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All Journal JAKPP : Jurnal Analisis Kebijakan & Pelayanan Publik BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Statistika dan Aplikasinya Jurnal Pertahanan dan Bela Negara Kompeten: Jurnal Ilmiah Ekonomi dan Bisnis Jurnal Ilmu Sosial dan Humaniora
Qorinul Huda
BPS Provinsi Lampung
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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ANALISIS SENTIMEN TWITTER TERHADAP PERLINDUNGAN DATA PRIBADI DENGAN PENDEKATAN MACHINE LEARNING Joko Ade Nursiyono; Qorinul Huda
Jurnal Pertahanan & Bela Negara Vol 13, No 1 (2023): Jurnal Pertahanan dan Bela Negara
Publisher : Indonesia Defense University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33172/jpbh.v13i1.1877

Abstract

As technology and information advances, the main defense and security aspects in the protection of personal data become very important. Protection of personal data is a human right that must be protected by the state. Data digitization is a demand and challenge in the advancement of information. Efforts in protecting personal data are basically carried out through legal certainty instruments in the form of regulations that regulate a system in order to realize a strong system in protecting cyber crime. Various regulations already exist in the legal system in Indonesia. Nevertheless, there are still cases of personal data leakage among Indonesians. The purpose of this study is to describe the condition of personal data protection in Indonesia and analyze cases of data leaks detected in Twitter tweets in the period July 1, 2021 to September 29, 2022. The study was conducted by using Twitter tweet scrapping techniques and classifying netizen responses based on positive, negative, and negative sentiments. neutral. Each sentiment is analyzed with wordcloud by finding what topics are often discussed by netizens on the protection of personal data. Furthermore, the classification evaluation is continued by looking at the accuracy of the machine learning classification algorithm, namely naive bayes and random forest. The results of the study stated that in the period from July 1, 2021 to September 29, 2022, the public's response to the protection of personal data was still negative. Which means that the data protection system in Indonesia is still not effective with the occurrence of various cases of data leakage. Based on the accuracy value, the Naive Bayes algorithm is very good at classifying tweets based on their sentiments, which is 99.84% compared to the random forest algorithm.
ECONOMIC GLOBALIZATION, ECONOMIC GROWTH, AND HUMAN CAPITAL : EMPIRICAL EVIDENCE USING THREE STAGE LEAST SQUARE IN INDONESIA Huda, Qorinul; Istiana, Nofita
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1483-1496

Abstract

The pace of globalization is increasing rapidly and dynamically as time goes by. Indonesia, located takes advantage of globalization to encourage economic growth. However, over the last decade, from 2000 to 2019, Indonesia's economic globalization index has tended to decline along with the increase in the global economic globalization index. Indonesia's economic growth has been relatively stagnant. Human capital, as the primary input in Indonesia's economic system, is suspected to be suboptimal. In the National Medium-Term Development Plan (RPJMN) for 2020-2024, economic growth and human capital are the main focus in achieving national prosperity. Human capital in this study uses health indicators as a proxy for assessing productivity and educational investment approaches. Data is transformed to meet the stationarity requirements of time series data. The study employs the Three Stage Least Square (3SLS) simultaneous equation method to examine total and direct effects. The estimation results show that changes in globalization growth are directly influenced by changes in economic growth, exchange rate growth, and inflation. Changes in economic growth are directly influenced by changes in exchange rate growth, globalization index growth, and inflation. Human capital is directly influenced by changes in globalization index growth, changes in economic growth, inflation, previous-year inflation, and changes in unemployment rates
Klasterisasi dan Perbandingan Indikator Ekonomi Makro Penentuan Upah Minimum di Jawa Tengah dan Jawa Timur Huda, Qorinul
Kompeten: Jurnal Ilmiah Ekonomi dan Bisnis Vol. 4 No. 3 (2025): November 2025
Publisher : PT Seval Literindo Kreasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57141/kompeten.v4i3.228

Abstract

Pertumbuhan ekonomi berkelanjutan merupakan salah satu tujuan suatu daerah. Pendelegasian kewenangan dalam desentralisasi menunjukkan sejauh mana keterlibatan pemerintah daerah dalam mendorong sektor-sektor ekonomi potensial di wilayahnya. Penggerak perekonomian daerah ditandai oleh berputarnya roda ekonomi dalam fungsi produksi, yaitu modal dan tenaga kerja, di mana tenaga kerja perlu mendapat perhatian untuk mencapai keseimbangan di pasar tenaga kerja yang mencerminkan tingkat pengangguran dan kesenjangan upah yang minimal. Upah perusahaan didasarkan pada upah minimum yang ditetapkan oleh pemerintah, yang pada dasarnya merupakan indikator dari situasi makroekonomi di suatu wilayah. Analisis yang dilakukan pada kabupaten dan kota di Provinsi Jawa Tengah dan Jawa Timur bertujuan untuk mengetahui apakah telah terjadi kesetaraan pada indikator-indikator penentu makroekonomi upah minimum di kedua wilayah tersebut. Hasil analisis klaster menunjukkan adanya wilayah dengan potensi tinggi, sedang, dan rendah berdasarkan pemetaan indikator makroekonomi, sementara analisis inferensi vektor menunjukkan bahwa secara agregat tidak terdapat perbedaan dalam indikator makroekonomi penentu upah minimum antara Provinsi Jawa Tengah dan Jawa Timur.
Pengembangan Pariwisata dan Tingkat Pengangguran Terbuka: Bukti Empiris dari Sepuluh Destinasi Pariwisata Nasional Indonesia Qorinul Huda; Muhammad Gozali Yahya; Setiawan Ariansyah; Ervan Nur Rahmat
Jurnal Ilmu Sosial dan Humaniora Vol. 2 No. 3 (2026): JULI-SEPTEMBER
Publisher : Indo Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63822/9r357825

Abstract

Tourism is a strategic sector expected to stimulate economic growth while reducing unemployment. However, its benefits have not been evenly distributed among local communities surrounding tourist destinations. This study examines the effect of tourism development on the Open Unemployment Rate (OUR) across ten National Tourism Destinations in Indonesia. The study employs panel data for the 2020–2023 period obtained from Statistics Indonesia (BPS) and the Directorate General of Fiscal Balance (DJPK). The analysis applies a Fixed Effects Model (FEM) estimated using the Feasible Generalized Least Squares–Seemingly Unrelated Regression (FGLS-SUR) approach. The results reveal that the number of guests and room occupancy rates in star-rated hotels have a significant negative effect on the Open Unemployment Rate, whereas the number of guests and room occupancy rates in non-star hotels, along with the proportion of government expenditure on tourism, have significant positive effects. These findings suggest that tourism development has not yet generated inclusive employment opportunities, particularly in the informal tourism sector and in the effectiveness of public spending. Therefore, tourism policies should prioritize greater local community participation, workforce capacity development, and more effective public expenditure to maximize employment creation.  
Inter Provincial Youth Human Capital Mapping and Its Implications for Economic Growth Policy in Indonesia Qorinul Huda
JAKPP (Jurnal Analisis Kebijakan & Pelayanan Publik) Volume 12 No. 1, Maret 2026
Publisher : Departemen Ilmu Administrasi FISIP UNHAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31947/jakpp.v12i1.48408

Abstract

Youth are a strategic national asset because they are of productive age, determining the direction of future economic development. This study is based on the hypothesis that the quality of youth human capital influences economic growth across provinces in Indonesia. Data are sourced from the Central Statistics Agency (BPS) in 2024, with 38 provinces as analysis units. The methods used include biplot analysis to map variations in youth human capital indicators (education, health, and employment) and multiple linear regression to examine their influence on per capita economic growth. The results show disparities in youth human capital across provinces, with Java and parts of Sumatra being relatively superior compared to eastern Indonesia. Health and employment factors have been shown to influence economic growth, while education shows a contradictory relationship due to the phenomena of skill mismatch and time lag. These findings confirm that human development, especially youth development, is a crucial foundation for achieving the 2025–2045 RPJPN targets towards an Advanced Indonesia. Mapping human capital potential allows for targeted local-scale policy mapping.
COMPARISON OF MACHINE LEARNING CLASSIFICATION ALGORITHMS IN GROUPING INCOME DISTRIBUTION INEQUALITIES IN JAVA AND BALI Qorinul Huda; Puput Budi Aji
Jurnal Statistika dan Aplikasinya Vol. 8 No. 2 (2024): Jurnal Statistika dan Aplikasinya
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.08208

Abstract

Inequality is a growing issue in several countries, both developed and developing countries. The level of state income reflected in Gross Domestic Product (GDP) cannot yet describe whether income allocation is equitable or not. High GDP is the goal of a country, but welfare is much more important. Community welfare in a country can be interpreted as how much state income is enjoyed by the community. One benchmark for whether a country's income is equally enjoyed by its people or not is through the Gini index. As industry 4.0 progresses, economic growth continues to increase. The largest share of Indonesia's GDP is on the islands of Java and Bali. Behind the rapid economic growth on the two islands, there is also inequality in income distribution. This research aims to classify districts and cities on the islands of Java and Bali based on factors that influence inequality using a data mining classification algorithm. This research uses four algorithms, namely Decision Tree, Logistic Classification, Random Forest, and Support Vector Machine (SVM). These four methods will be compared (compared) based on model evaluation, so that they are able to predict testing data for the next period in order to produce the correct regional classification. This research also accommodates handling of imbalanced data, data imputation, and forecasting using Generalized Regression Neural Network (GRNN).
Co-Authors Ervan Nur Rahmat Istiana, Nofita Joko Ade Nursiyono Muhammad Gozali Yahya Puput Budi Aji Setiawan Ariansyah