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All Journal PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat JURNAL GEOGRAFIKA (GEOGRAFI LINGKUNGAN LAHAN BASAH)
Rahmi, Hendryati
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences Economics, Econometrics & Finance Law, Crime, Criminology & Criminal Justice Public Health Social Sciences

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Sigma Class: Program Pembelajaran Interaktif sebagai Upaya Pengenalan Literasi Data bagi Siswa Pendidikan Dasar: Sigma Class: An Interactive Learning Program to Introduce Data Literacy for Primary School Students Adzim, Muhammad Fauzan; Rahmi, Hendryati; Primasdali, Indah; Mahfudzi, Muhammad Ferry; Nasywani, Nur; Fatmada, Srikandi Aristawati Hanny Nur; Maisarah, Maisarah
PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Vol. 11 No. Suppl-1 (2026): PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat
Publisher : Institute for Research and Community Services Universitas Muhammadiyah Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33084/pengabdianmu.v11iSuppl-1.10966

Abstract

Primary education is the foundation for developing critical, analytical, and logical thinking skills, making early strengthening of data literacy essential to help students understand, manage, and present information meaningfully. This article examines the implementation of Sigma Class as a program to introduce data literacy through interactive learning for grade five and grade six students in Kelurahan Palam, aiming to build a basic understanding of primary and secondary data and the presentation of data in tables, bar charts, and pie charts. The program was designed as activity-based learning that combines material exposition with a data-generating game and a voting activity, supported by tutor facilitation and an individual ten-item assessment at the end of each session. The activity involved 131 students from four schools, with each meeting lasting approximately 90 minutes. Results show an overall average score of 84.89, with the highest average of 90.87 in one class and the lowest average of 76.25 in another class within the same school, and all class averages exceeding each school's minimum mastery criteria. The findings affirm the effectiveness of activity-based and game-supported approaches for introducing data literacy, while also indicating the need to strengthen prerequisite arithmetic and to differentiate instructional strategies so that outcomes become more even across classes.
Spatial Autocorrelation Analysis of Rice Production in Indonesia in 2024 Rahmi, Hendryati; Azhar, Muhammad; Indrayani, A Fahmi
Jurnal Geografika (Geografi Lingkungan Lahan Basah) Vol 6, No 2 (2025): GEOGRAFIKA
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jgp.v6i2.17030

Abstract

Rice production is an essential component of Indonesia's agricultural sector and plays a vital role in maintaining national food security. However, the distribution of rice production across provinces remains spatially uneven, influenced by differences in geography, climate, and agricultural infrastructure. This study aims to analyze the spatial autocorrelation of rice production in Indonesia and to identify regional clustering patterns based on production levels. The research employs a quantitative descriptive approach, incorporating spatial analysis methods such as Moran's I and Local Indicators of Spatial Association (LISA), utilizing GeoDa software. Data were obtained from Statistics Indonesia (BPS) and provincial administrative boundary maps. The results indicate a positive spatial autocorrelation with a Moran's I value of 0.2163 and a p-value of 0.018, implying that provinces with high production tend to be located near other high-producing provinces. High–High clusters were found in West Java, Central Java, and West Nusa Tenggara, while Low–Low clusters appeared in Papua and Maluku. Additionally, Low–High clusters were identified in Banten, East Java, and Bali, indicating provinces with relatively low production surrounded by high-producing neighbors. No High–Low clusters were detected during the observation period. These findings show that rice production in Indonesia remains spatially uneven.
Co-Authors Adzim, Muhammad Fauzan Fatmada, Srikandi Aristawati Hanny Nur Indrayani, A Fahmi Mahfudzi, Muhammad Ferry Maisarah Maisarah, Maisarah Muhammad Azhar Nasywani, Nur Primasdali, Indah