This study was conducted with the aim to the clustering of provinces in Indonesia of the risk of the COVID-19 pandemic based on coronavirus disease 2019 (COVID-19) data. This clustering was based on the data obtained from the Indonesian COVID-19 Task Force (SATGAS COVID-19) on 19 April 2020. Provinces in Indonesia were grouped based on the data of confirmed, death, and recovered cases of COVID-19. This was performed using the K-Means Clustering method. Clustering generated 3 provincial groups. The results of the provincial clustering are expected to provide input to the government in making policies related to restrictions on community activities or other policies in overcoming the spread of COVID-19. Provincial Clustering based on the COVID-19 cases in Indonesia is an attempt to determine the closeness or similarity of a province based on confirmed, recovered, and death cases. Based on the results of this study, there are 3 clusters of provinces.

The premise of this work is the modification of the properties of chitosan-based film for possible use in food packaging applications. The biofilm was prepared via thermal and mechanical treatment through blending polymers with chitosan using Polyvinyl Alcohol (PVA) and loading different types of chemical agents, i.e., citric acid (CA), succinic acid (SA), and tetraethoxysilane (TEOS). The modification was carried out under high-speed homogenization at elevated temperature to induce physical cross-linkage of chitosan polymer chains without a catalyst. The findings showed that PVA improved the chitosan films’ Tensile strength (TS) and elongation at break (Eb). The presence of chemicals caused an increase in the film strength for all samples prepared, in which a 5% w/w of chemical in the optimum composition CS/PVA (75/25) provided the maximum strength, namely, 33.9 MPa, 44.0 MPa, and 41.9 MPa, for CA-5, SA-5, and TEOS-5, respectively. The chemical agents also increased the water contact angles for all tested films, indicating that they promoted hydrophobicity. The chemical structure analysis showed that, by incorporating three types of chemical agents into the CS/PVA blend films, no additional spectral bands were found, indicating that no covalent bonds were formed. The thermal properties showed enhancement in melting peak and degradation temperature of the blend films, compared to those without chemical agents at the optimum composition. The X-ray diffraction patterns exhibited that PVA led to an increasing crystallization tendency in the blend films. The morphological observation proved that no irregularities were detected in CS/PVA blend films, representing high compatibility with both polymers.

This research aims at investigating the corrosion behavior and hardness of AISI Stainless Steel 304 (AISI SS 304) in corrosive hydrochloric acid solution and temperature variation treatment. In this study, the samples of AISI SS 304 are immersed for six (6) days in the corrosive acid solution at the temperature of 30°C and 50°C. The solution used as the corrosive media are HCl, FeCl3, and NaCl in the concentration of 5%, 10% and 15%. The results show that the higher the concentration of the solution, the higher the corrosion rate of AISI SS 304 will be, and the higher the temperature, the higher corrosion rate will also occur in all corrosion media. The corrosion that occurs in AISI SS 304 is mostly in the form of uniform corrosion and some pitting corrosion, and the value of hardness decreases after corrosion.

Compound Poisson process (CPP) is one of the models of stochastic processes in which this model can model a real phenomenon that has an element of uncertainty in the process. CPP has two main components, those is a Poisson process on the component of the poses of an event that occurs and a sequence component of the magnitude as a result of the process of events that occur. This research aims to develop an algorithm to generate random numbers from CPP with a component in the Poisson process in the form of a nonhomogeneous Poisson process (NHPP) and a component in the magnitude of the effect in the form of an exponential distribution (CPP-NHPP-ED). The method used is using the acceptance and rejection method in the form of Thinning process techniques. The results of the study obtained several algorithms, namely the algorithm for CPP-HPP-ED, CPP-NHPP-ED type 1, and CPP-NHPP-ED type 2. These algorithms can be used for computer simulation analysis that can be applied to various fields of science and engineering.

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