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All Journal JURNAL PENDIDIKAN TAMBUSAI Justisi : Jurnal Ilmu Hukum Majalah Ilmiah METHODA
Putra, Reza Ananda
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Public Health Social Sciences

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Perancangan Game Quiz Aritmatika Menggunakan Metode Forward Chaining Berbasis Web Putra, Reza Ananda; Khairunnisa, Khairunnisa; Damayanti, Fera
Jurnal Pendidikan Tambusai Vol. 7 No. 3 (2023): Desember 2023
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jptam.v7i3.11221

Abstract

Pada studi ini peneliti membuat game quiz aritmatika berbasis web yang dapat membantu siswa dalam proses belajarnya dan membuat pembelajaran aritmatika menjadi lebih menarik dengan memanfaatkan inovasi yang semakin canggih. Yakni game quiz dimana terdapat tiga level dengan sepuluh pertanyaan per level. Level pertama meliputi penjumlahan dan pengurangan, level kedua meliputi perkalian dan pembagian, level ketiga meliputi penjumlahan, pengurangan, perkalian, dan pembagian. Game quiz ini hanya memungkinkan pengguna untuk memulai dari level satu dan membutuhkan skor minimal 70 agar bisa maju ke level berikutnya. Siswa dapat melatih kecepatan berpikir dan berhitung dengan memainkan game quiz yang tersedia di platform Google. Pendekatan forward chaining digunakan dalam perancangan game quiz ini guna menentukan jawaban benar dan salah serta untuk meningkatkan tingkat kesulitan soal. Hasil akhir aplikasi game quiz akan menunjukkan nilai, jawaban yang benar, dan rincian cara menjawab setiap pertanyaan.
SUSTAINABILITY ANALYSIS AND THE ROLE OF ENFORCEMENT LAW RELATING TO THE SILAT COLLEGE MONUMENT IN BOJONEGORO DISTRICT, EAST JAVA Putra, Reza Ananda; Handayani, Tri Astuti; Mansur, Mochamad
Justisi: Jurnal Ilmu Hukum Vol 10 No 1 (2025): Justisi: Jurnal Ilmu Hukum
Publisher : Program Studi Hukum Fakultas Hukum Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36805/jjih.v10i1.9379

Abstract

Pencak silat is a martial arts method created by the Indonesian people for protect yourself from danger. Pencak silat schools in Indonesia are synonymous with tugu universities which is the identity of a pencak silat school near the area with the symbol of a particular college. The existence of a martial arts monument can give rise to prolonged conflict between universities due to social jealousy and displeasure between other martial arts schools, to the detriment of civilians who live around the monument the martial arts. On the basis of frequent clashes due to pencak silat monuments made the governor of east java give an appeal to put in order the university monuments martial arts. Then the east java provincial government through the east java bakesbangpol issued an appeal for independently dismantle the martial arts school monument. The aim of this research is to determine the sustainability of the silat monument control program and to determine the role of law enforcement in controlling silat college monuments in Bojonegoro district, east java. The researcher used qualitative research methods with a type of empirical normative legal research.
Optimasi Algoritma Genetika pada Perbandingan ANN dan KNN untuk Klasifikasi Penyakit Jantung Zai, Andreas; Rambe, Lima Hartima; Putra, Reza Ananda; Rosnelly, Rika; Sagala, Tamado Simon; Jaya, Indra Kelana
Majalah Ilmiah METHODA Vol. 15 No. 1 (2025): Majalah Ilmiah METHODA
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methoda.Vol15No1.pp10-23

Abstract

A comparative analysis of genetic algorithm optimization methods on the performance of Artificial Neural Network (ANN) and K-Nearest Neighbor (KNN) in heart disease classification shows significant results. The research used a heart disease dataset consisting of 303 samples with 14 attributes. Genetic algorithm optimization produced substantial performance improvements in both models. The optimized ANN model achieved 94.85% accuracy, 93.00% precision, 97.00% recall, and 97.00% ROC AUC, demonstrating excellence in positive case identification. Meanwhile, the optimized KNN model achieved 93.30% accuracy, 92.00% precision, 95.00% recall, and 96.77% ROC AUC, yielding more balanced performance. The genetic algorithm optimization method proves its effectiveness in improving heart disease classification accuracy, where ANN is optimal for applications requiring high sensitivity and KNN is more stable for small datasets.
Co-Authors Fera Damayanti Indra Kelana Jaya Khairunnisa Khairunnisa Mochamad Mansur Rambe, Lima Hartima Rika Rosnelly, Rika Sagala, Tamado Simon Tri Astuti Handayani, Tri Astuti Zai, Andreas