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All Journal KOMPUTA : Jurnal Ilmiah Komputer dan Informatika Jurnal Informatika dan Rekayasa Komputer
Arfan Yeheskiel Mauko
Universitas Nusa Cendana
Computer Science & IT

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Steganografi Pesan Teks Terkompresi Metode Huffman Coding ke dalam Citra Digital dengan Memanfaatkan Padding pada Citra Bitmap 24 bit Yosias Reinald Bunga Nawa; Arfan Yeheskiel Mauko; Clarissa Elfira Amos Pah
Komputa : Jurnal Ilmiah Komputer dan Informatika Vol 15 No 1 (2026): Komputa : Jurnal Ilmiah Komputer dan Informatika
Publisher : Program Studi Teknik Informatika - Universitas Komputer Indonesia (UNIKOM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputa.v15i1.19856

Abstract

In the exchange of information over the Internet, message confidentiality is an important aspect because messages may be accessed by unauthorized parties. One technique used to protect message confidentiality is steganography, which conceals a message within another medium so that its existence remains unnoticed. The End of File (EoF) method is capable of preserving image quality; however, it may increase the file size after the embedding process. This study aims to address this limitation by utilizing the padding bits of 24-bit bitmap images as a message embedding medium and applying Huffman coding compression to improve storage efficiency. The system was tested using 15 text messages and 10 different 24-bit bitmap images. The results show that Huffman compression is effective for messages of certain lengths, whereas compression becomes less efficient for very short messages due to the overhead required to store the message header and Huffman code table. Fidelity testing produced an MSE value of 0 and an infinite PSNR value, indicating that the stego image is identical to the cover image because no pixel values are modified during the embedding process. This is possible because the secret data are stored in a memory area that does not contribute to the visual representation of the image. Furthermore, the embedded messages were successfully extracted and decompressed without any alteration when the stego images remained unmodified. However, robustness testing showed that the messages could not be recovered after the images were rotated by 90° or 180°, as changes in the bitmap data structure caused the loss of data stored in the padding bits.
Implementasi Sistem Pakar Pada Penyakit Kulit Menggunakan Metode Certainty Factor Rikardus Mbusa; Sebastianus Adi Santoso Mola; Arfan Yeheskiel Mauko
Jurnal Informatika Dan Rekayasa Komputer(JAKAKOM) Vol 6 No 1 (2026): JAKAKOM Vol 6 No 1 APRIL 2026
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jakakom.2026.6.1.2607

Abstract

Skin diseases in humans are disorders that affect the outermost layer of the body, characterized by symptoms such as itching, redness, and skin infections. These conditions may be caused by exposure to sunlight, viral infections, weakened immune systems, as well as the presence of fungi, bacteria, or parasites. This study aims to develop an expert system capable of diagnosing skin diseases based on the symptoms experienced by patients, using the Certainty Factor (CF) method. The Certainty Factor method itself is a technique used to measure the degree of uncertainty in knowledge-based systems, allowing for more accurate diagnostic outcomes. The system was tested using 100 test data entries encompassing various types of skin diseases, including morbus hansen, herpes zoster, contact dermatitis, tinea versicolor, tinea corporis, scabies, and psoriasis vulgaris. Each diagnosis is accompanied by a CF value that indicates the probability or confidence level. The results of the system testing showed an accuracy rate of 100%. With this optimal accuracy, the expert system is expected to serve as an early detection tool for skin diseases, providing reliable initial diagnoses and supporting treatment decision-making.
Co-Authors Clarissa Elfira Amos Pah Rikardus Mbusa Sebastianus Adi Santoso Mola Yosias Reinald Bunga Nawa