final project repositories with expert relevance judgments is still required.
RANCANGAN VERIFIKASI INTEGRITAS DOKUMEN PDF BERBASIS QR CODE DAN SHA-256 DENGAN EVALUASI LOKAL Sutriyono, Ade
TECHNOVATAR Jurnal Teknologi, Industri, dan Informasi Vol 4 No 4 (2026): OKTOBER
Publisher : Awatara Publisher

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Abstract

Document verification requires distinguishing issuance records, file equality, and signatory identity. This study designs a PDF verification mechanism using QR codes and SHA-256 and evaluates its comparison component locally. The method combines a targeted literature search, architecture and decision-model design, and testing with 12 synthetic PDFs containing 1, 3, or 10 pages. Demonstration QR codes are embedded before PDF finalization and hashing to prevent circular hash dependencies, ensuring strict byte-level integrity verification. Seventy-two comparisons cover identical controls, text changes, numeric changes, added pages, metadata changes, and different documents carrying the same QR code. All 12 controls yield matching hashes, whereas all 60 variants yield different hashes. Extracted text remains unchanged in the metadata cases. Six status-decision cases produce the specified local outcomes. These findings support byte comparison within the tested scope while identifying its limits: scanning a QR code without submitting the PDF does not check the user-held file, and a hash does not authenticate the signatory. The Google Workspace architecture remains an undeployed design. Cloud security, network performance, and usability are not evaluated. The contribution consists of a finalization procedure, distinct verification labels, and a reproducible test package.
KEPATUHAN KONFIGURASI TLS DAN HEADER KEAMANAN WEBSITE PTN DAN PTS DI WILAYAH LLDIKTI IV Firdaus, Mohamad
TECHNOVATAR Jurnal Teknologi, Industri, dan Informasi Vol 4 No 3 (2026): Juli
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Abstract

This cross-sectional study assesses TLS and security response headers on 16 purposively selected institutional websites: four public and twelve private universities in the LLDIKTI IV service area. Verified TLS connections and limited homepage requests supported a criterion-based configuration assessment. Twelve HTTPS HTML homepages were eligible for header analysis; three returned blocking responses and one showed client-dependent certificate verification. Fifteen successful handshakes negotiated TLS 1.3. HSTS appeared on 8/12 homepages, nosniff on 7/12, and active CSP on 5/12. Five met the framing profile and one met the selected Referrer-Policy profile. No observed CSP met the selected script, object, and base-URI profile. Independent checks confirmed assessed header values on three homepages. Findings support targeted configuration ownership, staged policy deployment, and repeatable monitoring. The nonprobability sample and uneven coverage restrict population-level conclusions

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