Abstract: Check-in locations on social media provide information about an individual’s location. The millions of units of data generated from these sites provide knowledge for human activity. In this research, we used a geolocation service and users’ texts posted on Twitter social media to analyze human mobility. Our research will answer the questions; what are the movement patterns of a citizen? And, how far do people travel in the city? We explore the people trajectory of 201,118 check-ins and 22,318 users over a period of one month in Makassar city, Indonesia. To accommodate individual mobility, the authors only analyze the users with check-in activity greater than 30 times. We used sampling method with a systematic sampling approach to assign the research sample. The study found that the individual movement shows a high degree of regularity and intensity in certain places. The other finding found that the average distance an urban inhabitant can travel per day is as far as 9.6 km.
Abstract: In the past decade, the social networking app has been growing very rapidly. Geolocation data is one of the important features of social media that can attach the user's location coordinate in the real world. This paper proposes the use of geolocation data from the Twitter social media application to gain knowledge about urban dynamics, especially on human mobility behavior. This paper aims to explore the relation between geolocation Twitter with the existence of people in the urban area. Firstly, the study will analyze the spread of people in the particular area, within the city using Twitter social media data. Secondly, we then match and categorize the existing place based on the same individuals visiting. Then, we combine the Twitter data from the tracking result and the questionnaire data to catch the Twitter user profile. To do that, we used the distribution frequency analysis to learn the visitors’ percentage. To validate the hypothesis, we compare it with the local population statistic data and land use mapping released by the city planning department of Makassar local government. The results show that there is the correlation between Twitter geolocation and questionnaire data. Thus, integration the Twitter data and survey data can reveal the profile of the social media users.
Abstract: Contamination of aromatic compounds in water can
cause severe long-lasting effects not only for biotic organism but also
on human health. Several alternative technologies for remediation of
polluted water have been attempted. One of these is adsorption
process of aromatic compounds by using organic modified clay
mineral. Porous structure of clay is potential properties for molecular
adsorptivity and it can be increased by immobilizing hydrophobic
structure to attract organic compounds. In this work natural
montmorillonite were modified with cetyltrimethylammonium
(CTMA+) and was evaluated for use as adsorbents of aromatic
compounds: benzene, toluene, and 2-chloro phenol in its single and
multicomponent solution by ethanol:water solvent. Preparation of
CTMA-montmorillonite was conducted by simple ion exchange
procedure and characterization was conducted by using x-day
diffraction (XRD), Fourier-transform infra red (FTIR) and gas
sorption analysis. The influence of structural modification of
montmorillonite on its adsorption capacity and adsorption affinity of
organic compound were studied. It was shown that adsorptivity of
montmorillonite was increased by modification associated with
arrangements of CTMA+ in the structure even the specific surface
area of modified montmorillonite was lower than raw
montmorillonite. Adsorption rate indicated that material has affinity
to adsorb compound by following order: benzene> toluene > 2-chloro
phenol. The adsorption isotherms of benzene and toluene showed 1st
order adsorption kinetic indicating a partition phenomenon of
compounds between the aqueous and organophilic CTMAmontmorillonite.