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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Advances in Applied Sciences Jurnal Pendidikan Teknologi dan Kejuruan KARMAPATI (Kumpulan Artikel Mahasiswa Pendidikan Teknik Informatika) ISSN: 2252-9063 Techno.Com: Jurnal Teknologi Informasi Jurnal Sarjana Teknik Informatika Jurnal Informatika dan Teknik Elektro Terapan Jurnal Eksplora Informatika SINTECH (Science and Information Technology) Journal MULTINETICS Journal of Computer System and Informatics (JoSYC) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Pendidikan Sains dan Komputer Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) Journal of Artificial Intelligence and Digital Business Galuh International Journal of Community Service and Development
Ida Bagus Nyoman Pascima
Universitas Pendidikan Ganesha
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IMPLEMENTASI METODE SARIMA DALAM MEMPREDIKSI JUMLAH PELANGGARAN LALU LINTAS DI KABUPATEN BULELENG suryani, rika; Indradewi, I Gusti Ayu Agung Diatri; Pascima, Ida Bagus Nyoman
Jurnal Informatika dan Teknik Elektro Terapan Vol. 14 No. 1 (2026)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v14i1.8827

Abstract

Penelitian ini bertujuan untuk membangun model peramalan jumlah pelanggaran lalu lintas di Kabupaten Buleleng sebagai upaya mendukung perencanaan pengawasan yang lebih proaktif. Permasalahan penelitian didasarkan pada keterbatasan pengawasan di lapangan serta belum optimalnya pemanfaatan data historis, sehingga pihak kepolisian belum memiliki gambaran prediktif mengenai tren pelanggaran di masa mendatang. Metode yang digunakan adalah Seasonal Autoregressive Integrated Moving Average, yaitu metode prediksi deret waktu yang mampu menganalisis pola tren dan musiman. Data yang digunakan berupa data bulanan jumlah pelanggaran lalu lintas periode 2019 hingga 2024. Proses penelitian dilakukan mengikuti tahapan Cross-Industry Standard Process for Data Mining yang meliputi pemahaman masalah, pemahaman data, persiapan data, pemodelan, evaluasi, dan implementasi. Hasil penelitian menunjukkan bahwa model peramalan yang dibangun menghasilkan tingkat kesalahan peramalan sebesar 24,23% serta kemampuan mengikuti arah pergerakan data aktual sebesar 54,5%. Model juga mampu menghasilkan prediksi jumlah pelanggaran untuk 12 periode ke depan.
Analisis Sentimen Penggunaan Cekat.AI dalam Menggantikan Customer Service Menggunakan Logistic Regression dan TF-IDF Ardyaputra, Gede Yudha; Pascima, Ida Bagus Nyoman; Suputra, Putu Hendra
Journal of Computer System and Informatics (JoSYC) Vol 7 No 2 (2026): February 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v7i2.9292

Abstract

The rapid development of artificial intelligence has significantly transformed customer service systems, particularly through the use of chatbots to replace human customer service agents. Cekat.AI is one of Indonesia’s local AI-based chatbot innovations that has been increasingly adopted by companies. However, its implementation has generated diverse public reactions on social media platforms, especially X and TikTok. The main problem addressed in this study is how users perceive and respond sentimentally to the use of Cekat.AI as a replacement for human customer service, as well as the underlying factors influencing these ssentiments This study aims to analyze public sentiment using the Logistic Regression method with Term Frequency–Inverse Document Frequency (TF-IDF) feature extraction on social media comments from X and TikTok. To address class imbalance in sentiment data, the Synthetic Minority Over-sampling Technique (SMOTE) was applied. The results indicate that negative sentiment dominates at 52.5%, followed by positive sentiment at 35.1% and neutral sentiment at 12.4%. The implementation of SMOTE significantly improved the Recall of the neutral class from 18.6% to 64.1%, with a cross-validation accuracy of 79.98%. Topic modeling further reveals that negative sentiment is primarily driven by automation anxiety and concerns over job displacement. These findings suggest that the main challenge in adopting Cekat.AI lies in social acceptance rather than technical performance. This study provides a dual contribution, namely technically proving the effectiveness of SMOTE in handling extreme imbalance in Indonesian text data, and practically revealing that public resistance to local AI is rooted in job displacement anxiety, not merely technical service aspects.
Perbandingan Performa LLaMA-2 dan GPT-3.5 Turbo Menggunakan Metode Retrieval Augmented Few-shot pada Analisis Sentimen I Wayan Adi Maha Wiguna; Ida Bagus Nyoman Pascima; Luh Putu Eka Damayanti
Jurnal Sarjana Teknik Informatika Vol. 14 No. 1 (2026): Februari
Publisher : Program Studi Informatika, Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jstie.v14i1.31872

Abstract

Large Language Models (LLM) memerlukan metode tambahan untuk optimasi pada tugas spesifik seperti analisis sentimen. Penelitian ini membandingkan performa GPT-3.5 Turbo dan LLaMA-2 melalui penerapan metode Retrieval Augmented Few-shot (RAFS) pada domain pariwisata, dengan skenario Zero-shot sebagai baseline. Hasil eksperimen menunjukkan bahwa LLaMA-2 mengalami peningkatan performa yang jauh lebih signifikan dibandingkan GPT-3.5 Turbo setelah penerapan RAFS. Akurasi LLaMA-2 meningkat dari 0,833 menjadi 0,862, sementara GPT-3.5 Turbo hanya meningkat tipis dari 0,851 menjadi 0,856. Perbedaan substansial terlihat pada metrik kelas minoritas; f1-score GPT-3.5 hanya naik dari 0,555 ke 0,572, sedangkan LLaMA-2 melonjak drastis dari 0,462 ke 0,676 dengan kenaikan presisi dari 0,395 ke 0,844. Secara head-to-head, LLaMA-2 terbukti sedikit lebih unggul dibanding dengan GPT-3.5 Turbo dalam menghasilkan klasifikasi yang tepat dan seimbang. Meskipun GPT-3.5 memiliki baseline awal yang lebih tinggi, LLaMA-2 menunjukkan kemampuan adaptasi dan skalabilitas yang lebih baik terhadap augmentasi konteks. Temuan ini menegaskan bahwa model open-source dengan dukungan RAFS mampu menyamai, bahkan melampaui model proprieter dalam menangani kompleksitas sentimen ulasan pelanggan.
Pengembangan Game Edukasi Mobile Sebagai Media Pendukung Peningkatan Kecerdasan Musikal Anak di Sekolah Menengah Pertama Pasaribu, Alesandro Obigael; Pascima, Ida Bagus Nyoman; Andayani, Made Susi Lissia
TIN: Terapan Informatika Nusantara Vol 6 No 9 (2026): February 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i9.9415

Abstract

This study was motivated by the suboptimal implementation of music education, particularly music notation material, in junior high schools, which has resulted in students’ low musical intelligence and the limited use of interactive technology-based learning media. This study aims to develop a mobile educational game as a learning medium to help students understand music notation and support the improvement of their musical intelligence. The method used in this study was Research and Development (R&D) with the Game Development Life Cycle (GDLC) development model, which consists of the stages of Initiation, Pre-Production, Production, Testing, Beta, and Release. The result of this study is a mobile educational game called NOMU, which has undergone validation and testing processes. The content expert validation showed a validity score of 100% with the criterion of “Highly Valid, or usable without revision,” while the media expert validation also obtained a validity score of 100% with the criterion of “Highly Valid, or usable without revision” after the refinement stage. In addition, the results of the user response test indicated a “Very Positive” qualification with a “Very Good” criterion. These results indicate that the developed mobile educational game is feasible to be used as a supporting medium for music learning and has the potential to support the improvement of students’ musical intelligence in junior high schools. The implications of this study suggest that mobile educational games can serve as innovative learning media that support the development of students’ musical intelligence and encourage the integration of digital technology in music education at the junior high school level.
Performance comparison of feature extraction methods for electroencephalogram-based recognition of Balinese script Wirawan, I Made Agus; Pascima, Ida Bagus Nyoman; Mahendra, Gede Surya; Candiasa, I Made; Sukajaya, I Nyoman
International Journal of Advances in Applied Sciences Vol 15, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i1.pp55-64

Abstract

Recognizing Balinese script from electroencephalogram (EEG) signals remains a challenging problem due to low signal amplitude, non-stationary dynamics, and significant inter-subject variability. Despite previous attempts, no single feature extraction method has been universally effective in addressing these limitations. To fill this gap, this study systematically evaluates five feature extraction techniques—differential entropy (DE), power spectral density (PSD), discrete wavelet transforms (DWT), Hjorth parameters, and statistical features—on the Balinese imagined spelling using electroencephalography (BISE) dataset, which contains EEG recordings specifically designed for Balinese script recognition. For classification, both artificial neural networks (ANN) and support vector machines (SVM) are applied, and their performance is validated across multiple experimental settings. Results demonstrate that DE consistently provides more stable and discriminative features than the other methods, achieving the highest classification accuracy when combined with ANN. These findings highlight the potential of DE-based approaches to advance electroencephalogram driven Balinese script recognition, offering a culturally significant contribution to brain-computer interface (BCI) research and supporting future applications in inclusive artificial intelligence, digital heritage preservation, and assistive technologies.
Development of Automated Essay Scoring Using Retrieval Augmented Generation in SAGE I Gusti Nyoman Sapta Wiguna; Ida Bagus Nyoman Pascima; Luh Putu Eka Damayanthi
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 5 No. 2 (2026): Mei-Juli
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v5i2.8979

Abstract

Academic assessment through essay questions is a fundamental component of the educational ecosystem designed to measure students’ cognitive depth and critical reasoning. However, manual essay grading presents significant pedagogical and administrative challenges including high susceptibility to subjective bias and an overwhelming workload for educators. To address these critical issues this research develops the Smart Automated Grading Engine or SAGE, an advanced Learning Management System engineered to automate qualitative assessments. SAGE integrates large language models via the Gemini API with a robust Retrieval Augmented Generation architecture. By strictly grounding the artificial intelligence evaluation process in teacher curated reference documents and specific grading rubrics the system effectively neutralizes the risk of information hallucination. The system was empirically validated at SMAN 1 Blahbatuh involving 180 authentic essay responses from 36 eleventh grade students. The automated assessments were statistically compared against the manual evaluations of three expert history teachers. Comprehensive technical evaluations utilizing Black Box and White Box testing confirmed the platform absolute functional stability and architectural security. Crucially the accuracy testing demonstrated exceptional pedagogical reliability where the SAGE platform achieved a Quadratic Weighted Kappa coefficient of 0.9133 categorizing its performance as having almost perfect agreement. Furthermore, the system exhibited a remarkable precision rate of 94.44 percent within a stringent 10 point score tolerance. Ultimately the integration of this technology proves to be an effective objective and efficient solution capable of replicating human evaluation sharpness while significantly alleviating educator burnout.
Implementasi Algoritma Levenshtein Distance pada Sistem Evaluasi Keterbacaan Berbasis Speech-to-Text dalam Aplikasi Literasi Multisensori untuk Anak Disleksia I Made Aris Danuarta; I Nyoman Indhi Wiradika; Ida Bagus Nyoman Pascima
KARMAPATI (Kumpulan Artikel Mahasiswa Pendidikan Teknik Informatika) Vol. 15 No. 2 (2026): [ONGOING] Karmapati Vol 15 No 2 Tahun 2026
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/karmapati.v15i2.113741

Abstract

Disleksia merupakan gangguan belajar spesifik yang menghambat kemampuan anak dalam mengenali kata secara akurat dan lancar. Salah satu kendala utama dalam intervensi literasi di Indonesia adalah keterbatasan alat bantu mandiri yang mampu memberikan umpan balik pengucapan secara real-time. Penelitian ini bertujuan untuk mengimplementasikan algoritma Levenshtein Distance pada modul Speech-to-Text (STT) sebagai sistem evaluasi keterbacaan otomatis dalam aplikasi multisensori "DyLearn". Metode pengembangan yang digunakan adalah ADDIE (Analysis, Design, Development, Implementation, Evaluation). Algoritma Levenshtein Distance diterapkan untuk menghitung jarak perbedaan antara string teks target dengan hasil transkripsi suara yang ditangkap melalui Google ML Kit STT. Sistem melakukan normalisasi teks sebelum menghitung bobot insertion, deletion, dan substitution untuk menghasilkan nilai persentase akurasi pembacaan. Pengujian sistem dilakukan melalui uji ahli isi (2 ahli, 2 tahap), uji ahli media (2 ahli, 2 tahap), uji black box (25 skenario), uji white box (16 skenario logika), dan analisis data sesi latihan STT berbasis Levenshtein Distance terhadap 90 sesi latihan membaca. Hasil menunjukkan seluruh skenario fungsional berhasil dieksekusi sesuai kriteria, dan algoritma mampu mengklasifikasikan kata dengan rata-rata akurasi 90,09% pada kondisi variasi input suara pengguna. Implementasi ini memungkinkan adanya sistem monitoring berbasis data bagi guru dan orang tua melalui web admin panel untuk memantau kemajuan literasi anak secara objektif.
Pengembangan Film Animasi 3 Dimensi Sebagai Edukasi Penangkaran Penyu dan Terumbu Karang Made Sevta Reyma Priyandika; I Gede Partha Sindu; Ida Bagus Nyoman Pascima
KARMAPATI (Kumpulan Artikel Mahasiswa Pendidikan Teknik Informatika) Vol. 15 No. 2 (2026): [ONGOING] Karmapati Vol 15 No 2 Tahun 2026
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/karmapati.v15i2.114007

Abstract

Penelitian ini bertujuan untuk mengembangkan film animasi tiga dimensi sebagai media edukasi mengenai penangkaran penyu dan pelestarian terumbu karang. Latar belakang penelitian ini didasari oleh masih rendahnya pemahaman dan kesadaran masyarakat terhadap pentingnya konservasi ekosistem laut, khususnya penyu dan terumbu karang, akibat keterbatasan media edukasi yang menarik dan interaktif. Metode penelitian yang digunakan adalah Research and Development (R&D) dengan model pengembangan Multimedia Development Life Cycle (MDLC) yang meliputi enam tahapan, yaitu Concept, Design, Material Collecting, Assembly, Testing, dan Distribution. Produk yang dihasilkan berupa film animasi tiga dimensi yang menyajikan informasi proses penangkaran penyu, pelestarian terumbu karang, serta dampak aktivitas manusia terhadap ekosistem laut. Pengujian dilakukan melalui uji ahli isi, uji ahli media, dan uji respons pengguna. Hasil pengujian menunjukkan bahwa film animasi yang dikembangkan berada pada kualifikasi sangat valid dan memperoleh respons positif dari pengguna. Dengan demikian, film animasi tiga dimensi ini dinyatakan layak digunakan sebagai media edukasi untuk meningkatkan pemahaman dan kesadaran masyarakat terhadap pentingnya konservasi penyu dan terumbu karang.
Pengembangan Aplikasi Mobile Berbasis Android untuk Pembelajaran Basita Paribasa Bali Melalui Permainan Kuis Dua Pemain (QuizDuel) I Kadek Diwa Anjapuryana; Dewa Gede Hendra Divayana; Ida Bagus Nyoman Pascima
KARMAPATI (Kumpulan Artikel Mahasiswa Pendidikan Teknik Informatika) Vol. 15 No. 2 (2026): [ONGOING] Karmapati Vol 15 No 2 Tahun 2026
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/karmapati.v15i2.114400

Abstract

Penelitian ini difokuskan pada pengembangan QuizDuel, sebuah aplikasi mobile berbasis Android yang dirancang untuk mengatasi rendahnya minat dan keterlibatan peserta didik pada mata pelajaran muatan lokal Bahasa Bali, khususnya materi Basita Paribasa Bali. Fenomena ini diidentifikasi sebagai dampak dari dominasi metode konvensional yang cenderung statis. Guna menciptakan pengalaman belajar yang dinamis, QuizDuel mengintegrasikan konsep game edukasi melalui mekanisme kuis kompetitif dua pemain secara real-time. Penelitian Research and Development (R&D) ini mengadopsi model Agile, dengan mengintegrasikan ekosistem teknologi modern meliputi framework Flutter untuk antarmuka, Laravel sebagai backend, serta Supabase untuk sinkronisasi data instan. Kualitas sistem divalidasi melalui pengujian BlackBox dan WhiteBox, serta terbukti memperoleh koefisien validitas sempurna (1,00) berpredikat “Sangat Valid” dari ahli isi dan media. Evaluasi pengalaman pengguna menggunakan instrumen User Experience Questionnaire (UEQ) terhadap 30 siswa mencetak hasil yang didominasi predikat Excellent (daya tarik 2,21; kejelasan 2,06; efisiensi 2,22; stimulasi 2,14; kebaruan 1,93) dan Good pada aspek ketepatan (1,68). Didukung oleh respons guru yang mencapai skor 49,0 (Sangat Praktis), QuizDuel dinyatakan sangat layak dan efektif diimplementasikan sebagai inovasi media interaktif yang mampu mendongkrak partisipasi aktif siswa dalam melestarikan budaya lokal melalui teknologi digital.
Co-Authors Alfiansyah Andayani, Made Susi Lissia Ardyaputra, Gede Yudha Aristamy, I Gusti Ayu Agung Mas Arya Budhi Saputra, I Made Christina Purnama Yanti Darmika, I Wayan Dewa Gede Hendra Divayana, Dewa Gede Hendra Dewi Agustini Dharsika, Eka Edi Wijaya, Ikomang Fitriani, Rani Ligar Gede Aditra Pradnyana Gede Arna Jude Saskara Gede Surya Mahendra I Dewa Made Ditha Utama P I Gede Bendesa Subawa I Gede Mahendra Darmawiguna I Gusti Ayu Agung Diatri Indradewi I Gusti Lanang Agung Raditya Putra I Gusti Lanang Agung Raditya Putra I Gusti Nyoman Sapta Wiguna I Kadek Diwa Anjapuryana I Komang Yuda Muliawan I Made Andhika Pramana Putra I Made Ardwi Pradnyana I Made Aris Danuarta I Made Candiasa I Made Edy Listartha I Made Wedana Yuda Yana, Yuda I Nengah Eka Mertayasa I Nyoman Indhi Wiradika I Nyoman Sukajaya I Putu Dedy Wira Darmawan I Wayan Adi Maha Wiguna Iswardani, Putu Risanti Kadek Ayu Ariningsih Ketut Agustini Krisnayana, I Komang Bayu Luh Putu Eka Damayanthi Luh Putu Eka Damayanti M.Cs S.Kom I Made Agus Wirawan . Made Sevta Reyma Priyandika Mertayasa , I Nengah Eka Ni Kadek Nopiani Ni Komang Tri Witari Ni Nyoman Utami Januhari Ni Wayan Risa Rahayu Saraswati Nyoman Arta Ada Nyoman Sugihartini Pasaribu, Alesandro Obigael Pramudita, Putu Dimas Putra, I Komang Apriyatama Sukarma Putri, Ni Putu Meyka Pradnya Putu Hendra Suputra Putu Riesty Masdiantini, Putu Riesty Santoso, Erlinda Shirleen Sidiq, Maulana Sindu, I Gede Partha Sukarasa, Made Dwi Supriatman, Rian Dwicahya suryani, rika Thoyyibah, Luthfiyatun Wiguna, I Wayan Adi Maha Yogantara, Ketut Manik