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All Journal METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Sevanam: Jurnal Pengabdian Masyarakat RIDE Sama Jiva Jnanam (International Journal of Social Studies) Jurnal Informatics Nivedita
Sanjaya, I Gede Wahyu
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Journal : Jurnal Informatics Nivedita

 1 
Analisis Kepuasan Mahasiswa Program Studi Informatika Terhadap Proses Pendidikan Kartika, Luh Gede Surya; Saskara, I Putu Adi; Pratama, Putu Adi; Utama, Putu Kussa Laksana; Sanjaya, I Gede Wahyu
Journal Informatics Nivedita Vol 1 No 1 (2024): Journal Informatics Nivedita
Publisher : Universitas Hindu Negeri I Gusti Bagus Sugriwa Denpasar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25078/nivedita.v1i1.4482

Abstract

This study aims to analyze the level of student satisfaction with learning services at the Informatics Study Program of the State Hindu University (UHN) I Gusti Bagus Sugriwa Denpasar in the Odd Semester 2023/2024. The research method used was a survey with 42 respondents from the class of 2023. Data was collected through questionnaires that included aspects of the use of learning technology, the suitability of evaluation materials with course objectives, lecturers' interpersonal relationships, student involvement in research, and lecturers' mastery of cutting-edge issues. The results of the analysis showed that the aspects of the use of media and learning technology, the suitability of exam materials/assignments with course objectives, and the ability of lecturers to interact with students obtained the highest satisfaction score (4.43) and belonged to the category of "Very Satisfied." However, the aspects of student involvement in lecturer research (4.17) and lecturer mastery of cutting-edge issues (4.18) obtained the lowest scores, even though the number means that belonged to the category “Satisfied/Good”. This study recommends increasing student involvement in research and strengthening lecturer competencies related to current issues.
Rancang Bangun Blog Berita Berbasis Laravel dan Tailwind Primayani, Sang Ayu Putu; Sanjaya, I Gede Wahyu
Journal Informatics Nivedita Vol 1 No 1 (2024): Journal Informatics Nivedita
Publisher : Universitas Hindu Negeri I Gusti Bagus Sugriwa Denpasar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25078/nivedita.v1i1.4523

Abstract

Penelitian ini bertujuan untuk merancang dan mengembangkan sebuah blog berita berbasis web yang efisien dan menarik menggunakan framework Laravel dan Tailwind CSS. Melalui pendekatan penelitian pengembangan, penelitian ini mengikuti tahapan analisis kebutuhan, perancangan sistem, pengembangan sistem, pengujian, dan evaluasi. Hasil penelitian menunjukkan bahwa blog berita yang dikembangkan berhasil memenuhi kebutuhan pengguna dan memiliki tampilan yang modern serta responsif. Penggunaan Laravel dan Tailwind CSS mempermudah proses pengembangan serta menghasilkan sistem yang fleksibel dan mudah dipelihara. Penelitian ini memberikan kontribusi dalam pengembangan sistem informasi berbasis web, khususnya dalam bidang pengembangan blog berita. Berdasarkan hasil pengujian menggunakan Black Box Testing sistem diuji menggunakan 18 butir model pengujian dan mendapatkan hasil 100% valid, hal ini menunjukkan bahwa sistem sudah berjalan dengan baik dan dapat dipublikasikan untuk digunakan secara umum.
Irrelevancy Detection in Multilingual Tourism Review Utama, Putu Kussa Laksana; Kartika, Luh Gede Surya; Pratama, I Putu Adi; Sanjaya, I Gede Wahyu; Saskara, I Putu Adi
Journal Informatics Nivedita Vol 1 No 1 (2024): Journal Informatics Nivedita
Publisher : Universitas Hindu Negeri I Gusti Bagus Sugriwa Denpasar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25078/nivedita.v1i1.4730

Abstract

This study investigates irrelevancy within multilingual tourism reviews, focusing on how off-topic or ambiguous user-generated content can undermine reliable insight for travelers. A consolidated dataset is constructed by combining a publicly available resource from Kaggle with additional posts acquired from X (formerly Twitter). Each review is manually labeled as relevant or ambiguous to capture instances where the content fails to clearly address travel or hotel-related topics. We employ a multilingual BERT embedding model to encode the diverse language inputs, enriched with a sentiment vector derived via knowledge distillation from twitter-xlm-roberta-base to DistilBERT. A gating mechanism then fuses the semantic and emotional signals, highlighting parts of each review most influenced by user attitudes. The final classification stage involves fine-tuning a BERT-based network to distinguish between unambiguous and ambiguous content. Experimental comparisons with a Monolingual BERT approach and a baseline (multilingual embedding without sentiment) reveal that incorporating sentiment features yields consistent improvements in accuracy, precision, recall, and F1-score. This outcome underscores the importance of capturing emotional cues to mitigate errors arising from partial dissatisfaction, unclear references, or cultural nuances. From a practical standpoint, the results point to potential applications in automated moderation, improved recommendation systems, and policy guidelines for tourism platforms. Overall, this work demonstrates that sentiment-aware, multilingual models can enhance detection of irrelevancy and ambiguity, fostering more trustworthy and context-rich online review ecosystems in the travel domain.
Co-Authors Agung, I Gusti Ngurah Pertu Ananda, Nyoman Anggara Putu Dharma Putra Bayu Praditya I Putu Adi Pratama I Putu Adi Pratama, I Putu Adi I Putu Adi Saskara Luh Gede Surya Kartika, Luh Gede Surya Pratama, Putu Adi Primayani, Sang Ayu Putu Putra, Anggara Putu Dharma Putu Kussa Laksana Utama, Putu Kussa Laksana Riska Mahardika Saskara, I Putu Adi Utama, I Putu Kussa Laksana Utama, Putu Kussa Laksmana