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Digitalisasi Keuangan PKK Berbasis Model Matematika untuk Akuntabilitas dan Pemberdayaan Komunitas Syifa Afidah Nurul Arifin; Rina Mayanti; Sekar Ageng Pratiwi; Irnawati Irnawati; Ahmad Taufik; Nuriza Zahra; Irfan D Andreansyah
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 8, No 5 (2025): Oktober 2025
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v8i5.9814

Abstract

Abstrak - Pemberdayaan Kesejahteraan Keluarga (PKK) adalah ruang bagi perempuan untuk saling menguatkan, belajar, dan mengelola berbagai kegiatan sosial kemasyarakatan, termasuk urusan keuangan. PKK hadir sebagai motor sosial yang berperan penting dalam pengelolaan kegiatan, termasuk urusan keuangan berbasis komunitas. Namun, sistem pencatatan kas yang masih manual menjadi hambatan tersendiri dalam menjaga akuntabilitas. Penelitian ini bertujuan mendigitalisasi sistem keuangan PKK dengan pendekatan model matematika mikro yang sederhana namun fungsional. Prototipe sistem dirancang melalui Canva, sebuah platform visual yang digunakan untuk menghasilkan website dan aplikasi interaktif yang mudah digunakan oleh pengurus PKK tanpa latar belakang teknis. Metode yang digunakan adalah metode prototype dengan tahapan identifikasi kebutuhan pengguna, perancangan, uji coba pengguna, hingga evaluasi dan revisi. Prototipe yang dihasilkan telah diuji coba kepada pengurus PKK dan mendapatkan tanggapan positif dari sisi tampilan, kemudahan penggunaan, serta penyajian data kas secara akuntabel. Hasil menunjukkan bahwa visualisasi logika keuangan seperti saldo kas, surplus-defisit, dan laporan transaksi berhasil ditampilkan dengan baik. Sistem ini berfungsi efektif sebagai media edukasi keuangan dan alat bantu meningkatkan akuntabilitas komunitas secara inklusif.Kata kunci: PKK; Digitalisasi Keuangan; Model Matematika; Akuntabilitas; Canva; Abstract - Family Empowerment Welfare (PKK) is a space for women to strengthen each other, learn, and manage various social activities in the community, including financial affairs. The PKK is present as a social motor that plays an important role in the management of activities, including community-based financial affairs. However, the manual cash recording system is an obstacle in maintaining accountability. This research aims to digitize the PKK financial system with a simple but functional micromathematics model approach. The prototype of the system was designed through Canva, a visual platform used to produce an interactive website and application, that is easy for PKK administrators to use without a technical background. The method used is a prototype method with stages of identifying user needs, designing, testing users, to evaluation and revision. The resulting prototype has been tested to PKK administrators and received positive responses in terms of appearance, ease of use, and presentation of cash data in an accountable manner. The results show that the visualization of financial logic such as cash balance, surplus-deficit, and transaction statements is successfully displayed. This system functions effectively as a financial education medium and a tool to increase community accountability inclusively.Keywords: PKK; Financial Digitalization; Mathematical Model; Accountability; Canva;
MODEL CERDAS PENGENALAN POLA WARNA MENGGUNAKAN ARSITEKTUR BAM KONTINU BERBASIS NEURAL NETWORK Sestri Novia Rizki; Vani Maharani Nasution; Ahmad Taufik
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 13, No 2 (2025): Jurnal Tikomsin, Vol 13, No.2, Oktober 2025
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v13i2.1027

Abstract

Color pattern recognition is an important field in digital image processing that has various applications, such as in object identification systems, image classification, and computer-based visual recognition. This study aims to design and implement a color pattern recognition system using Artificial Neural Networks (ANN) with the continuous Bidirectional Associative Memory (BAM) method. The continuous BAM method was chosen because of its ability to perform a bidirectional association process between input patterns and target patterns adaptively and stably. The research stages include collecting color data in RGB format, normalizing input values, forming an association matrix, training the network, and testing the system on a number of predetermined color patterns. The test results show that the continuous BAM model is able to recognize color patterns with a fairly high level of accuracy and a relatively fast convergence time. This system also shows resilience to small changes in color intensity values, so it has the potential to be applied to image recognition applications that require accurate color identification. Of the four color patterns resulting from the calculation, there are 2 patterns that match the target, namely the red and blue color patterns with the final target values [-1,1] output [-6,6] and [-1,-1] output [-6,-18].