Claim Missing Document
Check
Articles

Found 2 Documents
Search

Comparison of image enhancement methods for pratima theft detection using artificial intelligence Made Sudarma; Ni Wayan Sri Ariyani; I Putu Agus Eka Darma Udayana; Ida Bagus Gde Pranatayana; Lie Jasa
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i1.pp213-228

Abstract

The theft of pratima in Balinese temples threatens the spiritual and cultural balance of the community. These sacred objects, regarded as manifestations of God in Hinduism, hold profound religious significance, and their loss represents both material and spiritual desecration. To address this issue, this study investigates a security system that leverages image enhancement for low-light detection. Four techniques—contrast limited adaptive histogram equalization (CLAHE), adaptive histogram equalization (AHE), histogram equalization (HE), and gamma correction—were evaluated to improve image quality. CLAHE yielded the lowest mean squared error (MSE) of 21.16 and the highest peak signal-to-noise ratio (PSNR) of 38.13 dB. For object detection, VGG-19 and AlexNet were assessed. The best configuration, VGG-19 with HE, reached 83.33% accuracy and 93.75% recall, and achieved a receiver operating characteristic area under the curve (ROC AUC) of 0.90±0.02 across five runs. Thresholds derived from the ROC analysis were selected using the Youden J statistic to balance sensitivity and specificity. The approach outperformed lightweight and classical baselines in AUC, indicating superior discrimination under low illumination. These findings show that superior image quality does not always align with higher detection accuracy, and they highlight the importance of pairing effective enhancement with robust detectors for temple security. The study contributes practical insights for preserving Balinese cultural and spiritual heritage by strengthening efforts to protect pratima against theft.
Morphological Characterization and GC-MS Profiling of Tukad Sumaga Tangerine (Citrus reticulata) Sulfian Fajar; I Ketut Suada; I Nyoman Wijaya; I Gede Putu Wirawan; Ida Bagus Gde Pranatayana
Jurnal Penelitian Pendidikan IPA Vol 12 No 9 (2026)
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v12i9.14662

Abstract

Tukad Sumaga tangerine (Citrus reticulata) is a local citrus cultivar with potential as a horticultural genetic resource; however, its morphological characteristics and volatile chemical profile require systematic documentation. This study aimed to characterize the morphological traits and fruit quality of Tukad Sumaga tangerine and identify volatile compounds in its leaf extract using gas chromatography–mass spectrometry (GC-MS). Morphological characterization was conducted based on citrus descriptors, covering roots, stems, branching patterns, leaves, flowers, fruits, and seeds. Fruit quality was assessed based on total soluble solids (TSS), while leaf samples were extracted using 70% ethanol through maceration and analyzed by GC-MS. The plants exhibited a woody taproot system, upright cylindrical stem, sympodial branching with a spreading habit, ovate to elliptic glabrous leaves, actinomorphic white flowers, and ovoid to pyriform fruits with relatively rough peel surfaces. Fruit TSS reached 16 °Brix, with three to five seeds per fruit. GC-MS identified 15 compounds with similarity indices of 95–99%, including 3-hexanone, 2-hexanone, 3-hexanol, 2-hexanol, linalool, bicycloelemene, β-elemene, trans-β-caryophyllene, germacrene-D, and bicyclogermacrene. These findings provide baseline information for identification, conservation, and further investigation of Tukad Sumaga tangerine as a local citrus genetic resource