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All Journal JSIKTI (Jurnal Sistem Informasi dan Komputer Terapan Indonesia)
Widya Dharma, I Gusti Ngurah Adi
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Computer Science & IT

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Optimizing Chili Price Prediction Using Machine Learning Classification Antara, I Gede Made Yudi; Sugiartawan, Putu; Ardriani, Ni Nengah Dita; Dewa, Hari Putra Maha; Widya Dharma, I Gusti Ngurah Adi; Satya, I Putu Adnya
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 8 No 1 (2025): September
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.214

Abstract

Optimizing chili price prediction is critical for agricultural stakeholders, enabling better decision-making in supply chain management, market strategies, and farming practices. This research focuses on leveraging machine learning classification models to improve the accuracy and reliability of chili price predictions. The research addresses the challenges of class imbalance, which often occurs due to the uneven representation of price fluctuations in datasets. Resampling techniques, including oversampling the minority class with Synthetic Minority Oversampling Technique (SMOTE) and undersampling the majority class, were employed to balance the dataset and enhance the model's sensitivity to less frequent price drops. Key predictive features such as weather conditions, market demand, transportation costs, and economic indicators were integrated into the models. Advanced classification algorithms like Random Forests and Gradient Boosted Trees were utilized, demonstrating their effectiveness in handling non-linear relationships and class imbalance. Regularization techniques and k-fold cross-validation were applied to prevent overfitting and ensure robust model performance across different data subsets.The results show significant improvements in precision, recall, and overall model accuracy, making the approach suitable for real-world applications. By optimizing machine learning models, this research provides actionable insights for stakeholders to manage price volatility effectively, supporting sustainable agricultural practices and market stability.
Digitalization of Bale Beleq in Pejanggik Village Based on a 360-Degree Virtual Reality Tour Website Sandani, Rezi; Mahendra, I Gede Orka; Widya Dharma, I Gusti Ngurah Adi
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 6 No 1 (2023): September
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.263

Abstract

Cultural heritage preservation plays a vital role in maintaining local identity and historical continuity. Bale Beleq, located in Pejanggik Village, is a significant cultural landmark representing the legacy of the Sasak community in Lombok. However, the lack of digital documentation and limited accessibility hinder public engagement and threaten the sustainability of this cultural heritage. Motivated by the need to preserve and promote local traditions through technology, this research develops a digital platform integrating a website and 360° Virtual Reality (VR) tour. The system aims to provide immersive access to cultural information, enabling users to virtually explore Bale Beleq through panoramic visualization, interactive hotspots, and multimedia narration. The system was developed using the Multimedia Development Life Cycle (MDLC) method, encompassing conceptualization, design, material collection, development, testing, and distribution. Functionality testing using the Black Box method confirmed that all features—such as the virtual tour, gallery, historical descriptions, and audio guides—performed effectively according to design specifications. The evaluation showed that over 90% of users rated the system as highly engaging and informative, proving its potential as an effective medium for cultural promotion and education. Future work will focus on expanding multilingual capabilities, optimizing mobile interfaces, and integrating AI-based virtual guides to enhance interactivity and personalized learning experiences.
Co-Authors Ardriani, Ni Nengah Dita Dewa, Hari Putra Maha I Gede Made Yudi Antara Mahendra, I Gede Orka PUTU SUGIARTAWAN Sandani, Rezi Satya, I Putu Adnya