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All Journal El-Mujtama: Jurnal Pengabdian Masyarakat Jurnal Ilmiah Sistem Informasi
Pratama, Rangga Wahyu
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Religion Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences

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Market Day: Strategi Menumbuhkan Jiwa Kewirausahaan pada Anak di Dusun Cempaka Putih Desa Punggur Kecil Lamhot, Vannes; Pratama, Rangga Wahyu; Dimas, Dimas; Prakoso, Yudha Rizki Dwi; Jhosua Praypsworsh
El-Mujtama: Jurnal Pengabdian Masyarakat  Vol. 5 No. 6 (2025): El-Mujtama: Jurnal Pengabdian Masyarakat 
Publisher : Intitut Agama Islam Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/elmujtama.v5i6.9808

Abstract

Community service was carried out in Cempaka Putih Hamlet, Punggur Kecil Village, Kubu Raya Regency with the aim of developing an entrepreneurial spirit in children. The main problem raised was the children's lack of knowledge about entrepreneurship, both in terms of concept and practice. Entrepreneurship is not only related to economic aspects, but also trains the ability to innovate, critical thinking, cooperation, and problem-solving skills. The market day program was created to help children understand the concept of entrepreneurship, implemented with an Asset-Based Community Development (ABCD) approach that focuses on individual and community development. This program consists of delivering material on the basics of entrepreneurship and direct practice through selling activities. The results of the activity showed that market day had a positive impact on the development of children's creativity, ability to work together, development of skills, critical thinking skills, problem solving, innovation and entrepreneurial spirit. Children were more enthusiastic, creative and able to cooperate in practicing simple entrepreneurial concepts. This activity not only introduced the concept of entrepreneurship but also became a means to foster an entrepreneurial spirit from an early age.
Comparison of the Harmony Search and Gravitational Search Algorithms on a Decision Tree for Predicting Focus Levels Pratama, Rangga Wahyu; Hutabarat, Peter Tymoty
Jurnal Ilmiah Sistem Informasi Vol. 5 No. 1 (2026): January: Jurnal Ilmiah Sistem Informasi
Publisher : LPPM Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/pyk6nr81

Abstract

Tingkat kefokusan merupakan faktor penting dalam produktivitas yang dipengaruhi oleh berbagai variabel seperti durasi tidur, konsumsi kafein, dan kondisi lingkungan kerja. Decision Tree Regressor memiliki potensi untuk memprediksi tingkat kefokusan, namun performanya sangat bergantung pada konfigurasi hyperparameter yang optimal. Penelitian ini bertujuan untuk membandingkan efektivitas algoritma Harmony Search (HS) dan Gravitational Search Algorithm (GSA) dalam mengoptimalkan hyperparameter Decision Tree Regressor untuk prediksi tingkat kefokusan. Metode penelitian menggunakan Machine Learning Life-Cycle dengan dataset FocusSense yang terdiri dari 10.000 sampel dari platform Kaggle. Proses optimasi dilakukan terhadap empat hyperparameter yaitu max_depth, min_samples_split, min_samples_leaf, dan max_leaf_nodes. Model dievaluasi menggunakan tujuh metrik evaluasi meliputi MSE, MAE, R², MAPE, Max Error, MSLE, dan EVS. Hasil penelitian menunjukkan bahwa model Decision Tree Regressor yang dioptimasi dengan Harmony Search menghasilkan performa terbaik dengan nilai MSE sebesar 14,626492 (penurunan 28,00% dari baseline), R² sebesar 0,873901 (peningkatan 5,94% dari baseline), dan MSLE sebesar 0,006663 (penurunan 26,13% dari baseline). Sementara itu, model yang dioptimasi dengan GSA menghasilkan MSE sebesar 16,134090 dan R² sebesar 0,860903, yang masih lebih baik dari baseline namun di bawah performa HS. Kesimpulan penelitian ini membuktikan bahwa algoritma Harmony Search lebih efektif dibandingkan Gravitational Search Algorithm dalam mengoptimalkan hyperparameter Decision Tree Regressor untuk prediksi tingkat kefokusan, dengan peningkatan akurasi prediksi yang signifikan pada data kontinyu.
Co-Authors Dimas, Dimas Hutabarat, Peter Tymoty Jhosua Praypsworsh Lamhot, Vannes Prakoso, Yudha Rizki Dwi