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All Journal Dinamik Semantik Techno.Com: Jurnal Teknologi Informasi Telematika : Jurnal Informatika dan Teknologi Informasi Jurnas Nasional Teknologi dan Sistem Informasi JAIS (Journal of Applied Intelligent System) Proceeding SENDI_U Journal of Information System Sistemasi: Jurnal Sistem Informasi Journal of Applied Geospatial Information Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Eksplora Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Techne : Jurnal Ilmiah Elektroteknika Jurnal Sistem Cerdas EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Jurnal Teknologi Informasi dan Terapan (J-TIT) Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Teknik Informatika (JUTIF) Journal of Applied Computer Science and Technology (JACOST) Advance Sustainable Science, Engineering and Technology (ASSET) Journal La Multiapp Community: Jurnal Pengabdian Pada Masyarakat
Ardytha Luthfiarta
Teknik Informatika S1, Fakultas Ilmu Komputer, Universitas Dian Nuswantoro
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Physics Social Sciences Other

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Evaluation of the Accuracy and Efficiency of Deep CNN Architecture in Feature Extraction for Guava Disease Classification Wicaqsana, Shiva Augusta; Luthfiarta, Ardytha; Dwi Mareta, Amalia Putri; Fitri, Maulatus Shaffira
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11655

Abstract

This study analyzes and compares several Deep Convolutional Neural Network (DCNN) architectures to evaluate the balance between classification accuracy and computational efficiency in guava fruit disease detection. A hybrid DCNN–Machine Learning (ML) approach was applied to 3,784 images from the Guava Fruit Disease Dataset using a 10-fold cross-validation scheme and undersampling techniques to address data imbalance. Six DCNN architectures were systematically tested, and the combination of ResNet50 with Artificial Neural Network (ANN) showed the best performance with an accuracy of 0.9979 and an F1-score of 0.9975, surpassing the InceptionV3 baseline (0.9974). In addition to being the most accurate, ResNet50 was also 2.5 times faster in feature extraction than DenseNet201, demonstrating an optimal balance between accuracy and time efficiency. These findings emphasize the importance of analyzing the accuracy-efficiency trade-off in selecting a DCNN architecture and open up opportunities for developing more efficient models for future agricultural image classification applications.
Analisis Komparatif Kinerja Llama Murni, Rag Native, dan Rag Fine-Tuning Desyana, Nindya; Luthfiarta, Ardytha
Jurnal Nasional Teknologi dan Sistem Informasi Vol 11 No 3 (2025): Desember 2025
Publisher : Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v11i3.2025.263-272

Abstract

Penelitian ini mengatasi masalah halusinasi pada Large Language Models (LLM) seperti LLaMA ketika menjawab kueri domain spesifik. Tujuan penelitian adalah membandingkan kinerja tiga arsitektur chatbot: LLaMA murni, Retrieval-Augmented Generation (RAG) berbasis LangChain (RAG Native), dan RAG Fine-Tuning. Implementasi RAG pada penelitian ini menggunakan framework LangChain sebagai sistem penghubung antara model LLaMA dan sumber pengetahuan eksternal (vector database). Framework ini menyediakan pipeline retriever-reader yang memungkinkan integrasi antara model bahasa dan data kontekstual melalui embedding serta pencarian vektor. Metode evaluasi dilakukan secara kuantitatif menggunakan metrik ROUGE-L dan BLEU pada dataset studi kasus. Hasil penelitian menunjukkan peningkatan kinerja yang progresif: arsitektur LLaMA murni (baseline) memperoleh skor ROUGE-L sebesar 46.48, implementasi RAG Native (LangChain) meningkat menjadi 61.42, dan model RAG Fine-Tuning (LangChain Optimized) mencapai kinerja tertinggi dengan skor 83.06. Penelitian ini menyimpulkan bahwa integrasi arsitektur RAG melalui framework LangChain secara signifikan meningkatkan akurasi respons chatbot, dan proses fine-tuning pada konfigurasi RAG merupakan langkah optimasi krusial untuk mencapai performa terbaik pada domain spesifik.
Pelatihan Pembuatan Website Pembelajaran Berbasis Google Sites Bagi Siswa SMA Mardisiswa Semarang Utomo, Danang Wahyu; Kurniawan, Defri; Luthfiarta, Ardytha; Supriyanto, Catur; Winarsih, Nurul Anisa Sri; Fitriyani, Shelomita; Salam, Abu; Dewi, Ika Novita; Rakasiwi, Sindhu
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 7 No. 1 (2026): Edisi Januari - April
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jpkmn.v7i1.8211

Abstract

Perkembangan teknologi informasi memberikan dampak positif pada literasi digital, yaitu semakin berkembang. Adanya literasi digital menjadikan proses pembelajaran interaktif. Kompetensi TIK penting bagi siswa dalam mengembangkan media pembelajaran secara digital. Namun, SMA Mardisiswa menghadapi permasalahan rendahnya kompetensi TIK siswa, yang berdampak pada kurang optimalnya pemanfaatan media pembelajaran digital. Solusi yang diusulkan adalah pelatihan berbasis learning by doing dengan menerapkan siklus Kolb’s experiential learning yang menekankan praktik langsung dalam pembelajaran. Pelatihan dilaksanakan melalui tahapan pemberian materi, praktik pembuatan website menggunakan Google Sites, serta pendampingan. Peserta kegiatan berjumlah 30 siswa kelas XII. Hasil evaluasi menunjukkan adanya peningkatan kompetensi dasar pengembangan web pembelajaran. Rata-rata nilai post-test sebesar 84 meningkat dari nilai pre-test sebesar 64, atau mengalami peningkatan 31,25%. Selain itu, siswa mampu mengembangkan media pembelajaran berbasis web secara mandiri. Metode yang diterapkan terbukti dapat meningkatkan kompetensi TIK siswa dalam pengembangan web dasar.
Comparative Analysis of Vectorization Methods for Academic Supervisor Recommendations Nabila, Qotrunnada; Luthfiarta, Ardytha; Syabilla, Mutiara; Ahmad, Azizu; Riyanto, Rozaki
Jurnal Teknologi Informasi dan Terapan Vol 11 No 2 (2024): December
Publisher : Jurusan Teknologi Informasi Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/jtit.v11i2.438

Abstract

Selecting final project supervisors often poses challenges for students due to limited lecturer quotas and difficulties in finding suitable expertise matches. This study proposes using the Cosine Similarity method with vectorization approaches such as Bidirectional Encoder Representations from Transformers (BERT), FastText, Bag of Words (BoW), Term Frequency-Inverse Document Frequency (TF-IDF), and Word2Vec to enhance the accuracy of recommendation systems. Data sourced from Google Scholar underwent scraping, preprocessing, and vectorization to evaluate the most effective method for understanding context and recommending relevant supervisors. The analysis revealed that BERT and Word2Vec based approaches achieved superior performance, delivering a perfect hit ratio (1.00) and overcoming the limitations of TF-IDF and BoW in capturing technical language. This recommendation system is expected to streamline the supervisor selection process, minimize mismatches, and effectively support academic advisory processes across educational institutions
Automatic Speech Recognition for Javanese Language using Wav2Vec 2.0 with Finetuning Setiawan, Johanes; Luthfiarta, Ardytha; Nugraha , Adhitya; Rismiyati, Rismiyati; Jessica Carmelita , Bastiaans,; Deny Novandian , Yohanes
Jurnal Nasional Teknologi dan Sistem Informasi Vol 12 No 1 (2026): April 2026
Publisher : Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v12i1.2026.1-9

Abstract

Penelitian ini bertujuan untuk mengembangkan sistem pengenalan suara untuk bahasa Jawa dengan memanfaatkan model Wav2Vec 2.0 melalui proses finetuning. Bahasa Jawa, sebagai salah satu bahasa daerah dengan lebih dari 80 juta penutur, memiliki tantangan tersendiri dalam pengenalan suara akibat keterbatasan data dan kompleksitas linguistiknya. Penelitian ini menggunakan dataset audio yang diambil dari OpenSLR dan diterapkan pada dua varian model, yaitu wav2vec2-base dan wav2vec2-large, yang masing-masing memiliki jumlah parameter 94,4 juta dan 315 juta. Proses finetuning dilakukan untuk meningkatkan akurasi sistem dalam mengenali variasi suara bahasa Jawa. Evaluasi dilakukan menggunakan metrik Word Error Rate (WER) dan evaluation loss, dengan hasil akhir menunjukkan bahwa model wav2vec2-base memiliki WER sebesar 15,02% dan model wav2vec2-large sebesar 15,57%. Hasil ini menunjukkan efektivitas pendekatan finetuning dalam meningkatkan performa pengenalan suara bahasa Jawa.
LITE-BoostTrack: A Hybrid Real-Time Multi-Object Tracking Architecture for Resource-Constrained Environments Ruri Suko Basuki; Adhitya Nugraha; Ardytha Luthfiarta; Ika Novita Dewi; Allifian Ilham Febriyana; Michael Surya Adi Prasaja; Dzawil Uqul
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 11, No. 2, May 2026
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v11i2.2478

Abstract

Multi-object tracking (MOT) is a fundamental task in computer vision that underpins applications such as intelligent surveillance, autonomous driving, and crowd analysis. The primary challenge in MOT lies in maintaining identity consistency under frequent occlusions while ensuring real-time performance on resource-constrained devices. This study proposes LITE-BoostTrack, a hybrid tracking framework that combines the confidence-based association mechanism of BoostTrack with the lightweight embedding strategy of the Lightweight Integrated Tracking and Embedding (LITE) architecture. The proposed model extracts appearance descriptors directly from the internal feature maps of the YOLOv8 detector, thereby eliminating the need for an external re-identification network. This design significantly reduces computational complexity while preserving reliable identity association. Experiments were conducted on the MOT20 benchmark using standard MOT evaluation metrics, including HOTA, MOTA, IDF1, IDSW, and FPS, to assess both tracking accuracy and runtime efficiency. The results show that LITE-BoostTrack achieves a HOTA of 27.31 and IDF1 of 37.48, outperforming LITE-BoT-SORT (HOTA 25.73, IDF1 33.88), while reducing identity switches by 37% (2,939 vs. 4,674) and maintaining real-time performance at 13.22 FPS. These outcomes demonstrate that substantial efficiency gains can be achieved through detector-level feature integration without introducing additional deep embedding modules. Although occasional failures still occur under severe occlusion, LITE-BoostTrack provides a balanced and practical solution that effectively combines accuracy and efficiency for real-time multi-object tracking in edge-computing and embedded vision systems.
Co-Authors ., Junta Zeniarza ., Junta Zeniarza Abu Salam Abu Salam Adhitya Nugraha Adhitya Nugraha Adhitya Nugraha Affandy Affandy Ahmad, Azizu Al Fahreza, Muhammad Daffa Allifian Ilham Febriyana Althoff, Mohammad Noval Aris Febriyanto Aryanti, Firda Ayu Dwi Astuti, Yani Parti Bagus Dwi Satya, Mohammad Wahyu Basiron, Halizah Cahya, Leno Dwi Catur Supriyanto Catur Supriyanto Catur Supriyanto Defri Kurniawan Deny Novandian , Yohanes Desyana, Nindya Dhita Aulia Octaviani Dwi Mareta, Amalia Putri Dzaki, Azmi Abiyyu Dzaki, Muhammad Hafizh Dzawil Uqul Edi Faisal Edi Sugiarto Egia Rosi Subhiyakto, Egia Rosi Erwin Yudi Hidayat Fahreza, Muhammad Daffa Al Fahrezi, Sahrul Fahrezi Fahrezi, Sahrul Yudha Fahri Firdausillah Fairuz Dyah Esabella Farandi, Muhammad Naufal Erza Farsya, Nabila Zibriza Fauzyah, Zahrah Asri Nur Firmansyah, Gustian Angga Fitri, Maulatus Shaffira Fitriyani, Shelomita Ganiswari, Syuhra Putri Hafiizhudin, Lutfi Azis Haresta, Alif Agsakli Harun Al Azies Hasan Shobri Heru Lestiawan Huda, Alam Muhammad Ika Novita Dewi Imam Muttaqin, Almas Najiib Indrawan, Michael Irham Ferdiansyah Katili Ivan Zuhdiansyah Jessica Carmelita , Bastiaans, Julius Immanuel Theo Krisna Junta Zeniarja Krisna, Julius Immanuel Theo Kurniawan, Defri L. Budi Handoko Leno Dwi Cahya Maharani, Zahra Nabila Mahardika, Pramesthi Qisthia Hanum Md. Mahadi Hasan, Md. Mahadi Michael Indrawan Michael Surya Adi Prasaja Muhammad Daffa Al Fahreza Muhammad Jamhari Muhammad Naufal Muhammad Rafid Mulyana, Yudha Mumtaz, Najma Amira Muttaqin, Almas Najiib Imam Nabila, Qotrunnada Nauval Dwi Primadya Nisa, Laila Rahmatin Novandian, Yohanes Deny Nugraha , Adhitya Octaviani, Dhita Aulia Primadya, Nauval Dwi Putra, Permana Langgeng Wicaksono Ellwid Putri, Ni Kadek Devi Adnyaswari Rafid, Muhammad Ramadhan Rakhmat Sani Rismiyati Rismiyati RISMIYATI RISMIYATI Riyanto, Azizu Ahmad Rozaki Riyanto, Rozaki Ruri Suko Basuki Sahrul Yudha Fahrezi Salsabila, Pramesya Mutia Satya, Mohammad Wahyu Bagus Dwi Setiawan, Dicky Setiawan, Johanes setiawan, nabila putri Sindhu Rakasiwi Soeroso, Dennis Adiwinata Irwan Sri Winarno Sri Winarno Suprayogi Suprayogi Suryaningtyas Rahayu Syabilla, Mutiara Syarifah, Ulima Muna Utomo, Danang Wahyu Wibowo Wicaksono Wibowo Wicaksono Wicaqsana, Shiva Augusta Winarsih, Nurul Anisa Sri Wulandari, Kang Andini Wulandari, Kang, Andini Zarifa, Yasmine Zuhdiansyah, Ivan