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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Teknik Informatika UNIKA Santo Thomas Jurnal Mantik Brilliance: Research of Artificial Intelligence Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Digital Transformation Technology (Digitech) INCOME: Indonesian Journal of Community Service and Engagement
Anisyah, Ani
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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Pengembangan Sistem Logging Peminjaman Fasilitas dengan Perekaman User Behaviour Menggunakan MongoDB Mi'raj, Rafi Arsalan; Anisyah, Ani; Sukamto, Rosa Ariani
Digital Transformation Technology Vol. 5 No. 1 (2025): Periode Maret 2025
Publisher : Information Technology and Science(ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/digitech.v5i1.6488

Abstract

Penelitian ini bertujuan membangun sistem logging yang mampu merekam aktivitas pengguna secara detail untuk dianalisis dalam mengungkap pola penggunaan aplikasi peminjaman fasilitas. Sistem dikembangkan melalui tiga tahapan utama, yaitu analisis kebutuhan, perancangan arsitektur sistem menggunakan MongoDB sebagai database NoSQL, serta implementasi API backend berbasis Django dan frontend dengan JavaScript untuk menangkap data interaksi pengguna secara real-time. Data yang dikumpulkan meliputi aktivitas seperti waktu login, navigasi halaman, frekuensi penggunaan fitur, pencarian kata kunci, serta proses peminjaman yang dilakukan oleh pengguna. Hasil analisis menunjukkan bahwa pengguna lama memiliki pola navigasi yang lebih efisien dan konsisten, dengan mayoritas langsung mengakses fitur inti. Sebaliknya, pengguna baru menunjukkan variasi jalur yang lebih eksploratif, terutama dalam tahap awal penggunaan.Pada aspek durasi sesi dan jumlah aksi, kedua kelompok menunjukkan kecenderungan pada rentang 6–15 aksi per sesi dan durasi 0–5 menit. Visualisasi data seperti user path, frekuensi akses halaman, dan tren pencarian berhasil mengungkap perbedaan signifikan antara kedua kelompok pengguna. Hasil penelitian ini memberikan dasar berbasis data untuk peningkatan efisiensi antarmuka dan penyusunan strategi onboarding yang lebih tepat sasaran.
Rancang Bangun Aplikasi Pemesanan Air Isi Ulang Berbasis Android dengan Integrasi Firebase dan Location Based Service di Depot Bumi Qta Firdaus, Ayesha Ali; Munir, Munir; Anisyah, Ani
Digital Transformation Technology Vol. 5 No. 1 (2025): Periode Maret 2025
Publisher : Information Technology and Science(ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/digitech.v5i1.6567

Abstract

Transformasi digital menjadi kebutuhan penting dalam meningkatkan efisiensi layanan pada sektor usaha kecil dan menengah. Depot Bumi Qta, sebuah usaha air minum isi ulang di Kabupaten Serang, mengalami permasalahan dalam pencatatan pesanan manual yang sering menimbulkan kesalahan dan keterlambatan pengiriman. Penelitian ini bertujuan untuk membangun aplikasi pemesanan air isi ulang berbasis Android yang terintegrasi dengan Firebase, guna menggantikan proses manual dan meningkatkan kualitas layanan. Metode pengembangan yang digunakan adalah Waterfall, dengan tahapan meliputi analisis kebutuhan, perancangan, implementasi, pengujian, dan evaluasi. Firebase dimanfaatkan sebagai backend untuk penyimpanan data real-time, autentikasi pengguna, dan pengiriman notifikasi pesanan. Hasil pengujian menggunakan metode Black Box Testing menunjukkan bahwa seluruh fitur aplikasi berjalan sesuai fungsinya, sedangkan evaluasi usability menggunakan System Usability Scale (SUS) menghasilkan skor rata-rata 83,18 yang berada dalam kategori sangat baik. Kontribusi utama dari penelitian ini adalah pengembangan sistem pemesanan digital yang mampu mengurangi human error, mempercepat proses layanan, serta menyediakan pelacakan pengiriman secara real-time. Aplikasi ini terbukti layak untuk diimplementasikan pada usaha serupa dalam skala kecil hingga menengah, dan dapat menjadi acuan dalam pengembangan sistem layanan distribusi berbasis mobile lainnya.
A Dental Chatbot Based on IndoBERT with Next Sentence Prediction and Intent Classification Isya, Nadhief Athallah; Rasim, Rasim; Anisyah, Ani
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.6620

Abstract

Low public awareness regarding the importance of dental health remains a significant issue in Indonesia. This situation is exacerbated by limited access to consultation services that are easy, fast, affordable, and available at any time. As a result, many dental diseases go undetected at an early stage. Additionally, the tendency to delay dental check-ups is often caused by time constraints and the distance to healthcare facilities, leading many people to avoid consulting with dentists. To address this problem, this research developed a dental health chatbot based on Natural Language Processing (NLP) using IndoBERT. The model was pretrained with the Masked Language Model (MLM) approach and fine-tuned using Next Sentence Prediction (NSP) and intent classification tasks. The dataset was compiled from Indonesian-language dental health articles, symptom–disease sentence pairs, and follow-up questions, all validated by certified dentists. The system was implemented as a web application using React JS for the frontend, Express JS and MySQL for the backend, and integrated with the NLP model through a Flask API. Evaluation results show that the chatbot can provide relevant dental health information, including lightweight consultations to assist in early symptom detection, answer follow-up questions, and generate digital medical records. Expert validation produced an average score of “Good” across the aspects of clarity, relevance, medical accuracy, and completeness, with Likert scale scores ranging from 3.53 to 3.67. This research is expected to contribute as an accessible 24-hour online dental health information service aimed at increasing public knowledge and awareness.
Perancangan Dashboard Interaktif Untuk Mengoptimalisasi Analisis Hasil Audit Mutu Internal (AMI) Dengan Metode Pureshare Bahtiar, Muhammad Yusuf; Wahyudin, Asep; Anisyah, Ani
Jurnal Komputer Teknologi Informasi Sistem Informasi (JUKTISI) Vol. 4 No. 2 (2025): September 2025
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v4i2.550

Abstract

Pendidikan tinggi memainkan peran penting dalam dinamika global saat ini, perlu adanya kesinambungan dan peningkatan kualitas melalui penjaminan mutu sesuai dengan standar yang ditetapkan. Meskipun pelaporan Audit Mutu Internal (AMI) telah terdigitalisasi, tahap analisisnya masih menjadi kendala. Pimpinan program studi kesulitan menginterpretasi data audit yang tersaji dalam format tabel statis, sehingga menyulitkan dalam identifikasi tren, perbandingan kinerja, dan pengambilan keputusan taktis berbasis data. Penelitian ini bertujuan untuk merancang sebuah dashboard yang berfokus pada visualisasi dan analisis untuk mengoptimalkan pemahaman terhadap hasil temuan AMI. Perancangan dashboard dilakukan menggunakan metode PureShare yang mengintegrasikan pendekatan top-down dan bottom-up untuk memastikan keselarasan antara kebutuhan pengguna dan fungsionalitas sistem, sedangkan untuk mengevaluasi fungsionalitas sistem digunakan metode Black-Box. Hasil penelitian menunjukkan bahwa dashboard yang dikembangkan berhasil mentransformasi data statis menjadi visualisasi interaktif yang informatif, dilengkapi fitur drill-down, kustomisasi grafik, dan filter tahun. Fitur inovatif “Generate Analisis” berbasis Large Language Model (LLM) juga terbukti efektif dalam mempercepat interpretasi data menjadi wawasan strategis yang bermanfaat. Hasil pengujian black-box mengonfirmasi bahwa seluruh fungsionalitas utama berjalan sesuai harapan tanpa adanya error kritis. Dapat disimpulkan bahwa implementasi dashboard dengan metode PureShare berhasil menyediakan solusi yang fungsional dan relevan untuk mendukung pengambilan keputusan yang lebih efisien berbasis data.
Development of an Academic Services Chatbot Based on Retrieval-Augmented Generation (RAG) Husain, Mohammad Labib; Wibisono, Yudi; Anisyah, Ani
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.6719

Abstract

Higher education institutions struggle to provide accurate and accessible academic information. Traditional chatbots are often limited in capability, while standard Large Language Models (LLMs) pose a significant risk of factual "hallucinations," rendering them unsuitable for official university use where trustworthiness is paramount. This study aims to increase the accessibility and effectiveness of academic services by developing a trustworthy chatbot. The primary objective is to implement the Retrieval-Augmented Generation framework to create a reliable AI assistant that is factually grounded in a verified, domain-specific knowledge base. A knowledge base was constructed from official FPMIPA UPI documents and structured using hierarchical chunking. The system employs a multi-stage RAG pipeline featuring query contextualization and reranking before generation with Gemini 2.5 Pro. Performance was evaluated using metrics from the RAGAS framework on a 100-question dataset categorized into factual, reasoning, and out-of-context queries. The evaluation revealed strong performance on factual queries, achieving a Faithfulness score of 0.9100. A significant performance decrease was observed for reasoning tasks, with Context Recall dropping to 0.5926. Crucially, the system successfully handled 81.25% of out-of-context questions by correctly refusing to answer, thereby effectively preventing hallucination. The RAG framework provides a viable and empirically-validated blueprint for creating a trustworthy conversational AI for higher education. The model proves to be an effective tool for factual information delivery and has strong potential to modernize how student support and academic services are delivered.
Stock Price Prediction Using the ETSFormer Model Case Study: PTBA Atqiya, Muhammad Azka; Riza, Lala Septem; Anisyah, Ani
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.6729

Abstract

The capital market in Indonesia is currently experiencing very rapid development. This growth is significantly evidenced by the increasing number of investors, especially from the millennial and Gen Z demographics. However, this growing investor base also faces a major challenge: high stock price volatility. These fluctuations are triggered by various factors, ranging from domestic economic policies and global geopolitical conditions to rapidly changing market sentiment. This research aims to build a stock price prediction model for PT Bukit Asam Tbk (PTBA) using the ETSFormer architecture, a modern Transformer-based method designed for time-series data. The historical stock price data used in this study covers a five-year period from 2020 to 2025. To ensure optimal model performance, the best model was identified using the Grid Search technique to find the most effective combination of hyperparameters. The results of this study determined that the best model was achieved with the hyperparameters model dimension = 16, batch size = 16, and a learning rate = 0.01, which yielded a validation loss of 0.0074. In the evaluation phase, this model demonstrated solid performance with a MAPE score of 3.28%, an MAE of 86.76, and an RMSE of 117.2. Although the resulting model is quite good at reading long-term trend directions, observations indicate limitations in capturing short-term price volatility. This implies that the model is more suitable for strategic trend analysis than for predicting daily fluctuations.
Non-Playable Characters Based On Large Language Models For Role Playing Games (RPG) Mulyana, Ade; Wibisono, Yudi; Anisyah, Ani
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.6779

Abstract

Interactive dialogue is a central element in role-playing games (RPG), particularly those that emphasize storytelling and immersion. This study explores the development of a dynamic Non-Playable Character (NPC) system using a Large Language Model (LLM) to simulate responsive conversations in a fictional world. The objective of this research is to design an NPC dialogue system that can maintain contextual consistency with the game’s lore while adapting to player input dynamically. The method used is engineering-based development, involving prompt engineering and a Retrieval-Augmented Generation (RAG) approach to embed narrative context into the LLM prompts. The system is implemented in a 2D RPG titled Kage no Meiyaku: Shinobi no Michi, where players interact with multiple NPCs whose responses evolve based on both pre-defined lore and game progression. Evaluation is conducted using a Likert scale across four dialogue quality dimensions: coherence, emotional engagement, narrative relevance, and persona consistency. The results show that the system generates engaging and contextually accurate responses, with average scores ranging from 4.0 to 4.5. Some limitations are identified, such as occasional misspellings and generic responses in ambiguous inputs. However, the approach demonstrates strong potential for AI-assisted storytelling in games. This research contributes to expanding LLM applications in interactive fiction and opens future work toward feature-rich RPG elements such as transactional systems, branching narratives, and real-time battle interactions.
Design Blockchain Architecture for Population Data Management to Realize a Smart City in Cimahi, West Java, Indonesia Nugroho, Eddy Prasetyo; Afrianto, Irawan; Piantari, Erna; Anisyah, Ani; Al Husaeni, Dwi Novia; Bisulthon, Ibrahim Danial; Jundurrahmaan, Irham
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 9 No. 4 (2023): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i4.27493

Abstract

Smart city as a concept of city development which integrates information and communication technology with the intention of optimizing city management becomes a major goal for Indonesia, especially through the movement towards 100 Smart Cities. However, population data management is crucial in achieving this for optimal planning and management. Personal data protection becomes a crucial challenge with the rapid population growth and mobility in cities. The need for a more reliable protection system is very necessary. This research proposes a blockchain architecture that not only manages digital identities but also population data. The focus is population administration in Cimahi City, West Java, with the hope of providing security, transparency, and a strong audit trail for all population data. The contribution of this research is to design a blockchain architecture specifically for population data management, meeting the needs of population administration in cities, especially the city of Cimahi. Through a blockchain architecture development approach, this research considers the diverse administrative needs of the population and applies a blockchain model that enables data security and integrity. This implementation of blockchain architecture provides promising results in maintaining the security and integrity of population data, enabling greater transparency and auditability. This implementation of blockchain architecture provides promising results in maintaining the security and integrity of population data, enabling greater transparency and auditability. This research also shows that the use of blockchain technology specifically for population data management can be a reliable and innovative solution in ensuring the security and reliability of data important for smart city development.However, this research has limited access to central data, so the data obtained is still very limited. Therefore, further research is needed to follow up on these limitations. Apart from that, this research is also expected to provide knowledge and solutions in securing data, especially population data in government environments.
Pengembangan User Experience Website E-Marketing Dengan Metode Goal-Directed Design Pada Usaha Cokelat Cantique Kanaya, Salsabila; Siregar, Herbert; Anisyah, Ani; Kusnendar, Jajang
Digital Transformation Technology Vol. 4 No. 2 (2024): Periode September 2024
Publisher : Information Technology and Science(ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/digitech.v4i2.5043

Abstract

Strategi pemasaran berbasis website memainkan peran penting dalam meningkatkan daya saing bisnis, terutama dengan menciptakan pengalaman pengguna yang lebih baik dan meningkatkan jumlah pelanggan yang melakukan riset online sebelum membeli. Cokelat Cantique, usaha yang menawarkan produk cokelat karakter, menyadari pentingnya pengalaman pengguna yang positif dalam membangun loyalitas pelanggan. Penelitian ini bertujuan untuk mengembangkan user experience (UX) website e-marketing Cokelat Cantique dengan menggunakan metode Goal-Directed Design, guna meningkatkan UX dan memperkuat brand. Metode Goal-Directed Design mencakup 6 fase, yaitu research, modelling, requirements definition, framework definition, refinement, dan development support, yang mana pada tahap development support dilakukan validasi ahli UX untuk memastikan bahwa dengan UX sudah sesuai dengan prinsip-prinsip kegunaan dan kenyamanan pengguna dan evaluasi User Experience Questionnaire (UEQ) dan System Usability Scale (SUS) dengan 30 responden. Hasil UEQ menunjukkan bahwa keenam aspek UEQ dari website ini mendapatkan penilaian “Excellent”, dengan nilai rata-rata terendah sebesar 1,68, yaitu pada aspek novelty. Pengujian SUS mencapai skor 81 yang termasuk dalam kategori “Excellent” dan “Acceptable”. Hasil tersebut menunjukkan bahwa metode Goal-Directed Design efektif dalam menciptakan website yang memenuhi kebutuhan pengguna, meskipun perlu adanya perbaikan pada aspek novelty dan kemudahan navigasi.
Co-Authors Achmaddifa, Deffin Ade Mulyana, Ade Ahmaddifa, Deffin Al Fathin, Deva Shofa Al Husaeni, Dwi Novia Amadudin, Muhammad Nur Yasin Asep Wahyudin Atqiya, Muhammad Azka Bisulthon, Ibrahim Danial Eddy Prasetyo Nugroho Firdaus, Ayesha Ali Husain, Mohammad Labib Irawan Afrianto Isya, Nadhief Athallah Julianti, Sukma Junaeti, Enjun Jundurrahmaan, Irham Kanaya, Salsabila Kusnendar, Jajang Lala Septem Riza M. Yusuf Bahtiar, M. Yusuf Mi'raj, Rafi Arsalan Munir Munir, Munir Octaverin, Ghifari Piantari, Erna Ramadhani, Muhammad Satria Rasim, Rasim Rizky Rachman Judhie Putra Rosa Ariani Sukamto Siregar, Herbert Wibisono, Yudi Yosafat