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All Journal Jurnal Ilmiah Mahasiswa Pendidikan Biologi International Journal of Disaster Management
Zahrina Zahrina
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Humanities Biochemistry, Genetics & Molecular Biology Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Environmental Science Social Sciences

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Studi Morfologi Serbuk Sari Enam Anggota Familia Rubiaceae Zahrina Zahrina; Hasanuddin Hasanuddin; Wardiah Wardiah
Jurnal Ilmiah Mahasiswa Pendidikan Biologi Vol 2, No 1 (2017): Pebruari 2017
Publisher : Jurnal Ilmiah Mahasiswa Pendidikan Biologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (516.812 KB)

Abstract

AbstractThe aim of this study is to determine the pollen morphology of six species of familia Rubiaceae. The approach used in this study is a qualitative approach. This type of research is non-experimental by using descriptive method. Data was collected using acetolysis method. Data was analyzed descriptively. The results showed that the pollen unit of six species of familia Rubiaceae all have monad types. Shape of pollen can be divided into prolate spheroidal, subprolate, and prolate. Morinda citrifolia L. and Hedyotis corymbosa L.Lamk. included into prolate spheroidal. Ixora paludosa Kurz., Gardenia augusta Merr., Mussaenda frondosa L. included into subprolate. Coffea arabica L. included into prolate. The size of pollen can be divided into perminuta and minuta-. Hedyotis corymbosa L.Lamk., Coffea arabica L., and Ixora paludosa Kurz. included into perminuta. Morinda citrifolia L., Gardenia augusta Merr., and Mussaenda frondosa L. included into minuta-. Aperture type can be divided into inapertura, tricolporate, and monocolpate. Hedyotis corymbosa L.Lamk. included into inapertura. Coffea arabica L., Ixora paludosa Kurz., Morinda citrifolia L., Gardenia augusta Merr. included into tricolporate. Mussaenda frondosa L. included into monocolpate. Sculpture or exin ornamentation can be divided into scabrat type and reticulate type. Morinda citrifolia L. and Coffea arabica L. included into scabrat. Gardenia augusta Merr., Mussaenda frondosa L., Hedyotis corymbosa L.Lamk., and Ixora paludosa Kurz. included into reticulate. The conclusion of the study indicated that the pollen unit of six species of familia Rubiaceae have the same type, that is called as monad. The shape, size, aperture and sculpture of pollen is varies.Keywords: pollen, morphology, rubiaceae
Integration of machine learning and climate data for enhanced dengue hemorrhagic fever (DHF) prediction: A case study in Banda Aceh Rizka Puspitasari; Connie Cai Ru Gan; Muhammad Yani; Zahrina Zahrina; Taufik Fuadi Abidin
International Journal of Disaster Management Vol 8, No 2 (2025)
Publisher : TDMRC, Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/ijdm.v8i2.47069

Abstract

The increasing impact of climate change, including rising average temperatures and altered precipitation patterns, has led to changes in the prevalence and distribution of climate-sensitive diseases (CSDs), such as Dengue Hemorrhagic Fever (DHF). DHF remains a significant public health concern in Indonesia, particularly in Banda Aceh, due to its high incidence. The burden on healthcare systems is substantial, contributing to increased morbidity and mortality, especially among vulnerable populations. This study aimed to integrate climate data with machine learning methods to develop predictive models for DHF incidence. Data from 2010 to 2023 included DHF case counts and monthly climate variables such as humidity, rainfall, temperature, and wind speed. The predictive models employed Gradient Boosting, Support Vector Regression (SVR), Random Forest, and Linear Regression algorithms. Model performance was evaluated by comparing prediction accuracy using Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) metrics. The results demonstrated that the Linear Regression model predicted monthly DHF incidence with greater accuracy than the other models, as indicated by lower MAE and RMSE values. These findings suggest that integrating climate data with machine learning provides an effective tool for early warning systems for DHF, supporting public health planning and interventions in Banda Aceh City, particularly in anticipation of an increase in DHF cases.
Co-Authors Connie Cai Ru Gan Hasanuddin Hasanuddin Muhammad Yani Rizka Puspitasari Taufik Fuadi Abidin Wardiah Wardiah