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All Journal Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) JTAM (Jurnal Teori dan Aplikasi Matematika) EIGEN MATHEMATICS JOURNAL Jurnal Pengabdian Kepada Masyarakat (Mediteg) Enthusiastic : International Journal of Applied Statistics and Data Science Journal of Mathematics: Theory and Applications Jurnal Pengabdian Masyarakat Bangsa Journal of Data Science Theory and Application
Hayati MT, Ma’rufah
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Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences

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Pemanfaatan Looker Studio untuk Mengembangkan Kompetensi Analisis dan Visualisasi Data Siswa SMKS Nurul Huda Pringsewu Rosni, Rosni; Madonna, Nora; Fitriawati, Andi; Al Mahkya, Dani; Irawan, Agus; Simanjuntak, Erica Grace; Hayati, Ma’rufah; Nasrullah, Nasrullah; Irfan, Miftahul; Mahrani, Dwi; Sofia, Ayu; Yulita, Tiara; Rivai, Muklas
Jurnal Pengabdian Masyarakat Bangsa Vol. 4 No. 1 (2026): Maret
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v4i1.4194

Abstract

Kemampuan dalam memanfaatkan teknologi, khususnya dalam eksplorasi dan visualisasi data, menjadi tantangan signifikan dalam dunia pendidikan di era digital saat ini. SMKS Nurul Huda Pringsewu sebagai mitra kegiatan pengabdian menunjukkan adanya keterbatasan kompetensi siswa dalam mengolah data dan menyajikannya dalam bentuk visual yang informatif. Menanggapi permasalahan tersebut, tim Pengabdian kepada Masyarakat (PkM) melaksanakan pelatihan menggunakan aplikasi Looker Studio untuk eksplorasi data dan pembuatan dashboard statistik. Looker Studio merupakan platform berbasis web yang memudahkan pengguna dalam mengolah data numerik dan menyajikannya secara visual, sehingga proses pembacaan data tidak lagi dilakukan secara manual. Pelatihan ini bertujuan untuk meningkatkan kemampuan siswa dalam mengolah dan memvisualisasikan data menggunakan teknologi terkini. Hasil dari kegiatan ini menunjukkan peningkatan kompetensi siswa dalam mengeksplorasi data statistik serta peningkatan kualitas pembuatan dashboard yang lebih informatif dan menarik. Kegiatan ini diharapkan dapat menjadi langkah awal dalam membekali siswa dengan keterampilan digital yang relevan dengan kebutuhan industri saat ini.
Utilizing Geographically Weighted Regression with a Gaussian Kernel to Analyze Unemployment Hayati, Ma'rufah; Madonna, Nora; Simanjuntak, Erica Grace; Nikmah, Rohmatun
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 6 Issue 1, April 2026
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol6.iss1.art3

Abstract

Unemployment is a major challenge in economic development, reflecting an imbalance between labor supply and available job opportunities. This study aimed to examine the spatial variation of factors influencing the open unemployment rate (OUR) in Lampung Province, Indonesia, and to compare the performance of a global regression model with the geographically weighted regression (GWR) model in explaining these variations. The GWR method, using a fixed Gaussian kernel, was applied to capture spatial heterogeneity across regions. Secondary data were obtained from the Statistics Indonesia of Lampung Province in 2023, including economic growth (EG), human development index (HDI), and labor force participation rate (LFPR). The results showed that in the global regression model, LFPR was the only variable that significantly reduced unemployment, while EG and HDI were not statistically significant. The Breusch–Pagan test confirmed spatial heterogeneity, supporting the use of the GWR. The GWR model performed better, with Akaike information criterion (AIC) of 40.8262 and R² of 0.6059. Spatial analysis indicated that EG and HDI positively affected unemployment in several districts, suggesting limited job absorption and possible skill mismatches, whereas LFPR consistently showed a negative relationship with the open unemployment rate (OUR) across regions.
Co-Authors Agus Irawan Andi Fitriawati Anggi Desnanti Ayu Sofia Dani Al Mahkya Dwi Mahrani Febby Yuliana Sari Hudori, Mahfuz Irfan, Miftahul Madonna, Nora Mahfuz Hudori Muslim, Agus Nasrullah Nasrullah Nikmah, Rohmatun Permatasari, Reni Rahmawati Azizah Reni Permata Sari Rivai, Muklas Rosni, Rosni Sari, Reni Permata Simanjuntak, Erica Grace Tri Fatmala, Cici Utami, Sari Wardhani Utami Dewi Yuliana Dalimunthe, Desy Yulita, Tiara