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Connectivity measures real energization state of manifold applications and user interference in many criteria-based network systems. Randic index is a parameter of this type that can be used to measure the combined power of molecular graph or graphical network system. The concept of Randic index has been applied in a connected system in Indonesia tourism sectors under some uncertain conditions. First, Randic index of fuzzy graph (FG) and fuzzy subgraph are introduced and investigated their properties. Second, different upper and lower bounds of Randic index and their isomorphic properties in fuzzy graphs are exhibited. Third, the Randic index in directed fuzzy graph (FDG) is introduced. Due to presence of similar contribution of vertices, many formulas for calculating Randic index of regular fuzzy graphs are presented. Fourth, some similarity and distinction of Randic index with connectivity index (CI) and Wiener index (WI) in fuzzy graph are analyzed. Fifth, an algorithm and a flowchart are proposed to determine Randic index in a fuzzy graph. Finally, an application is depicted to mention the order of important crossroads and stoppages between Balai Kemambang (BKB) and Bukit Kendalisada (BKS) in Indonesia tourism sectors. [ABSTRACT FROM AUTHOR]

The Mentawai Islands are located offshore of West Sumatra, Indonesia, and are likely to be hit by a large-scale tsunami in the future. In this study, maps showing tsunami evacuation times (ETs) along the road on the Mentawai Islands were developed to mitigate tsunami impact. We define the tsunami ET as the time required for an evacuee to move to a safe location through the road network from the tsunami inundation area. The safe locations were determined using a digital elevation model and the assumed tsunami inundation heights. The closest safe place for each location on the road network was determined using the shortest path search algorithm for the graph network. First, areas with high tsunami risk on the islands were identified using the obtained ET maps. Second, the appropriateness of the evacuation approach in the Matobe village on Sipora Island was evaluated based on the ET maps. Finally, population exposures to the different ET levels were estimated to quantify the potential risk of loss of life to a tsunami disaster in the Mentawai Islands. This study contributes to the tsunami disaster preparation of residents of the Mentawai Islands. [ABSTRACT FROM AUTHOR]

Individual tree counting (ITC) is a popular topic in the remote sensing application field. The number and planting density of trees are significant for estimating the yield and for futher planing, etc. Although existing studies have already achieved great performance on tree detection with satellite imagery, the quality is often negatively affected by clouds and heavy fog, which limits the application of high-frequency inventory. Nowadays, with ultra high spatial resolution and convenient usage, Unmanned Aerial Vehicles (UAVs) have become promising tools for obtaining statistics from plantations. However, for large scale areas, a UAV cannot capture the whole region of interest in one photo session. In this paper, a real-time orthophoto mosaicing-based tree counting framework is proposed to detect trees using sequential aerial images, which is very effective for fast detection of large areas. Firstly, to guarantee the speed and accuracy, a multi-planar assumption constrained graph optimization algorithm is proposed to estimate the camera pose and generate orthophoto mosaicing simultaneously. Secondly, to avoid time-consuming box or mask annotations, a point supervised method is designed for tree counting task, which greatly speeds up the entire workflow. We demonstrate the effectiveness of our method by performing extensive experiments on oil-palm and acacia trees. To avoid the delay between data acquisition and processing, the proposed framework algorithm is embedded into the UAV for completing tree counting tasks, which also reduces the quantity of data transmission from the UAV system to the ground station. We evaluate the proposed pipeline using sequential UAV images captured in Indonesia. The proposed pipeline achieves an F1-score of 98.2% for acacia tree detection and 96.3% for oil-palm tree detection with online orthophoto mosaicing generation. [ABSTRACT FROM AUTHOR]

Only halal food is food allowed by Islamic sharia. In contrast, haram food is forbidden, for example, alcohol, pork, blood, carrion, and meat not slaughtered according to sharia regulations. In Indonesia, halal certificates are issued by the Halal Product Guarantee Agency (BPJPH) based on Article 39 of Law Number 33/2014 concerning Halal Product Guarantees. A halal certificate guarantees that food is composed of halal ingredients. However, many halal food products do not have a halal certificate. Therefore, it is useful to estimate the halal status of food products that have not been certified. In this work, we attempted to predict the halal status of food using several graph similarity algorithms. We acquired product data from the KlikIndomaret website, which contained the food product name, the composition of the food product, and the manufacturer. Then, we crawled the halal food database on the Halal MUI website. Both datasets were merged into a single dataset based on the product names. Then, similarity algorithms such as Jaccard Similarity, Approximate Nearest Neighbor, Adamic Adar and Preferential Attachment were performed on the products in the dataset. The accuracy of each algorithm evaluated by F-measure. [ABSTRACT FROM AUTHOR]