Sainmatika: Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam

Comparison of the Morphological Structure of Pollen in Five Provenances of Gyrinops versteegii (Thymelaeaceae) in Lombok

Sukma Rukmana, Tri Mulyaningsih, Aida Muspiah — Thu, 14 Mar 2024 00:00:00 +0000

Gyrinops versteegii (Thymelaeaceae) is one of the agarwood-producing trees originating from Lombok, there are five provenances, namely Pantai, Madu, Buaya, Soyun, and Beringin. This study aims to compare the morphological structure of pollen in five provenances of G. versteegii in Lombok. The method of sampling and data analyzes were used random sampling and descriptive. Samples were taken from West Lombok: Sidemen Village (Pantai), North Lombok: Menggala Village (Buaya), Gangga Village (Beringin), Central Lombok: Taman Baru Village (Madu), and Soyun from Karang Pule Village, Mataram. The study parameters were pollen diameter and pollen morphology: shape, aperture, and sculpture. The results showed that the size of pollen from Buaya was wider than that from Madu, Beringin and Pantai. Based on the length of the polar axis/equatorial diameter, Buaya Provenance, Beringin and Pantai pollen are round in shape, and Madu Provenance is subprolate in shape. The Buaya, Madu and Beringin provenances have a monocolpate opening type, and the Periporate type for the Pantai provenance.

Binary Logistic Regression Analysis in Determining Risk Factors of Acute Respiratory Infection (IRA) on Under-Five Children

Nugraha Dethan, Faustianus Luan, Leonardus Obe — Sat, 16 Mar 2024 00:00:00 +0000

Acute Respiratory Infection (ARI) is a prevalent ailment and stands as one of the primary causes of mortality among children under the age of five. As reported by the Ministry of Health of the Republic of Indonesia, ARI predominantly affects children aged one to four years, with an incidence rate of 13.7%. Binary logistic regression is utilized to predict the likelihood of ARI occurrences in children under five, employing a linear combination of log-odds pertaining to suspected contributory factors. This study aims to evaluate the risk factors associated with ARI and develop an optimal logistic regression model by analyzing data from 166 participants who visited the Tarus regional health center between July 21 and September 1, 2023. Factors considered in this research as predictors for ARI (dependent variable ) include Immunization Status (X₁), exposure to cigarette smoke at residence (X2), exposure to wood smoke at residence (X3), exclusive breastfeeding (X4), and nutritional status (X5). The final analysis revealed that incomplete immunization, exposure to cigarette smoke, and exposure to wood smoke at residence significantly heighten the risk of ARI. The most fitting logistic model obtained was expressed as logit (π_ijk)=-1.1051+1.2297X₁+0.8709X₂+1.31085X₃.

Geographic Information System (GIS) Spatial Analysis to Detect the Distribution Pattern of Unused Land Fires at Ogan Ilir Regency

Sunarto, Kiagus Muhammad Sobri, Alfitri, Abdul Nadjib — Sun, 07 Apr 2024 00:00:00 +0000

Land fires pose a serious threat to the environment and communities in Ogan Ilir Regency, South Sumatra. This study aims to analyze the distribution pattern of land fires using GIS spatial analysis technology. Through Sentinel-2 image classification and fire intensity analysis, it had been identified focal points of dormant land fires mainly in South Indralaya, North Indralaya, and West Pemulutan sub-districts. The results of this study provide in-depth insight into the spatial distribution of land fires and the factors that influence their occurrence. This research also produced a map of the distribution of fire hotspots in unused land areas. From the research, it can be concluded that spatial analysis can map in detail and comprehensively the burning locations on unused land. The implication of this research is the need to develop more effective mitigation strategies to address the risk of land fires in the future. Therefore, this study not only makes an important contribution to the scientific literature but also offers new directions for research and policy focused on sustainable and effective land fire risk management.