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All Journal EKONOMIKA45 The Indonesian Journal of Computer Science
Joshua Agung Nurcahyo
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Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering

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Hyperparameter Tuning Algoritma Supervised Learning untuk Klasifikasi Keluarga Penerima Bantuan Pangan Beras Joshua Agung Nurcahyo; Theopilus Bayu Sasongko
The Indonesian Journal of Computer Science Vol. 12 No. 3 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i3.3254

Abstract

Indonesia memiliki berbagai macam program untuk menekan kemiskinan, salah satunya adalah program bantuan pangan beras. Namun, berdasarkan temuan di lapangan, program bantuan ini tidak tepat sasaran. Melalui klasifikasi supervised learning dengan hyperparameter tuning, penelitian ini bertujuan untuk mengetahui algoritma klasifikasi umum yang paling optimal dan akurat dalam menentukan keluarga penerima bantuan pangan beras. Algoritma Support Vector Machine (SVM), decision tree, naïve bayes, dan K-nearest neighbor (Knn) serta metode hyperparameter tuning grid search, random search, dan optimasi bayesian digunakan dalam penelitian. Data pada penelitian ini bersumber dari IFLS. Berdasarkan hasil analisis, penerapan hyperparameter tuning memiliki dampak yang signifikan dalam meningkatkan kinerja algoritma KNN, decision tree, dan SVM. Algoritma Knn dengan random search serta optimasi bayesian dan SVM dengan optimasi bayesian memberikan nilai akurasi yang sama, yakni sebesar 74%.Oleh karena itu, model tersebut memiliki kinerja yang setara dan sama baiknya dalam mengklasifikasikan keluarga penerima bantuan pangan beras.
Pengaruh Tingkat Pendapatan Individu Berdasarkan UMP Terhadap Tingkat Kebahagiaan di Provinsi DIY Joshua Agung Nurcahyo; Hanif Rosyadah; Fitriana , Fitriana
EKONOMIKA45 :  Jurnal Ilmiah Manajemen, Ekonomi Bisnis, Kewirausahaan Vol. 11 No. 1 (2023): Desember : Jurnal Ilmiah Manajemen, Ekonomi Bisnis, Kewirausahaan
Publisher : Fakultas Ekonomi Universitas 45 Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30640/ekonomika45.v11i1.1894

Abstract

A region's level of welfare and development can be measured using subjective and objective welfare. Subjective well-being measured by taking an individual approach and paying attention to individual subjective perceptions of life; one of the measurement indicators is happiness. In the Province of DIY, there is an interesting phenomenon although per capita income and UMP are relatively low, the level of happiness is high. Based on this phenomenon, further research is needed to determine whether individual income levels based on UMP affect individual happiness in DIY. Binary logistic regression modeling using IFLS 5 data shows that individuals with incomes above the UMP tend to be happier than those below the UMP. On the other hand, the people of DIY have cultural values that teach them to accept the reality of life in order to gain happiness with sincerity. The existence of this character makes people have confidence and optimism in any condition, so they feel happy. Based on the findings of the analysis and literature review, in general, the people of DIY have a level of happiness that is classified as happy. However, if there is an increase in income, the level of happiness also tends to increase to be happier. These findings suggest that increased income can be an essential factor in increasing individual happiness. However, efforts to increase happiness focus on more than just material aspects but also involve other aspects that affect life and well-being, such as culture and personal character.
Co-Authors Fitriana , Fitriana Hanif Rosyadah Sasongko, Theopilus Bayu