Transportation plays an important role in helping every community activity and also has an important function in economic, social and developmental development. Online transportation provides alternative transportation solutions in the middle of the density of vehicles to be fast and able to reach places that are likely to be inaccessible to other public vehicles. People who usually use public transport or conventional taxi services have begun to switch to online-based taxis that are considered cheaper and more practical. Market research institutes in Southeast Asia show that 250 million Indonesians are quickly adapting the growth of application-based transportation (taxis and ojek online) to facilitate their lives. Various factors that influence people prefer online transportation compared to public transport or conventional taxis. The purpose of the study is to determine the main factors that people prefer to use Oline transportation. The study used the VIKOR method system which obtained the results based on the VIKOR index value where alternative A1: Easy and Safe (VIKOR index value 0) as a rank one and alternative A2: Price (VIKOR index value 0.1809520) as the second rank.
Along with the progress of the times, the development of graphology has changed towards computerization. The fundamental problem in automated graphology is how to determine personality traits through digital handwriting using the principles of graphology. Although various models and approaches have been developed in research related to automated graphology, there are still obstacles to overcome such as the selection of preprocessing techniques and image processing algorithms to extract handwriting features and proper classification techniques to get maximum accuracy. Therefore, this study aims to design a reliable framework using image processing and machine learning approaches such as filtering, thresholding, and normalization to determine the personality traits through handwriting features. Then, handwriting features are classified according to the Big Five model. Experiments using the decision tree, SVM (kernel RBF), and KNN produced an accuracy above 99%. These results indicated that the proposed framework can be well applied to predict the personality of the Big Five model through handwriting analysis features.
This study focuses on efforts to implement Government Decree No. 49 of 2018 concerning civil servants with employment contracts (P3K) in northern Aceh. This study uses descriptive qualitative research methods using data collection methods using observation, interviews, and documentation. The results showed that the government's efforts to implement Government Decree No. 49 to 2018 regarding Civil Servants with Contract of Work (P3K) is carried out with the first phase receiving first aid from PTT staff and the agriculture department, while not accepting it for other groups, although in limited circumstances due to local budget constraints. P3K is very useful for the government in filling gaps in various government institutions or institutions. For the community itself, there are several benefits related to P3K, namely by having multiple records, the income earned will be the same as for a civil servant, will receive the same benefits as a civil servant, the application age is higher and can be reduced to the maximum retirement age.
Automotive maintenance workers or commonly known as mechanics are exposed to numerous work stressors while performing their works. Maintenance activities required worker to be in different type of working posture, which mostly awkward posture and in high risk to developed musculoskeletal disorder. Statistics data disclosed that musculoskeletal disorder among maintenance workers is quite high compared to the other types of job sectors. Therefore, this study aims to examine the working posture amongst the mechanics based on their job activities. By using an ergonomic assessment sheet for posture known as Rapid Entire Body Assessment (REBA), ten common vehicle maintenance activities with ten mechanic in the maintenance jobs have been evaluated based on their feedback. The findings showed that, nine out of ten activities are in the high risk and necessary action need to be taken soon. Awkward posture such as excessive bending and twisting for several body parts with heavy parts as well as poor coupling design on the automotive parts or tools are the factors that influence the risk of injury in this maintenance activities. This study is very useful for automotive industry to evaluate their worker’s condition in maintenance activities. This should be an employer and employee essential knowledge to understand that vehicle maintenance work will include awkward posture. Self-awareness regarding the high risk in developing musculoskeletal disorder will reduce the worker chance to be in discomfort while working.
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