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All Journal Business Economic, Communication, and Social Sciences Journal (BECOSS) Engineering, Mathematics and Computer Science Journal (EMACS)
Galang Madya Putra
Politeknik Statistika STIS
Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Industrial & Manufacturing Engineering Mathematics

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Journal : engineering mathematics and computer science journal emacs

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Faktor-Faktor yang Mempengaruhi Persentase Penduduk Miskin di Indonesia Tahun 2015-2018 Menggunakan Regresi Data Panel Ian Tryaldi Halim; Annisa Putri Ramadhanty; Dewi Retno Oscarini; Galang Madya Putra; Helen Fricylya Br Tobing; Rani Nooraeni
Engineering, MAthematics and Computer Science (EMACS) Journal Vol. 2 No. 2 (2020): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v2i2.6368

Abstract

Indonesia as a country rich in natural resources has not been able to make it as a country that is free from poverty. The percentage of poor people in Indonesia is still high, is still less efficient, the government's policy in alleviating poverty. This can be seen from the increase in the human development index, gross domestic product and the number of health facilities that are not counted by reducing the percentage of the poor population. The purpose of this study is to describe the percentage of poor people in Indonesia and to analyze the factors that influence the percentage of poor people in Indonesia. This study uses panel data regression analysis using the Random Effect Model (REM) method. The results showed the regional gross domestic product and the level of openness significantly open to the percentage of Indonesia's poor population. While the human development index and the amount of health development are not significant to the percentage of poor people in Indonesia. From the results of this study, Indonesia can optimize employment opportunities that can be released so that it can improve the state of the country. This implementation is expected to increase the number of poor people in Indonesia which can be significant.
Klasifikasi Status Desa/Kelurahan DIY (Yogyakarta) Menggunakan Model Decision Tree (Studi Kasus Data Praktik Kerja Lapangan Politeknik Statistika STIS Tahun 2020) Apriliansyah Mahmud; Ana Pangestika; Annisa Putri Ramadhanty; Galang Madya Putra; Galuh Sri Natungga Dewi Susilo Putri; Rani Nooraeni
Engineering, MAthematics and Computer Science (EMACS) Journal Vol. 3 No. 1 (2021): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v3i1.6787

Abstract

Status desa/kelurahan menjadi sebuah hal yang penting guna mengetahui perkembangan pembangunan yang ada pada desa/kelurahan tersebut serta dalam melakukan evaluasi terkait kebijakan yang telah dibuat mengenai infrastruktur. Badan Pusat Statistik (BPS) telah melakukan proses klasifikasi dengan metode skoring. Oleh karena itu pada penelitian ini akan mengimplementasikan model decision tree dikarenakan indicator klasifikasi status desa/kalurahan yang digunakan BPS belum mengikuti perkembangan zaman. Dalam penelitian ini menggunakan data hasil Praktik Kerja Lapangan (PKL) Politeknik Statistika STIS tahun 2020 yang dilaksanakan di D.I.Yogyakarta. Diharapkan penelitian ini dapat menjadi metode alternatif untuk mengganti metode yang sudah ada. Hasil penelitian menunjukkan bahwa dari 438 desa/kelurahan model decision tree mampu mengklasifikasi secara benar 392 desa/kelurahan sesuai dengan status desa/kelurahan sebelumnya. Model ini memiliki tingkat kebaikan model (specificity) sebesar 90.32%, presisi model (precision) sebesar 87.5%, sensitivitas model (recall) sebesar 88.42%, serta F1 Score sebesar 87.95%.
Co-Authors Ana Pangestika Annisa Putri Ramadhanty Apriliansyah Mahmud Dewi Retno Oscarini Galuh Sri Natungga Dewi Susilo Putri Helen Fricylya Br Tobing Ian Tryaldi Halim Iqbal Mukti Pratama Nooraeni, Rani Risni Julaeni Yuhan Vivy Maharani