Residential electricity demand can be influenced by the behavior of users. Therefore, it is essential to know users’ behaviors to reduce electricity consumption or for energy saving. This research aims to analyze users’ behaviors concerning the use of light-emitting diodes (LED) lamps in the residential sector in Makassar, Indonesia. Moreover, the drivers of users’ behaviors in terms of usage and habitual behavior are also identified by two composed regression models. Some options for both models were compared by using statistical tests to get better models. A questionnaire was developed, and the survey was done on respondents that have 900 VA and greater of installed power capacity in their homes to get data for analysis. The main finding of this research shows that the user’s perception of energy saving was quite good. Both proposed models, namely LED usage model and habit model, were well §validated with R adj 2 a value above 39% for both models. Six considered variables can explain usage behavior better than the habit of users. Among the significance variables, the factor of the technology aspect has the highest effect on the usage of LED lamps and the general perception factor for the user’s habit. Presented results may give useful information in designing programs for consumers in Makassar, such as energy conservation programs or home energy management systems.

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AHP TOPSIS is a decision support method to find the closest alternative by showing the value of the ideal positive alternative solution and negative ideal solution to get the best alternative, where the AHP method is used to give the weight value of the criteria and TOPSIS to get the ranking from each alternative. This study conducted the best alternative selection using the application of the AHP method integrated with TOPSIS to assess eight criteria and six alternatives in determining the ideal location of rubber plantations in Merauke Regency. The results provide recommendations to the relevant Dinas and developers to choose the ideal location and invest in the rubber plantation business.

In general, industrial sector consumes high energy. Therefore, efforts to manage the energy usage in this sector are useful as it can reduce significantly total energy consumption mainly for electricity. This research aims to observe consumers’ perceptions and success factors to improve efficiency of electricity energy usage for industry particularly for manufacturing small-medium enterprises (SMEs) in Makassar as a representative big city in Indonesia. A questionnaire for survey is designed to get data from 127 respondents and analysed using statistical approach. Observed variables related to energy efficiency in SMEs include human resources, production technology, rainfall, and tax. Results shown the developed questionnaire is reliable (Cronbach’s alpha value exceeds 0.6). Perception of consumers about energy saving is quite good. From aspect of demographic characteristic, there is a difference in users’ perceptions on energy saving. Other results show the significant relationship between human resources, production technology, and rainfall condition to the energy efficiency level at SMEs. Knowledge or findings of this study provide valuable information in relation to strategy to improve efficiency of electricity usage in industries.

Butsudan production companies have a major problem, namely that the production process has been delayed so that it is difficult to meet production targets on time. The problem is because the scheduling system used is not optimal. Based on these problems, the purpose of this study is to minimize the makespan value by determining the right sequence of jobs. In this study, the method used is the Heuristic Pour Algorithm, Branch and Bound, and NEH. Based on the results of the calculation using the company method, the makespan is 9.958,4 minutes, and the Heuristic Pour method is obtained by the makespan value of 9.461,1 minutes with job sequence J3-J2-J1-J4, the Branch and Bound method obtained by the makespan value of 9.717,3 minutes with job sequence J3-J1-J2-J4, the NEH method obtained the makespan result of 9.846,5 minutes with job sequence J2-J4-J1-J3. So using the proposed method can minimize makespan by 111,9 minutes to 497,3 minutes or about 8 hours.