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All Journal Jurnal Manajemen Informatika dan Sistem Informasi Jurnal Computer Science and Information Technology (CoSciTech)
Agusviyanda Agusviyanda
Institut Kesehatan Payung Negeri Pekanbaru
Computer Science & IT

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PENERAPAN METODE ANALITYCAL HIERARCHY PROCESS (AHP) PADA SISTEM PENDUKUNG KEPUTUSAN UNTUK MENETAPKAN KRITERIA KELAYAKAN PESERTA MTQ PROVINSI RIAU Agusviyanda; Anam, M Khairul; Jamaris, Muhammad; Asnal, Hadi; Hamdani
Jurnal Manajemen Informatika dan Sistem Informasi Vol. 7 No. 1 (2024): MISI Januari 2024
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/misi.v7i1.1058

Abstract

The Riau Province Quranic Recitation Development Institute (LPTQ) has the main task of assisting in nurturing prospective Quranic reciters, conducting selections, and deciding participants eligible to compete i Lembaga Pengembangan Tilawatil Quran (LPTQ) Provinsi Riau mempunyai tugas pokok membantu melaksanakan pembibitan calon tilawah hingga seleksi untuk memutuskan peserta untuk mengikuti Musabaqah Tilawatil Qur’an dilevel nasional. LPTQ secara berkala melakukan seleksi dari tingkat kabupaten dengan mempertimbangkan beberapa kriteria wajib dan kriteria pertimbangan. Selama ini keberadaan LPTQ sangat efektif namun masalah yang kemudian muncul adalah belum adanya peran teknologi dalam proses seleksi. Oleh karena itu penelitian ini memberikan solusi terkait perhitungan seleksi dengan menggunakan metode AHP. Perhitungan menggunakan metode Analytical Hierarchy Process (AHP), AHP adalah metode yang digunakan untuk mengevaluasi dan membuat keputusan dengan mempertimbangkan berbagai kriteria. Metode ini mengevaluasi alternatif berdasarkan kriteria yang berbeda, memberikan skor relatif untuk setiap alternatif. Penelitian ini melakukan pembobotan berdasarkan kriteria yaitu Waktu, Suara, Lagu, Fasahah, dan Tajwid. Setelah itu dirumuskan perankingan yang mana dapat menetukan alternatif terbaik sebagai penunjang keputusan peserta MTQ yang layak. Percobaan yang dilakukan menggunakan perwakilan dari masing-masing kabupaten dan kota yang ada di provinsi riau. Perhitungan bobot menggunakan Microsoft excel dan software Expert Choice 2000. Hasil dari penelitian ini dengan menggunakan tools yang berbeda namun hasil yang dihasilkan tetap sama. n the national-level Quranic Recitation Competition (Musabaqah Tilawatil Qur’an). Periodically, the LPTQ carries out selections at the district level, considering both mandatory criteria and additional considerations. Although the existence of LPTQ has been effective, a challenge arises due to the absence of technological involvement in the selection process. Hence, this study, titled "Implementation of the Analytical Hierarchy Process in the Decision Support System to determine eligibility criteria for participants in the Riau Province Quranic Recitation Competition," aims to assign weight values to each attribute based on the mentioned criteria. Subsequently, a ranking process will be conducted to determine the optimal alternatives in supporting the decision-making for eligible participants in the provincial-level Quranic Recitation Competition. The system is expected to assist LPTQ in making decisions on whether an individual qualifies to represent Riau at the national level.
Perbandingan Metode Learning Vector Quantization Dan Backpropagation Dalam Klasifikasi Personality Pada Anak Novita, Rita; Sujana, Teguh; Agusviyanda, Agusviyanda; Fitri, Triyani Arita; Susanti, Susanti
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

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Abstract

This research focuses on classifying children's personalities at Rumah Bermain Bilal using Artificial Neural Network algorithms, specifically Learning Vector Quantization (LVQ) and Backpropagation. The primary objective of this study is to evaluate the effectiveness of these algorithms in categorizing children's personality data and to identify the most accurate method for educational settings. The experiments were conducted with various configurations, including the number of iterations and learning rate, to assess the performance of each algorithm comprehensively. The findings show that the LVQ method demonstrates higher accuracy than Backpropagation. For training data, LVQ achieved an accuracy of 73.47%, whereas Backpropagation reached only 40.82%. For test data, LVQ achieved an accuracy of 84.62%, significantly outperforming Backpropagation's 53.85%. These results indicate that LVQ is more effective in personality classification, especially in an educational context. It is hoped that these findings will assist educational institutions in implementing artificial intelligence-based methods to understand children's personality traits better, thereby supporting the development of more targeted teaching strategies.
Co-Authors -, Teguh Sujana Anam, M Khairul Asniati Asniati Hadi Asnal, Hadi Hamdani Jamaris, Muhammad Mila Ayuni Rita Novita Susanti Susanti Triyani Arita Fitri Ulfa Hasana