Cloud-Based Processing on Data Science for Visualization

Ashari, Ahmad; Tjoa, A Min; Riasetiawan, Mardhani

doi:10.14569/ijacsa.2016.070260

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…There are several studies that discuss the linked design between datasets, the examples are Ashari [7], Deng [8] and Huuskonen and Oksanen [9]. However in this researches, the design between data sets that contain the relationship between them is not discussed.…”

Section: Literature Reviewmentioning

confidence: 99%

Linked open data for agricultural land evaluation

Fibriani,

Mardhani,

Ashari

2024

E3S Web Conf.

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The government has programs that related to food independence which can be achieved by optimizing agricultural data analysis as decision support. The analysis requires a combination of several data but these data are in different sources and formats. Linked Open Data (LOD) is the answer, it makes the interconnectedness of all data that be needed, the interconnected data can be used for the next process in land evaluation. Land evaluation has 2 activities: land characteristics, and land quality. This research focus on designing a prototype of a land evaluation system model based on linked open data. There are 12 data sources that will be used for this land evaluation. The datas are spatial data which have longitude and latitude. In addition, any 2 types of data that be used text and geojson. The linked between these attributes from many sources and was using LOD’s consept creates a relationship terminology.

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Section: Literature Reviewmentioning

confidence: 99%

Linked open data for agricultural land evaluation

Fibriani,

Mardhani,

Ashari

2024

E3S Web Conf.

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“…API is a public platform with which data is selected by users to be processed and shared in various forms. The data generated are then processed using Google Fusion for further visualization and analysis according to the focus of the study (Ashari, Tjoa, & Riasetiawan, 2016). For the record, this present study upheld psychological research ethics.…”

Section: Data Collectionmentioning

confidence: 99%

Hashtag war: 2019 Presidential election rhetoric in Indonesia

et al. 2020

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Twitter as a social media has become increasingly used, including by its use by each Presidential candidate's stronghold to launch a campaign to influence prospective voters' electoral decisions in the 2019 Presidential Election in Indonesia. One strategy used in such a campaign on Twitter was by disseminating hashtags that were expected to become trending topics on Twitter. The dissemination of these hashtags aimed to build political rhetoric that can influence prospective voters' electoral decisions. Thus, this study sought to explore the patterns of hashtags disseminated by each candidate's stronghold to build political rhetoric and find out public sentiments in the posted Twitter contents. The number of tweets with #Jokowi2Periode and #2019GantiPresiden hashtags during the period of the 2019 Indonesian presidential and vice-presidential debates that were successfully downloaded using MAXQDA 18.1.1 software was 92,276. The research findings revealed that the distribution pattern of the #Jokowi2Periode hashtag tended to be more scattered (decentralized) by relying on the actor's presentation and the actor's speed in responding to tweets. In contrast, the spread of the #2019GantiPresiden hashtag was more centralized by relying on communication channels on Twitter. These two distribution patterns are discussed with the perspective of cyber psychology, through cuesfiltered-in and cues-filtered-out theories.

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