GHG Inventory on energy sector using mobile application in Surabaya City: Some challenges and opportunities

Global warming which causes climate change has a significant social economic impact. Indonesia's commitment to protecting the global climate has been a concern since the 1990s. Through Presidential Regulation No.61 of 2011 concerning the National Action Plan (RAN) for Reducing Greenhouse Gas Emission, each region needs to develop climate change mitigation actions through reducing emission or increasing the absorption of Greenhouse Gases (GHGs) from various emission sources. The formulation of climate change mitigation actions needs to be supported by greenhouse gases inventory activities and measurement of emission. Measurement of GHG emission is a cross-sectoral activity. Therefore, an information system through an electronic GHG calculator platform is needed as an instrument for measuring GHG emission that can support districts/cities to formulate the most relevant mitigation actions. This study describes the sources of GHG emission based on energy use and its measurement using GHG calculator. GHG calculator is developed based on the theoretical context and designed in form of mobile application. Using Focus Group Discussion (FGD) technique and Spearman's correlation analysis, this research aims to evaluate GHG assessment based on the use of mobile application in Surabaya City. The findings of this study are 1) there is positive feedbacks regarding the use of mobile platform to predict and calculate GHG emission. It shows that perception on easiness and usability level of mobile calculator are correlated significantly; 2) there are some opportunities and challenges in implementing mobile application for measuring GHG emission in Surabaya City

BencanaVis visualization and clustering of disaster readiness using K Means with R Shiny: A case study for Disaster, Medical Personnel and Health Facilities data at Province level in Indonesia

The open data movement has led us into immensely useful applications and innovations for decision making, both for individual citizen as well as government. This study aims to create a web application called BencanaVis which provide innovative visualization of disaster government open data using Shiny, a web framework from R programming language. The datasets being used are available from Indonesian National Disaster Management Authority agency (or BNPB), the official Indonesian Open Data government portal and the Indonesian National Statistical Bureau (or BPS) website. We create three types of scenarios or experiments for the dataset. After that, we normalize the data using min-max use normalization. Then, we employ PCA (principal component analysis) to reduce feature dimensionality. Furthermore, we apply K-Means clustering techniques and calculate the cluster validity using Sum of Square Error (SSE), Davis-Bouldin Index (DBI), Dunn Index, Connectivity Index and Silhouettes Index. The cluster member from optimal number of k are then being analyzed to create a score for disaster readiness. We shall analyze this disaster readiness using the scoring produced by weighting the attributes values with weights from the AHP methods. Furthermore, we provide two visualizations; they are 3D scatter plot and cluster distribution using leaflet library from R. There are two other visualizations provided in the web application use heatmap and streamgraph library. The heatmap visualization shows the pattern distribution of all attributes and streamgraph visualization which refers to stacked area chart shows the number of 21 types disaster which recorded from BNPB data in 16 years during the year 2000 - 2016

User acceptance of e-government citizen report system (a case study of City113 app)

The aim of this study is to understand the factors that drive what citizen's intention to use the City113 mobile application, an e-government system for citizen report. Initially, a preliminary an open-ended questions survey has been conducted to explore what factors motivate citizens to use the City113. The findings factors were compared to existing prominent technology adoption models (including TAM, DOI, UTAUT, TRA, TPB, and DTPB) and suggested the Decomposed Theory of Planned Behavior (DTPB) model with a new construct specific to gamification called playfulness is the most suitable model for representing user acceptance of the e-government citizen report application. We perform the analysis using SPSS and SmartPLS for validity and reliability test and inferential analysis for validating the model. The data were collected using questionnaire targeting citizens in 7 sub-districts of Surabaya city. The number of sample size is calculated using Slovin formula collecting 156 valid responses. This study suggests that the most significant determinant of user's intention to use the City113 mobile application is attitude (R2 = 0.435, t=5.238). There are only two factors influencing the attitude towards using the City113: Perceived Ease of Use and Perceived Usefulness. Citizens may have a positive or negative feeling towards using an e-government citizen report system mainly influenced by their perceptions on whether the system is easy to use and whether the system will deliver benefits for them or not.</p

<i>Teenstagram TimeFrame</i>: a visualization for Instagram time dataset from teen users (case study in Surabaya, Indonesia)

The aim of this study is to create Teenstagram, a visualization for online pattern activity using Instagram dataset from teen users (junior high school, 7th-9th grade) in Surabaya, Indonesia. First, an offline workshop about ethics using Internet and social media for 18 junior high schools in Surabaya were conducted about three weeks, from 3rd until 26th October 2016. Second, we create Teenstagram, by building a web application to visualize and analyze the pattern activity from teen users using Instagram. We get the 290 Instagram users account from 579 students who fill in the survey from the first stage of the research. We employ K-Modes using R to cluster the dataset with six categorical features; online type activity (like, comment follow), days in the week (Monday-Sunday), hour (00-23), student activity (study time, rest time, school time), type of school (public and private activity), and sex (male, female). We propose a tool for analyzing Instagram dataset for online time activity, this result reveals the time pattern from the teen users using social media (e.g. Instagram) and what are the characteristics of each pattern has

What is inside the mind of teenagers on Instagram?

Instagram is one of the most used social media with 45 million active users on each month. In Indonesia, the highest number of internet users is between the age of 13 34 years old. It shows that most of the new internet users are young people. In this research, we create a topic model for the Instagram caption of teenager users in Surabaya, Indonesia, using latent dirichlet allocation (LDA) method. By using pen and paper questionnaire, we collected total number of Instagram 494 valid accounts with 4,664 captions. The data were collected from January 2014 to June 2017. The process of modelling using LDA was performed by experimenting with a set of number of topics: 2, 3, 4 and 5. The two topics were selected because it has a small value of perplexity, which indicates that the model has a good level of conformity. The two topics represents two categories: school and relationship . It was found that the topic model was dominated by the relationship category

Clustering student Instagram accounts using author-topic model

This study proposes topic model to cluster a group of high school teenager's Instagram account in Surabaya, Indonesia by using the author-topic models method. We collect valid 235 Instagram accounts (133 female, 102 male students). We gather a total of 3,346 captions of Instagram posts from 18 senior high schools. We find topics that define their Instagram's post or caption; these seven topics are namely: feeling, Surabaya events, photography, artists, vacation, religion and music. Through the process, the lowest perplexity come from 90 iterations, which suggests six groups of topics. The six topics are concluded based on the lowest perplexity value and labelled according to the words included in the topic. The topic of photography discussed by six schools. Photography, artists and vacation are discussed by three schools, while feeling and religion and music are being discussed by two and one school respectively