The Tabita Women's Association (PW) faces obstacles in determining objective criteria in determining community members affected by Covid-19 for social assistance to be distributed so that they are right on target. This is due to the absence of a systematic and measurable system in determining which citizens are eligible as recipients of social assistance. To help PW Tabita, it is necessary to establish a system capable of providing output recommendations for the selection of the most appropriate community members as recipients of social assistance. The criteria for selecting social assistance recipients refer to the fulfillment of several elements, namely: employment status, monthly income, number of dependents, residence status, electricity tariff status, insurance participants, and PKH (Family Hope Program) participants. The Simple Multi-Attribute Rating Technique (SMART) method is a method applied in this research. The results showed that determining the appropriate weight for each criterion greatly influenced the results of the calculation of the recommendation for providing social funds for people affected by Covid-19. Then in order to obtain more accurate results, it is necessary to test the validity of the criteria to obtain more precise criteria in accordance with the eligibility needs of receiving social funds for community members affected by Covid-19 from PW Tabita.
<p><em>Penelitian ini memaparkan bagaimana menunjukkan keaslian citra digital dari tindakan klaim kepemilikan citra digital oleh pihak yang tidak bertanggung jawab. Hal tersebut dapat dilakukan dengan proses watermaking menggunakan Information Dispersal Algorithm (IDA). Untuk menjaga </em><em>kerahasiaan parameter pembangkit proses watermarking dapat dilakukan dengan proses encoding dan decoding dengan algoritma Huffman. Pembuktian keaslian citra digital ter-watermark dilakukan dengan proses deteksi dan ekstraksi watermark pada citra digital ter-watermark yang memiliki ukuran yang sama dengan citra digital asli, maupun yang telah mengalami perubahan ukuran. Citra yang telah disisipi data akan mengalami penurunan kualitas. Untuk engevaluasi </em><em>kualitas citra hasil steganografi adalah dengan penilaian secara obyektif yaitu menghitung nilai Mean Square Error (MSE) dan Peak Signal to Noise Ratio (PSNR). Dari hasil pengujian pada citra digital asli dan citra digital watermark tidak mengalami perubahan yang signifikan. Hal ini </em><em>menunjukkan bahwa perbandingan kualitas antara citra asli dan citra watermark tidak jauh berbeda. Sehingga dapat disimpulkan bahwa kualitas citra pada steganografi mengalami penurunan namun sangat kecil, atau dapat dikatakan bahwa kualitas citra tetap baik.</em></p>
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