In 2018, the Indonesian government launched the Making Indonesia 4.0 Roadmap under The Industrial Revolution 4.0 era. This road map aims to increase industrial competitiveness and make the nation one of the world’s top 10 economies by 2030. The role of the Internet of Things (IoT) in The Industrial Revolution 4.0 is important to improve work efficiency and reduce companies’ costs. Although several manufacturing companies in Indonesia have successfully implemented this technology, so it is important to identify the critical success factors in its application for other companies. Therefore, this study discusses the essential factors of success for implementing IoT in automotive companies in Indonesia, which have differing specific application characteristics from the conditions in other countries. The Delphi method obtained data from 8 dimensions and 32 sub-dimensions. These included the finance, regulatory, people and management, operation, technology, innovation, ideas, and resource dimensions. Other automotive companies can use the results as a reference in implementing IoT and evaluating and improving their business performance, as well as formulating the right strategy to achieve excellence in the long term.

Facilities and infrastructure of maritime logistics activities such as ports, vessels, and containers are important indicators for developing national export-import activities. Maritime Logistics activities in container terminals has a big problem of dwelling time while apparently there are also bigger problems in Container yards. This leads to process and time efficiency problem. Container utilization can be improved in the loading and unloading process at Container Terminals and Container Yards. The Loading and Unloading processes at container yards happen to be the longest duration of all logistics activities. Therefore, increased loading and unloading efficiency at container yards are needed as an effort to increase export-import activities. The study was conducted by observing the loading (lift-on) and unloading (lift-off) process flow to identify waste using the Value Stream Mapping (VSM) method. Waste of Waiting is identified both in Loading and Unloading processes. VSM design results in an increased level of efficiency up to 84.89% for the unloading process and 80.51% for the loading process. The VSM method is needed as waste identification and efficiency improvement efforts for container service in Jakarta container depot. The VSM method is needed as waste identification and efficiency improvement efforts for container service in Jakarta container yard.

The implementation of technology is used to support the Making Indonesia 4.0 Program in various industrial sectors in Indonesia to achieve optimization of company performance. This is in line with the Indonesian Government Program through the Ministry of Industry, namely Making Indonesia 4.0. In the Making Indonesia 4.0 Program, there are 7 leading manufacturing sectors. The automotive sector is the object of this research because automotive sector is a leading player in the export of Internal Combustion Engines (ICE) and Electrified Vehicles (EVs). The technology discussed in this research is to support the Making Indonesia 4.0 Program, namely the application of the Internet of Things (IoT) to automotive companies. This research aims to evaluate the critical success factor (CSF) of IoT implementation in automotive companies in Indonesia and obtain a relationship from each dimension that becomes an evaluation of the critical success factor (CSF) of IoT implementation in automotive companies in Indonesia. In this research, the validation stage was carried out by 5 panels of experts in Indonesia who have experience and knowledge in the field of IoT application in automotive companies. The results of the research using the DEMATEL method obtained 4 critical success factors (CSF) for IoT implementation in automotive companies in Indonesia which are dispatchers who are the top priority because they have a greater influence. The four dimensions are the Marketing Dimension, Finance Regulation, and Resources. While the other 4 dimensions, namely the Dimensions of Innovation and Ideas and Resources, Operations, People, and Management, Technology became the receiver as the last priority because it received greater influence. The results of this research can be used as a reference for the automotive industry and various other industries in conducting evaluations related to the critical success factor (CSF) of IoT implementation in companies to improve company performance.

Lean is a method to reduce activities in the form of waste to increase efficiency in manufacturing or production lines and can be implemented in health services. This study analyse the flow of prescription services in BPJS Outpatient Pharmacy Installation as data for improvement. The results showed non-value added activities of 22%, value added activities of 74%, necessary non-value added activities of 4%, and process cycle efficiency of 74%. As for non-concoction drugs, non-value added activities are around 39%, value added is 61% and process cycle efficiency is 61%. The data shows that there is a process of non-value added and necessary non value added which causes the waiting time for outpatient pharmacy. Furthermore, using fishbone analysis to determine the cause of the problem and build improvements based on FMEA results. From the research results obtained that waste that often occurs is waiting that occurs in the taking of drugs. The recommended improvements are the addition of human resources in the collection and compounding of drugs, classifying and allocating types of drugs based on the speed of the drug and the implementation of 5S in BPJS outpatient pharmacy.

The automotive industry is one of the industries that plays a major role in Indonesia’s revenue sources, one of which is in meeting daily needs, especially for transportation and logistics. This causes the growth of truck production targets each year and has become one of Indonesia’s focus to target 1.29 million trucks produced in 2020. This study aims to minimize production time with the optimal number of workstations to minimize costs that will come out for increasing production capacity in truck assembly lines in Indonesia. The study was conducted with a lean manufacturing approach to analyze the waste contained in the assembly line. The study began by calculating time for each work using the time study method. The time obtained is then inputted to the mixed integer linear programming mathematical programming model developed in the LINGO 17.0 software. The result of data processing in the LINGO 17.0 software is the allocation of each job to the new workstation to get the production cycle time in accordance with the production takt time, and also the total idle time of the new assembly line.

Service quality improvement at I Gusti Ngurah Rai International Airport in Indonesia needs to be done to improve service to passengers. This is done because the I Gusti Ngurah Rai International Airport in Indonesia is an international airport with a large number of passengers compared to other international airports. So it is necessary to improve quality to maintain airport performance and increase satisfaction and loyalty to passengers to visit I Gusti Ngurah Rai International Airport. This study, to improve airport passenger services by conducting initial analysis, namely determining the attributes of the airport passenger service level that need to be improved. The method used in this study uses the Servqual method and the Theory of Inventive Problem Solving (TRIZ) method. In this study, there are 28 service quality attributes based on 5 dimensions of service quality. Based on the service quality calculation, there are 7 positive gap attributes, 4 zero gap attributes, and 17 negative gap attributes. So, 17 service quality attributes indicate passengers are not satisfied with the services provided on these attributes. Based on the results of the method, the initial stage is an analysis using a cause-effect diagram to see the potential contradictions and causes of problems by the 17 attributes. So that 12 attributes cause contradictions in solving problems and 5 attributes that do not cause contradictions in solving problems. Attributes that cause contradictions are then analyzed using the TRIZ method using 39 engineering parameters, a contradiction matrix, and 40 inventive principles. Meanwhile, attributes that do not cause contradictions will be analyzed and solutions will be provided based on 40 inventive principles. Based on the results of the analysis carried out using TRIZ, it was found that the proposed improvements for each attribute were adjusted based on the principles of universality, segmentation, change parameters), taking out, mechanical vibration, preliminary action, and mechanics substitution.