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FORENSIC ANALYSIS OF MITM ATTACK ON ‘AISYIYAH UNIVERSITY YOGYAKARTA NETWORK USING NIST METHOD

Ridwan, Virgiawan aqil, Firdonsyah, Arizona
Abstract: Abstract: Man-in-the-Middle (MITM) attacks are a threat that can occur on public wireless networks, including campus Wi-Fi environments. This study aims to analyze MITM attacks on the Wi-Fi network at Universitas ‘Aisyiyah… iyah Yogyakarta using the National Institute of Standards and Technology (NIST) digital forensics methodology. The study applied the four NIST phases: collection, examination, analysis, and reporting. The digital evidence analyzed included packet capture (PCAP) files, as well as digital traces such as browser history, cookies, and cache data obtained from the victim’s device. The analysis process utilized Wireshark, the SQLite Database Browser, and ChromeCacheView to identify suspicious activity and correlate the discovered digital traces. The results of the study show that the MITM attack was successfully reconstructed through the correlation of digital traces, leading to the identification of ARP spoofing and DNS spoofing originating from a device with the IP address 192.168.200.12 and the MAC address a0:47:d7:73:ef:fb. The correlation of digital traces in the victim’s network and system traffic revealed communication redirection and web access manipulation. This study concludes that the NIST method is capable of reconstructing MITM attacks and identifying digital evidence from activity traces on both the network and the system.             Keywords: ARP spoofing; digital forensics; DNS spoofing; MITM; NIST     Abstrak: Serangan Man-in-the-Middle (MITM) merupakan ancaman yang dapat terjadi pada jaringan nirkabel publik, termasuk lingkungan WiFi kampus. Penelitian ini bertujuan menganalisis serangan MITM pada jaringan WiFi Universitas ‘Aisyiyah Yogyakarta menggunakan metode forensik digital National Institute of Standards and Technology (NIST). Penelitian menerapkan empat tahapan NIST, yaitu collection, examination, analysis, dan reporting. Bukti digital yang dianalisis meliputi file packet capture (PCAP), jejak digital berupa history browser, cookies, dan cache yang diperoleh dari perangkat korban. Proses analisis menggunakan Wireshark, SQLite Database Browser, dan ChromeCacheView untuk mengidentifikasi aktivitas mencurigakan serta mengorelasikan jejak digital yang ditemukan. Hasil penelitian menunjukkan bahwa serangan MITM berhasil direkonstruksi melalui korelasi jejak digital yang mengarah pada identifikasi ARP spoofing dan DNS spoofing dari perangkat dengan alamat IP 192.168.200.12 dan MAC address a0:47:d7:73:ef:fb. Korelasi jejak digital pada lalu lintas jaringan dan sistem korban menunjukkan adanya pengalihan komunikasi serta manipulasi akses web. Penelitian ini menyimpulkan bahwa metode NIST mampu merekonstruksi serangan MITM dan mengidentifikasi bukti digital dari jejak aktivitas pada jaringan maupun sistem.   Kata kunci: ARP spoofing; DNS spoofing; forensik digital; MITM; NIST

DEVELOPMENT OF AN AUGMENTED REALITY APPLICATION FOR LEARNING THE VOLUME AND SURFACE AREA OF THREE-DIMENSIONAL SHAPES

Sapta, Andy, Pakpahan, Sondang Purnamasari
Abstract: This study focuses on the development of an Augmented Reality (AR)–based learning application designed to assist students in understanding the mathematical concepts of volume and surface area of three-dimensional geometric… tric shapes. The development process adopted the Multimedia Development Life Cycle (MDLC) model, which consists of six systematic stages: concept, design, material collecting, assembly, testing, and distribution. The research concentrated on the development and expert validation stages. Validation results from content and media experts indicate that the application meets pedagogical and technical feasibility standards. The content expert confirmed that the materials align with the national mathematics curriculum and are presented in a clear, contextual, and accurate manner, while the media expert highlighted the user-friendly interface, interactive features, and visual appeal of the application. Theoretically, this AR-based medium bridges the gap between abstract mathematical concepts and concrete visualization by enabling students to interact directly with virtual 3D objects. Practically, the application enhances learning motivation and engagement by providing dynamic, interactive experiences. Overall, this research contributes to the advancement of educational technology by offering a systematic model for developing AR-based learning media that support active and meaningful learning in the digital era.

DEVELOPMENT OF A DIGITAL E-CRM AS A SOLUTION FOR CUSTOMER RELATIONSHIP MANAGEMENT AND TRANSACTION ACTIVITIES AT TOKO ZUMA

Nurul Azzuma, Afdhal Syafnur, Rahayu, Elly
Abstract: Abstract: Toko Zuma faces challenges in optimizing customer relationship management and transaction recording due to conventional manual systems, which hinder real-time loyalty monitoring and sales analysis. This research… h aims to design a digital Electronic Customer Relationship Management (E-CRM) system as an integrative solution for systematic and centralized management. The design method employs Unified Modeling Language (UML) for requirements analysis, user interface design, and Black-box Testing for validation. Results demonstrate a 100% success rate across all primary modules. The platform features Point Reward, automated transaction management, and live chat for direct interaction. Implementation enables personalized promotional strategies based on accurate data to increase customer retention. In conclusion, the Digital E-CRM system effectively automates business processes, serving as a strategic instrument for transparent and measurable customer relationship management. Keywords: digital e-crm; relationship management; toko zuma; transaction activities.     Abstrak: Toko Zuma menghadapi kendala dalam optimalisasi manajemen hubungan pelanggan dan pencatatan transaksi karena masih menggunakan sistem manual konvensional. Penelitian ini bertujuan merancang sistem Electronic Customer Relationship Management (E-CRM) digital sebagai solusi integratif untuk pengelolaan basis data dan transaksi secara terpusat. Metode perancangan meliputi analisis kebutuhan menggunakan Unified Modeling Language (UML), desain antarmuka, dan validasi fungsional melalui Black-box Testing. Hasil pengujian menunjukkan tingkat keberhasilan 100% pada seluruh modul utama. Platform ini dilengkapi fitur Point Reward, manajemen transaksi otomatis, dan media interaksi live chat. Implementasi sistem ini memungkinkan strategi promosi personal berdasarkan data akurat untuk meningkatkan retensi pelanggan. Simpulannya, sistem E-CRM digital berhasil mengotomatisasi proses bisnis dan menjadi instrumen strategis dalam manajemen hubungan pelanggan yang transparan dan terukur. Kata kunci: aktivitas transaksi; digital e-crm; pengelolaan relasi; toko zuma.

PERFORMANCE EVALUATION OF AUTOMATED MEETING SUMMARIZATION BASED ON OPEN AI WHISPER AND INDOT5 FINE-TUNING

Lanang Oka Wiyana, I Gusti, Indah Ciptayani, Putu, Adisimakrisna Peling, Ida Bagus
Abstract: Abstract: Manual meeting documentation risks losing important information due to cognitive fatigue. Although automated summarization models have evolved, integrated end-to-end systems for Indonesian spoken language remain… n highly limited. This study aims to design and evaluate an end-to-end automated meeting summarization architecture that directly integrates Automatic Speech Recognition (ASR) via OpenAI Whisper for transcription and the IndoT5 language model for abstractive summarization. IndoT5 was fine-tuned using a dataset of 486 Indonesian spoken language transcript pairs. Testing was conducted on a CPU infrastructure using MP4, MP3, and WAV formats. Results show the optimal fine-tuning configuration significantly improved accuracy, achieving ROUGE-1 (0.4167), ROUGE-2 (0.1973), and ROUGE-L (0.2701) scores. Computationally, the system achieved a Real-Time Factor below 1, processing data faster than the actual recording duration. Conclusively, integrating Whisper and IndoT5 shows potential in producing coherent meeting summaries with lightweight computational overhead, making it viable for local infrastructure implementation to ensure data privacy. Keywords: abstractive summarization; ASR; end-to-end pipeline; IndoT5; real-time factor     Abstrak: Dokumentasi rapat manual rentan menghilangkan informasi penting akibat keterbatasan kognitif. Meskipun model peringkas otomatis telah berkembang, implementasi sistem terintegrasi (end-to-end) khusus percakapan lisan berbahasa Indonesia masih sangat terbatas. Penelitian ini bertujuan merancang dan mengevaluasi arsitektur peringkas rapat otomatis end-to-end yang mengintegrasikan langsung Automatic Speech Recognition (ASR) melalui OpenAI Whisper untuk transkripsi dan model bahasa IndoT5 untuk peringkasan abstraktif. Adaptasi domain dilakukan melalui fine-tuning IndoT5 menggunakan 486 pasang dataset transkrip lisan berbahasa Indonesia. Pengujian pada infrastruktur CPU menggunakan format MP4, MP3, dan WAV. Hasil pengujian menunjukkan konfigurasi fine-tuning optimal berhasil meningkatkan akurasi, dengan skor ROUGE-1 (0,4167), ROUGE-2 (0,1973), dan ROUGE-L (0,2701). Sistem mendemonstrasikan efisiensi komputasi dengan nilai Real-Time Factor di bawah 1, mengindikasikan waktu pemrosesan lebih cepat dari durasi rekaman asli. Kesimpulannya, integrasi Whisper dan IndoT5 menunjukkan potensi dalam menghasilkan ringkasan yang koheren dengan beban komputasi ringan, sehingga layak diimplementasikan pada infrastruktur lokal organisasi untuk menjaga privasi data. Kata kunci: ASR; end-to-end pipeline; IndoT5; peringkasan abstraktif; real-time factor  

FORENSIC ANALYSIS OF DIGITAL ARTIFACTS OF QR CODE PHISHING ATTACK AT 'AISYIYAH UNIVERSITY YOGYAKARTA

Djaibakal, Yunan Al-husaini, Firdonsyah, Arizona
Abstract: Abstract: The use of QR Codes in academic settings has increased with the digitization of attendance systems, but it has also introduced potential abuse in the form of quishing attacks (QR phishing). Previous studies have… e mainly focused on user behavior, while forensic analysis of digital artifacts as evidence is still limited. This study aims to conduct a forensic analysis of browser artifacts resulting from interactions with dangerous QR Codes at Aisyiyah University Yogyakarta using the framework of the National Justice Institute (NIJ). Six investigation parameters are defined: domain identification, endpoint identification, identification of supporting resources, visualization of image artifacts, timestamp correlation, and HTML reconstruction. Data is obtained from the Google Chrome profile directory and analyzed using Autopsy, focusing on Web Cache, Browser History, and Cookies artifacts. The results showed that five parameters were successfully identified with an investigation success rate of 83.3%, while HTML reconstruction could not be fully achieved due to cache limitations. These findings show that Web Cache artifacts provide evidentiary value in the forensic investigation of QR Code-based attacks. Future research should focus on improving full-page reconstruction techniques. Keywords: browser forensics; digital artifacts; NIJ; quishing; Web Cache     Abstrak: Penggunaan Kode QR di lingkungan akademik telah meningkat seiring dengan digitalisasi sistem absensi, tetapi juga menimbulkan potensi penyalahgunaan dalam bentuk serangan phishing (QR phishing). Studi sebelumnya sebagian besar berfokus pada perilaku pengguna, sementara analisis forensik artefak digital sebagai bukti masih terbatas. Studi ini bertujuan untuk melakukan analisis forensik artefak browser yang dihasilkan dari interaksi dengan Kode QR berbahaya di Universitas 'Aisyiyah Yogyakarta menggunakan kerangka kerja Lembaga Kehakiman Nasional (NIJ). Enam parameter investigasi didefinisikan: identifikasi domain, identifikasi titik akhir, identifikasi sumber daya pendukung, visualisasi artefak gambar, korelasi stempel waktu, dan rekonstruksi HTML. Data diperoleh dari direktori profil Google Chrome dan dianalisis menggunakan Autopsy, dengan fokus pada artefak Cache Web, Riwayat Browser, dan Cookie. Hasil menunjukkan bahwa lima parameter berhasil diidentifikasi dengan tingkat keberhasilan investigasi sebesar 83,3%, sementara rekonstruksi HTML tidak dapat sepenuhnya dicapai karena keterbatasan cache. Temuan ini menunjukkan bahwa artefak Cache Web memberikan nilai bukti dalam investigasi forensik serangan berbasis Kode QR. Penelitian selanjutnya harus fokus pada peningkatan teknik rekonstruksi halaman penuh.   Kata kunci: forensik peramban; artefak digital; NIJ; quishing; web cache

IMPLEMENTATION OF A PYTHON-BASED SCHEDULED AUDIO ALARM SYSTEM FOR LIBRARY LITERACY SUPPORT

Audya Eka Putri, Khalifah, Setyowati, Endah
Abstract: Abstract: Libraries function not only as information centers but also as literacy spaces that require an orderly and communicative service environment. One supporting service in fostering such an environment is the delivery… ery of literacy greetings to visitors. In practice, greetings are commonly delivered manually or through conventional bells, leading to inconsistency and dependence on staff availability. This study was conducted at the Amir Machmud Library, Ministry of Home Affairs, Jakarta, Indonesia, aiming to design and evaluate a Python-based scheduled audio alarm system for automated literacy greetings. An applied experimental method was employed, including system design, Python script development, scheduling configuration using Windows Task Scheduler, and direct system testing on a library computer connected to ceiling speakers. The system requires initial execution via Command Prompt (CMD) when the computer is powered on, after which it operates automatically according to predefined schedules. Testing results demonstrate that the system performs scheduled audio playback accurately and operates stably without further manual intervention. The findings indicate that the proposed system provides a practical and efficient solution to enhance service consistency and support a structured and conducive literacy environment in the library.             Keywords: scheduled audio alarm; library automation; python; literacy greeting.     Abstrak: Perpustakaan tidak hanya berfungsi sebagai pusat informasi, tetapi juga sebagai ruang literasi yang memerlukan suasana layanan yang tertib dan komunikatif. Salah satu bentuk dukungan layanan tersebut adalah penyampaian sapaan literasi kepada pengunjung. Dalam praktiknya, penyampaian sapaan masih dilakukan secara manual atau menggunakan bel konvensional sehingga kurang konsisten dan bergantung pada petugas. Penelitian ini dilaksanakan di Perpustakaan Amir Machmud, Kementerian Dalam Negeri, Jakarta, Indonesia, dengan tujuan merancang dan menguji sistem alarm audio terjadwal berbasis Python sebagai media penyampaian sapaan literasi. Metode yang digunakan adalah metode eksperimental terapan melalui tahapan perancangan sistem, pengembangan skrip Python, konfigurasi penjadwalan menggunakan Windows Task Scheduler, serta pengujian langsung pada komputer perpustakaan yang terhubung dengan speaker plafon. Sistem bekerja dengan mekanisme inisialisasi awal melalui Command Prompt (CMD) saat komputer dinyalakan, kemudian selanjutnya berjalan otomatis sesuai jadwal yang telah ditentukan. Hasil pengujian menunjukkan bahwa sistem mampu memutar audio secara konsisten dan stabil pada waktu yang telah diatur tanpa intervensi lanjutan dari petugas. Dengan demikian, sistem ini dapat menjadi solusi sederhana dan efisien untuk mendukung terciptanya suasana literasi yang lebih terstruktur dan kondusif di lingkungan perpustakaan.   Kata kunci: alarm audio terjadwal; otomasi perpustakaan; python; sapaan literasi.

OPTIMIZING RETRIEVAL-AUGMENTED GENERATION FOR DOMAIN-SPECIFIC KNOWLEDGE SYSTEMS THROUGH FINE-TUNING AND PROMPT ENGINEERING

Ahmad Fajri, Rila Mandala
Abstract: Abstract: This study discusses the optimization of RAG for a FAQ system in the field of information technology product security certification at BSSN. Although LLM generate reliable responses, they often lack up-to-date… and domain-specific knowledge, which can be addressed through the RAG approach. This research aims to optimize a domain-specific RAG system by improving embedding performance, enhancing prompt robustness, and increasing retrieval accuracy. The research methods consist of three stages. The first stage involves fine-tuning the bge-m3 embedding model and evaluating its performance using MRR, Recall, and AUC. The second stage applies prompt engineering techniques, namely the SRSM and Autodefense, to mitigate direct-injection and escape-character prompt injection attacks. The third stage evaluates the proposed RAG system using Precision, Recall, and F1-Score metrics against four baseline models. The results of research show that the fine-tuned embedding model achieves higher performance than the original model, with MRR@1 and Recall@1 values of 0.80 and an AUC@100 of 0.7023. In addition, the proposed prompt engineering techniques demonstrate robustness against prompt injection attacks, while the overall RAG system attains a perfect Precision, Recall, and F1-Score of 1.00. In conclusion, the proposed approach effectively enhances retrieval accuracy, embedding quality, and system security, resulting in a more reliable RAG-based FAQ system for information technology product security certification. Keywords: embedding fine-tuning; large language model; prompt engineering; prompt injection mitigation; retrieval-augmented generation   Abstrak: Studi ini membahas optimasi RAG untuk sistem FAQ di bidang sertifikasi keamanan produk teknologi informasi di BSSN. Meskipun LLM menghasilkan respons yang andal, mereka seringkali kurang memiliki pengetahuan terkini dan spesifik domain, yang dapat diatasi melalui pendekatan RAG. Penelitian ini bertujuan untuk mengoptimalkan sistem RAG spesifik domain dengan meningkatkan kinerja embedding, meningkatkan ketahanan prompt dan meningkatkan akurasi pengambilan. Metode penelitian terdiri dari tiga tahap. Tahap pertama melibatkan fine-tuning model embedding bge-m3 dan mengevaluasi kinerjanya menggunakan Mean Reciprocal Rank (MRR), Recall, dan AUC. Tahap kedua menerapkan teknik rekayasa prompt, yaitu Self- SRSM dan Autodefense, untuk mengurangi serangan direct-injection dan escape-character prompt injection. Tahap ketiga mengevaluasi sistem RAG yang diusulkan menggunakan metrik Presisi, Recall, dan F1-Score terhadap empat model dasar. Hasil penelitian menunjukkan bahwa model embedding yang disempurnakan mencapai kinerja yang lebih tinggi daripada model asli, dengan nilai MRR@1 dan Recall@1 sebesar 0,80 dan AUC@100 sebesar 0,7023. Selain itu, teknik rekayasa prompt yang diusulkan menunjukkan ketahanan terhadap serangan injeksi prompt, sementara sistem RAG secara keseluruhan mencapai Presisi, Recall, dan F1-Score sempurna sebesar 1,00. Kesimpulannya, pendekatan yang diusulkan secara efektif meningkatkan akurasi pengambilan, kualitas embedding dan keamanan sistem, menghasilkan sistem FAQ berbasis RAG yang lebih andal untuk sertifikasi keamanan produk teknologi informasi. Kata kunci: penyempurnaan embedding; model bahasa besar; rekayasa prompt; mitigasi injeksi prompt; retrieval-augmented generation

COMPARISON OF BILSTM, SVM FOR PBB-P2 TAX POLICY SENTIMENT ANALYSIS

Rofiqoh, Dayana, Subarkah, Pungkas, Isnaini, Khairunnisak Nur
Abstract: Abstract: The policy to increase the Rural and Urban Land and Building Tax (PBB-P2) in Indonesia often elicits mixed reactions from the public. Some support it because they believe it can strengthen regional fiscal capacity,… ity, while others reject it because they are concerned that it will increase the economic burden on the community. Understanding public sentiment towards this policy is important for evaluating the effectiveness of the policy and formulating appropriate communication strategies. This study aims to analyze public sentiment towards the PBB-P2 increase policy using data uploaded on Platform X (Twitter). The data were collected through crawling with the keyword “building tax,” then processed through several preprocessing stages before classifying tweets into positive and negative sentiments. Two models were used: Support Vector Machine (SVM) and Bidirectional Long Short-Term Memory (BiLSTM). Results show that SVM outperformed BiLSTM, achieving training accuracy of 99.4% and testing accuracy of 85.9%, with accuracy 0.8595, precision 0.8536, recall 0.8595, and F1-score 0.8449. Meanwhile, BiLSTM achieved training accuracy of 86.9% and testing accuracy of 82.9%, with accuracy 0.8294, precision 0.8150, recall 0.8294, and F1-score 0.8080. These findings suggest SVM is more effective in classifying public sentiment and can support better evaluation of regional tax policies.             Keywords: sentiment analysis; PBB-P2; BiLSTM; SVM; X platform     Abstrak: Kebijakan kenaikan tarif Pajak Bumi dan Bangunan Perdesaan dan Perkotaan (PBB-P2) di In-donesia sering memunculkan beragam reaksi dari masyarakat. Sebagian mendukung karena dianggap dapat memperkuat kapasitas fiskal daerah, sementara lainnya menolak karena kha-watir menambah beban ekonomi masyarakat. Pemahaman terhadap sentimen publik atas ke-bijakan tersebut penting untuk mengevaluasi efektivitas kebijakan dan merumuskan strategi komunikasi yang tepat. Penelitian ini bertujuan menganalisis sentimen masyarakat terhadap kebijakan kenaikan PBB-P2 menggunakan data unggahan di Platform X (Twitter). Data dik-umpulkan melalui proses crawling dengan kata kunci “pajak bangunan” kemudian diproses melalui beberapa tahap preprocessing sebelum diklasifikasikan menjadi sentimen positif dan negatif. Dua model digunakan dalam penelitian ini, yaitu Support Vector Machine (SVM) dan Bidirectional Long Short-Term Memory (BiLSTM). Hasil penelitian menunjukkan bahwa SVM memiliki kinerja lebih baik dibandingkan BiLSTM, dengan akurasi pelatihan 99,4% dan akurasi pengujian 85,9%. Nilai akurasi 0,8595, precision 0,8536, recall 0,8595, dan F1-score 0,8449. Sementara itu, BiLSTM memperoleh akurasi pelatihan 86,9% dan akurasi pengujian 82,9%, dengan akurasi 0,8294, precision 0,8150; recall 0,8294; dan F1-score 0,8080. Temuan ini menunjukkan bahwa SVM lebih efektif dalam mengklasifikasikan sentimen publik serta dapat mendukung evaluasi kebijakan pajak daerah dengan lebih baik.   Kata kunci: analisis sentimen; PBB-P2; BiLSTM; SVM; platform X

DEVELOPMENT OF A QR CODE-BASED WEBAR TO DIGITIZE LOCAL WISDOM AS AN EFFORT TO INCREASE TOURIST ATTRACTION IN BORDER AREAS

P, Noviyanti, Mira, Alexander Jerry
Abstract: Abstract: Current technological developments play a crucial role in driving the tourism industry, one of which is the utilization of technology. However, tourist attractions in border areas face challenges such as limited&#8230; d access to digital information and a lack of interactive media to present local wisdom such as history, customs, and culture. This study aims to develop and implement a QR Code-based Web-based Augmented Reality (WebAR) to digitize local wisdom at tourist attractions, making information more engaging and accessible to tourists. The research methodology adopted three approaches: UCD (User-Centered Design), Agile methods, and TAM (Technology Acceptance Model). This platform contains the local wisdom of two tourist villages in the border area, namely Sebujit Village and Jagoi Babang Village. The results of testing and evaluation using multiple linear regression and SEM-PLS methods on 45 respondents showed that the WebAR technology acceptance model was significant (F = 6.583; p < 0.001). User Attitude (ATU) is a key variable that significantly influences Intention to Use (BI) (β=0.429; p=0.001), while Ease of Use (PEOU) and Benefit (PU) indirectly influence BI through ATU. As additional validation, the classification test yielded an accuracy of 88.90% and an F1-score of 0.941, confirming that QR Code-based WebAR is effective and well-received as a digital information and promotion medium for local wisdom in border areas. Keywords: border areas; local wisdom; qr code; tourist attractions; web augmented reality.   Abstrak: Perkembangan teknologi saat ini memiliki peran penting dalam mendorong industri pariwisata, salah satunya dengan pemanfaatan teknologi. Namun, objek wisata di daerah perbatasan menghadapi tantangan seperti keterbatasan akses informasi digital dan kurangnya media interaktif untuk menyajikan kearifan lokal seperti sejarah, adat istiadat, dan budaya. Penelitian ini bertujuan untuk mengembangkan dan mengimplementasikan Web-based Augmented Reality (WebAR) berbasis QR Code untuk digitalisasi kearifan lokal objek wisata, menjadikan informasi lebih menarik dan mudah diakses bagi wisatawan. Metodologi penelitian mengadopsi tiga pendekatan, UCD (User-Centered Design), metode Agile, dan TAM (Technology Acceptance Model). Platform ini memuat kearifan lokal dua desa wisata di daerah perbatasan, yaitu Desa Sebujit dan Desa Jagoi Babang. Hasil pengujian dan evaluasi dengan metode regresi linier berganda dan SEM-PLS pada 45 responden menunjukkan bahwa model penerimaan teknologi WebAR ini signifikan (F = 6.583; p < 0.001). Sikap Pengguna (ATU) menjadi variabel kunci yang berpengaruh signifikan terhadap Niat Penggunaan (BI) (β=0.429; p=0.001), sementara Kemudahan Penggunaan (PEOU) dan Manfaat (PU) memengaruhi BI secara tidak langsung melalui ATU. Sebagai validasi tambahan, uji klasifikasi menghasilkan akurasi 88,90% dan F1-score 0,941, yang menegaskan bahwa WebAR berbasis Kode QR efektif dan dapat diterima dengan baik sebagai media informasi dan promosi digital kearifan lokal di wilayah perbatasan. Kata Kunci: daerah perbatasan; kearifan lokal; qr code; web augmented reality.

EVALUATION OF HYBRID MOVIE RECOMMENDATION SYSTEM BASED ON NEURAL NETWORKS

Widjaja, William, Robert, Johanes Terang Kita Perangin - Angin
Abstract: Abstract: Recommendation systems are becoming increasingly important with the growth of streaming platforms. The purpose of this study is to compare the performance of Content-Based Filtering, Neural Collaborative Filtering,&#8230; ing, and a combination of both in a movie recommendation system. The method used in this study involves retrieving movie details from the TMDB API and ratings from the MovieLens 32M Dataset (2010-2023). Each model's performance is evaluated using evaluation metrics such as RMSE and MAE. The results of this study indicate that Neural Collaborative Filtering achieves the best prediction performance (RMSE = 0.785423, MAE = 0.581262), followed by the hybrid model (RMSE = 0.800863, MAE = 0.660872), while Content-Based Filtering produces low performance and limits the capabilities of the hybrid model. In conclusion, these findings highlight the superiority of latent feature-based models such as NCF that learn directly from user interaction patterns over content-based approaches in the context of modern recommendation systems. Keywords: content-based filtering; hybrid filtering; movie recommendation; neural collaborative filtering.   Abstrak: Sistem rekomendasi menjadi semakin penting seiring berkembangnya platform streaming. Tujuan dari penelitian ini adalah membandingkan kinerja Content-Based Filtering, Neural Collaborative Filtering dan kombinasi keduanya dalam sistem rekomendasi film. Metode yang digunakan dalam penelitian ini melibatkan pengambilan detail film dari TMDB API dan rating dari dataset MovieLens 32M Dataset (2010-2023). Setiap peforma model dievaluasi dengan menggunakan metrik evaluasi seperti RMSE dan MAE. Hasil dari penelitian ini menunjukkan bahwa Neural Collaborative Filtering mencapai kinerja prediksi terbaik (RMSE = 0.785423, MAE = 0.581262), diikuti oleh model hybrid (RMSE = 0.800863, MAE = 0.660872), sementara Content-Based Filtering menghasilkankan peforma yang rendah dan membatasi kemampuan model hybrid. Kesimpulannya, penelitian ini menyoroti superiotas model berbasis latent feature seperti NCF yang belajar langsung dari pola interaksi pengguna dibandingkan pendekatan berbasis konten dalam konteks sistem rekomendasi modern. Kata kunci: content-based filtering; hybrid filtering; neural collaborative filtering; rekomendasi film.