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All Journal International Journal of Advances in Applied Sciences Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Pendidikan Teknologi dan Kejuruan APTEKINDO KARMAPATI (Kumpulan Artikel Mahasiswa Pendidikan Teknik Informatika) ISSN: 2252-9063 Jurnal Sains dan Teknologi Jurnal Teknologi Pembelajaran Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Informatika dan Teknik Elektro Terapan CESS (Journal of Computer Engineering, System and Science) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Eksplora Informatika SINTECH (Science and Information Technology) Journal Jurnal RESISTOR (Rekayasa Sistem Komputer) WIDYA LAKSANA IJISTECH (International Journal Of Information System & Technology) Jurnal Teknologi Informasi dan Pendidikan JIKA (Jurnal Informatika) Jurnal Pendidikan Teknik Mesin Undiksha Jurnal Teknologi Informatika dan Komputer Journal of Computer Networks, Architecture and High Performance Computing Unri Conference Series: Community Engagement IJISTECH Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Ilmu Komputer Dan Informatika MASALIQ: Jurnal Pendidikan dan Sains STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer INOVTEK Polbeng - Seri Informatika
Luh Joni Erawati Dewi
Universitas Pendidikan Ganesha
Religion Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Other

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PERBANDINGAN KINERJA NAIVE BAYES DAN SVM BERBASIS SMOTE DALAM ANALISIS SENTIMEN KOMENTAR YOUTUBE MENGENAI WACANA REDENOMINASI RUPIAH Kadek Kusuma Wardana; I Gede Aris Gunadi; Luh Joni Erawati Dewi
Jurnal Pendidikan Teknologi dan Kejuruan Vol. 23 No. 2 (2026): Edisi Juli 2026
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jptk-undiksha.v23i2.118046

Abstract

Redenomination is a policy of simplifying the nominal value of a currency without changing the exchange rate or purchasing power. The discourse on rupiah redenomination has again become a public concern after the government and Bank Indonesia announced its readiness for implementation, resulting in various public responses on social media, particularly YouTube. This situation has prompted the need for sentiment analysis to accurately identify public opinion trends. This study aims to compare the performance of Naïve Bayes and Support Vector Machine (SVM) in classifying comment sentiment on the channels CNBC Indonesia, Kompas Pontianak, and Kumparan. Data imbalance was handled using the Synthetic Minority Oversampling Technique (SMOTE), while feature extraction used TF-IDF. Evaluation was carried out using accuracy, precision, recall, F1-score, ROC AUC, overfitting testing, and K-Fold Cross Validation. The results show that SMOTE improves the performance of both models. SVM yielded the best results at a 50:50 ratio, with an accuracy of 76.34%, a precision of 76.33%, a recall of 76.34%, an F1-score of 75.46%, and an ROC AUC of 81.44%. Thus, SVM was more optimal than Naïve Bayes in classifying sentiment related to the rupiah redenomination discourse.
Evaluasi Kinerja Model LSTM dalam Memprediksi Nilai Penutupan IHSG Berdasarkan Variasi Optimizer Adam-based Valensia Natalia; I Nyoman Saputra Wahyu Wijaya; Luh Joni Erawati Dewi; Ni Putu Novita Puspa Ni Putu Novita Puspa
JUKOMIKA (Jurnal Ilmu Komputer dan Informatika) Vol. 9 No. 1 (2026): July
Publisher : LPPMPP Yayasan Sejahtera Bersama Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54650/jukomika.v9i1.713

Abstract

Prediksi Indeks Harga Saham Gabungan (IHSG) merupakan tantangan tersendiri karena pergerakannya yang bersifat non-linier dan dipengaruhi berbagai faktor eksternal. Penelitian ini mengevaluasi kinerja model Long Short-Term Memory (LSTM) dalam memprediksi nilai penutupan IHSG menggunakan tiga variasi algoritma optimasi berbasis Adam, yaitu Adam, AdamW, dan Nadam. Data yang digunakan adalah data historis IHSG dari Yahoo Finance periode 2015–2025 sebanyak 2.413 data harian. Model dibangun dengan teknik sliding window berukuran 60 dan dilatih menggunakan hyperparameter yang identik pada ketiga skenario untuk memastikan objektivitas perbandingan. Evaluasi dilakukan menggunakan metrik MAE, RMSE, dan MAPE. Hasil menunjukkan bahwa optimizer Adam menghasilkan performa terbaik dengan MAE sebesar 115,0, RMSE sebesar 144,4, dan MAPE sebesar 1,63%, unggul dibandingkan Nadam (MAPE 2,71%) dan AdamW (MAPE 3,18%). Keunggulan Adam berasal dari proses konvergensi yang lebih stabil sehingga model mampu mempelajari pola historis data secara lebih optimal.
Aplikasi Perhitungan Jumlah Kunjungan Museum dengan Metode Tracking Menggunakan YOLOv8 Komang Juliana; Ketut Agus Seputra; Luh Joni Erawati Dewi
MASALIQ Vol 6 No 5 (2026): MASALIQ: Jurnal Pendidikan dan Sains
Publisher : Lembaga Yasin AlSys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/masaliq.v6i5.11733

Abstract

The number of visitors to Museum Buleleng is still counted manually using a mechanical counter, which is less efficient, less accurate, and unable to provide real-time data, particularly when several visitors arrive simultaneously. This study aimed to design, implement, and evaluate a visitor-counting application based on You Only Look Once version 8 (YOLOv8) using a tracking method. The system used a webcam as the video source, YOLOv8 to detect person objects, and object ID tracking to prevent double counting. The application was developed using Python and OpenCV with a graphical user interface designed for ease of use. Testing conducted in the Public Relations Room of the Faculty of Engineering and Vocational Education at Universitas Pendidikan Ganesha (Undiksha) showed that the system achieved an average detection accuracy of 94.7% with a processing speed of 31 FPS, while the implementation of the tracking method was able to reduce counting duplication to 2.1%. During testing, the system recorded 50 incoming visitors, consisting of 22 females and 28 males, and 42 outgoing visitors, consisting of 18 females and 24 males, indicating that eight visitors remained in the room at the end of the observation. These results show that the application is capable of automatically, accurately, and in real time counting and monitoring the number of visitors. This study provides a practical contribution to the application of computer vision technology in visitor monitoring systems and has the potential to serve as a more efficient solution than manual counting methods at Museum Buleleng.
Co-Authors A. A. Gede Yudhi Paramartha Agus Gunawan Agus Seputra I Ketut Ahmad Asroni Ahmad Asroni, Ahmad Ariana, I Wayan Arunika, Ketut Biantara, I Gede Dody Okta Daniel Kevin Alexander Dewa Gede Hendra Divayana, Dewa Gede Hendra Dewa Komang Reiki Perdana Wisnu Dharmana, I Wayan Dwipayana, I Gusti Made Surya Dwipayana, Made Krisna Gede Arya Ardivan Pratama Saputra Gede Beny Indrawan Gede Indrawan Gede Rasben Dantes Handayani Putri, Dwi Prima I Gede Aris Gunadi I Gede Eka Artha Putra I Gede Krishna Adi I Gusti Andiani Octavia I Gusti Lanang Agung Andrayuga I Gusti Putu Yada Giri I Ketut Paramarta I Ketut Purnamawan I Ketut Purnamawan I Ketut Purnamawan I Ketut Resika Arthana I Made Agus Oka Gunawan I Made Candiasa I Made Gede Sunarya I Made Suryana Dwipa I Nyoman Pasek Nugraha I Nyoman Saputra Wahyu Wijaya Indrawan, Gede Beny Junaedi, Gede Tomi Kadek Kusuma Wardana Kadek Rihendra Dantes Kadek Yota Ernanda Aryanto Kadir, Ach. Khalil Komang Juliana Komang Setemen Luh Ayu Febriasih M.T. S.T. I Wayan Sutaya . Made Santo Gitakarma Meiliana, Komang Gita Ni Ketut Kertiasih Ni Ketut Opayanti Ni Putu Kasih Sumariani Ni Putu Novita Puspa Ni Putu Novita Puspa Ni Wayan Marti Nugraha, I Gede Pradipta Adi Nugraha, I Gusti Agung Satria Ony Andewi, Putu Pradiktha, Wisnu Dwijaya Pranata, Putu Ade PRIMAYUDI, IDA BAGUS KETUT KARISMA Putra, Gede Bakti Pratama Putra, I Gede Eka Artha Putra, I Nyoman Gede Ardi Yana Putri, Kadek Utari Darma Putu Ade Pranata Putu Gede Rizky Raditya Librawan Putu Haryaka Setadewa Putu Hendra Suputra Randi Wirdana, I Gede Richo, Rolando Alex Sanjaya, I Gede Ary Suta Sari, Gusti Ayu Gita Mulya Sariyasa . Sugiantari, Kadek Feny Tamayasa, Kadek Agus Valensia Natalia Wedatama, Made Restu Wisnu Dwijaya Pradiktha Yasa, I Kadek Purnama