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Purpose – This paper aims to detect or identify the presence of hydrocarbon infiltration on sampling point in the Rambe River area according to the obtained VOCs and the adsorbed SVOCs.

Design/Methodology/Approach – The Gore-sorber method has been used to capture volatile organic compounds (VOCs) and semi-volatile organic compounds (SVOCs) as indicators of subsurface hydrocarbon generation and entrapment. This method is usually used in environmental surveys for the oil investigations in certain areas for surface survey screening, designed to collect a broad range of VOCs and (SVOCs) at lower concentrations, quickly and inexpensively. The results also indicated a general correlation between the GORE-SORBER and reference method data. The research was conducted in Rambe River Village, Tebing Tinggi sub-district of Tanjung Jabung Barat district, Jambi Province Indonesia. The collection of the Gore-Sorber modules were analyzed using a gas chromatography-mass spectrometer thermal desorption (GC/MS).

Findings – The results showed that from all sampling points in Tebing Tinggi areas, the dominant components detected are carbonyl sulphide, dimethyl sulfide, ethane, propane, butane, 2-methyl butane, pentane, and carbon sulfide with carbon chain in the range C2-C5. These hydrocarbon gases (C1-C4) which may be from thermogenic or microbial processes. The highest concentrations of carbonyl sulfide were 392.67 ng and dimethyl disulfide 261.90 ng.

Originality/Value – In addition to estimate and predict the petroleum formation, this article provides information about the presence of oil fields in the area of the Sungai Rambe Village

Purpose – The purpose of this study is to explore the concept of spatial modeling in adolescent and under-five children’s nutritional status.

Design/Methodology/Approach – The indicator used to identify spatial autocorrelation is the Local Indicator of Spatial Association (LISA). LISA is a method of exploratory analysis of spatial data capable of detecting spatial relationships at the local level and its effects globally. Aplication of stochastic modeling in spatial nutrition identification mapping can be categorized into two cases based on spatial autocorrelation and non-spatial autocorrelation.

Findings – This results of this study indicate that there is no spatial autocorrelation in the adolescent nutritional dataset. The thematic map for anemia showed that that the highest number of anemia in adolescents was in KutaAlam sub-districts (48 people). Sub-districts that were second most common were Meuraxa, Jaya Baru, and Baiturrahman sub-districts. The fewest cases were found in Lueng Bata sub-district (12 people). There were no sub-districts affected by neighboring areas, in the case of adolescents’ anemia in Banda Aceh. For the under-five nutritional data set, it shows that there are four factors that significantly affect spatial influence, which are malnutrition, chronic energy deficiency, woman of child-bearing age, proportion of family planning, percentage of households with PHBS and coverage of access to clean water.

Research Limitations/Implications – Anemia data were obtained with a school-based survey. Household survey would be better to implement in spatial analysis.

Practical Implications – The comparison of the dataset with the two methods provides a simple example to implement special autocorrelation in practice.

Social Implications – The results contribute to a much better comparison in many cases in the nutritional field.

Originality/Value – This is the initial nutritional status of adolescents in Banda Aceh.