Jurnal Teknobisnis

Analysis Of Retailer Secured Channel Technology Platform Acceptance Model Using The UTAUT-2 Method

2023-11-15T07:04:26+00:00

The national cement industry has experienced oversupply since 2017 coupled with the decline in national cement consumption during the pandemic, these conditions have made business competition in the cement sector increasingly stringent. PT XYZ is one of the companies that produce cement in Indonesia with a marketing and distribution network throughout the archipelago, 85% of the company's revenue is derived from the sale of cement products and the remaining 15% from non-cement products. During the Covid-19 pandemic, there was an increase in the penetration of online shopping for retail products and a change in people's behavior in transactions. The secured channel retailer technology platform built on a digital ecosystem at PT XYZ is expected to be able to increase the number of users and transactions that are still not optimally used by its customers, this has prompted the author to find out what factors influence the level of acceptance and use. In this study, the authors used the UTAUT 2 method by adding the Trust variable. Using the PLS-SEM and SmartPLS methods as data analysis software to test the research hypothesis using data samples from 184 respondents. The results of this study indicate that of the 11 hypotheses tested, 2 were rejected. The influence of Hedonic Motivation and Price Value on Behavioral Intention is not significant because, on the secured channel retailer technology platform, the retail products sold are basic materials, not an item that is a category of routine needs or needs for pleasure. The Trust variable (TR) has the greatest influence on Behavioral Intention (BI) at 62.5% and the Habit variable (HA) has the greatest influence on Use Behavior (UB) at 47.3%. Service providers need to focus on ensuring the security of users' data and learning new habits of users so that interest in using this technology increases.

Product Innovation Design of Freight Shipping Website Application on Maritime Transportation Using the Design Thinking Method

2023-11-15T07:11:21+00:00

Indonesia is a maritime country, and most logistics activities are by sea. Digitization is needed as a form of differentiation and competitive advantage in logistics services. The current condition of shipping through maritime transportation has several problems such as uncertainty of ship departure and arrival schedules, inability to monitor shipments, too long broker chains, unable to provide integrated multimodal transportation shipments between islands in Indonesia, and lack of public knowledge about available ship routes and schedules and selection of the most appropriate type of ship. An innovation is needed in this case that can become a platform to facilitate and visualize the delivery of goods using digital maritime transportation based on web applications. This research uses the three stages of the design thinking model proposed by IDEO: inspiration, ideation, and implementation. In developing a system, a prototype is needed, or it can be called a minimum viable product. At the implementation stage, there is a usability testing process that uses a feedback capture matrix and a system usability scale. The results of the research are in the form of a product with the hope of pioneering the use of comprehensive digitization and making it easier for customers to ship goods via maritime transportation.

Decision Making of Diesel Power Plant Hybridization Method of Selat Nasik Diesel Power Plant in Belitung Island Using AHP-VIKOR

2023-11-15T07:14:28+00:00

The selection of best hybridization methods scenario of Diesel Power Plant or HRES (Hybridization Renewable Energy System) requires not only a good analysis of techno-economic criteria but also many other criteria such as land availability, energy sources availability, and so on. Considering the complexity of criteria involved in the selection of hybridization methods, Multi-Criteria Decision Making (MCDM) is commonly used to evaluate problems with multiple criteria that often have conflicting interests. The HOMER software was used as the basis for conducting techno-economic analysis of various hybridization scenarios that would be applied to the Selat Nasik Diesel Power Plant. Then, an FGD expert was conducted to validate and determine the important criteria for selecting hybridization method scenarios. A pairwise questionnaire were filled out by 5 (five) experts, and then the criteria were weighted using the Analytic Hierarchy Process (AHP). The obtained criteria weights then used by experts to assess several hybridization scenario options, and their rankings were determined using VIKOR. In this research, 17 sub-criteria were identified and categorized into 3 criteria: Technical and Design-Oriented Criteria (Lifespan of HRES, Energy Resources Sustainability, and Potential Power Generation), Financial-Oriented Criteria (CAPEX, O&M Cost, NPV, LCOE, and Diesel Fuel Consumption), and Socio-economic and Environment- Oriented Criteria (GHG Emission, Land Acquisition, Effect on Ecosystem (Animal and Nature Protection), Force Majeure, Noise Pollution, Prospective Jobs and Economic Growth, Political and Regulatory Aspect, Public Awareness Level, and Tradition and Cultural Heritage). Top three sub- criteria with the highest weights were selected: Energy Resources Sustainability (weight 0.408), LCOE (weight 0.096), and CAPEX (weight 0.087). Scenario 1 (S1 (Diesel, PV, Battery)) was chosen as the first-rank scenario (the best scenario) followed by S2 (PV, Battery), S3 (Wind Turbine, PV, Battery), and S4 (Diesel, Wind Turbine, Battery).

Modeling Prediction of Sulfur Dioxide (SO2), Nitrogen Oxides (NOX) Emissions and Particulate from Coal-Fired Power Plant Using Machine Learning

2023-11-14T08:13:27+00:00

Coal-fired power plants remain a crucial source of electricity in meeting national energy demands, despite the environmental challenges posed by the emissions generated during coal combustion. Emission coal-fired power plants include Sulfur Dioxide, Nitrogen Oxides, particulate matter have negative impact to the environment. To mitigate these emissions, regular monitoring, and measurement of gas emissions, as well as the development of emission prediction models, are essential. Machine learning has emerged as a promising approach for predicting gas emissions. In this study, Gradient Boosting (GB), Artificial Neural Network (ANN), and Support Vector Regression (SVR) machine learning models are employed. Factors influencing SO2, NOx, and particulate matter emissions are obtained from Distributed Control System records of the boiler system, along with the gas emission control technologies, comprising a total of 19 independent variables. Optimization of the boiler system can contribute to the reduction of gas emissions. The analysis results, measured by RMSE, R Square, and MAE, indicate that Gradient Boosting yields the most accurate predictions for gas emissions and particulate matter.

Prediction of Surabaya City Apartment Rental Price Using the Ensemble Method

2023-11-14T08:26:48+00:00

Increasing the need for residential space requires in city to improve development infrastructure to meet the needs of its inhabitants. Having an apartment will help optimize the capacity of residential land in limited land, especially for areas with high population density and small areas such as the city of Surabaya. Until 2020, the level of demand for housing or rental in apartments tends to decline and after the COVID-19 pandemic made a huge impact on the apartment market from a sales perspective and prices dropped dramatically. A property consulting firm, Coldwell Banker Commercial, stated that among other big cities, only Surabaya had a better performance in apartment marketing, because the sales rate and average price increased by 0.4%. Seeing the urgency and potential for the weakening of modern society in choosing apartment housing in the city of Surabaya, the authors conducted a study that could assist in predicting apartment rental prices according to apartment criteria in Surabaya such as sub-district location, unit type, area, floor number, and unit facility contents. The data used is data from travelio.com which is one of the most trusted websites in Indonesia for apartment rentals using the scraping method. The apartment rental price prediction model using the ensemble method found that the stacking model with a combination of gradient boosting regression, random forest, decision tree regression, linear regression meta liner regression has higher performance, with an MAE value of IDR 243,401, RMSE of IDR 179,432 and a value R2 is 63.28%, which means that it affects the price of apartment rentals by 63.28%, while 36.72% is influenced by other factors that are not included in the model.

Millennial Generation Preferences in Selection of Residentials in Jabodetabek Area

2023-11-14T08:41:40+00:00

Millennials consider houses as not only protecting and surviving but also fulfilling their desires and rising socioeconomic status. However, 31% of Indonesia's total millennial population doesn’t have a house, so millennials could become a big market for property industry. The purpose of this study is to analyze the combination of attributes which become the preference of the millennial and to analyze the characteristics and financial capabilities to buy a house by utilizing a conjoint analysis approach. Thirty-two combinations resulted from an orthogonal design and were distributed via an online questionnaire to 116 respondents. The results showed, the most important attributes were Location (17,42%), followed by Certificate State (SHM) (15,51%), Price (11,90%), Size Type (10,58%), Developer Reputation (10,48%), Public Facilities (10,31%), Floors (9,40%), Open Space (7,60%), and Number of Bedrooms (6,80%). Currently, most millennials are unmarried (53%), don't have children (59%) and work in Jakarta (28%) with income range IDR 5-10 million (42%). The preferred payment method is KPR for 6–15 years (43%) and installments of IDR 3-5 million (49%). The outcome of this study can be used as recommendations for new residential products for home developers and recommendations to the Jabodetabek regional government in regulating urban area planning.

Designing A Technology-Based Supply Chain Resilience Strategy in the Beauty Industry Against Pandemic Disruption

2023-11-14T08:58:48+00:00

The case of Covid-19 decreases day but day, but customer behavior has changed into covid behavior which shifted into technology. While the supply chain remains vulnerable, much research conducted proposes resilience enhancing strategies applied into technology. Therefore, this research focuses on designing a framework that contains technology-based strategies to increase supply chain resilience of the beauty industry starting from the proactive, concurrent, and reactive phases using the Best-Worst Method and ELECTRE. Three major steps were carried out for this research, starting with step (1) analyzing and identifying risks and strategies that affect the resilience of the beauty industry supply chain, (2) weighting the risks using the Best-Worst Method, and (3) ranking the strategies toward the risks using ELECTRE. At the end of the research, a framework which contains supply chain resilience strategies has been formed through identifying and weighting risk, as well as identifying and prioritizing the strategies. The riskiest risk is short product cycle, and the highest strategies rank are collaboration, knowledge, financial strength, and others.

Selection of Remote-Control Tie Switch Installation Location Using AHP-Promethee Method

2023-11-14T09:09:13+00:00

Remote-Control Tie Switch (RCTS) installation is one of the solutions that can be implemented to increase the reliability of the electric power distribution system. However, installing RCTS at all maneuvered points requires high investment costs, so it is necessary to prioritize locations based on sequence. In this research, there are 79 alternative locations and 5 criteria were used to prioritize RCTS locations. Alternatives based on the criteria produce different preferences, so these preferences must be measured first with Analytical Hierarchy Process (AHP). Then, Preference Ranking Organization Method for Enrichment Evaluation (Promethee) were used to get the location ranking order. The results of the AHP method show that the largest criterion weight is the number of customers (43,43%) and the smallest criterion weight is access to the location (4,64%), with a consistency ratio is 0,0787. The results of the Promethee method obtained the highest net flow value is the AMT02-KDG06 feeder maneuver point (0,415) and the lowest net flow value is the PLH03-PLH04 feeder maneuver point (-0,275). The results of the sensitivity analysis by increasing and decreasing the weight to 5%, 10% and 15% obtained no significant change in the rank position of the location and standard deviation.

Financial Feasibility Analysis of Cilampuyang Hydropower Plant Project (2X15 MW)

2023-11-14T09:22:11+00:00

The Cilampuyang Hydropower Plant (2x15 MW) project is deemed feasible based on the financial analysis conducted. The electricity demand in West Java is projected to reach 20.1 million customers by 2030, with a growth rate of 3.27%. In light of the renewable energy policy, hydropower is considered a viable solution. The project is undertaken by PT Bangun Daya Utama and PT Bukaka Teknik Utama. According to the Renewable Power Generation Costs in 2021 report by IRENA, the construction costs for new hydropower plants from 2010 to 2021 ranged from USD 600/kW to USD 4,500/kW, equivalent to approximately Rp. 8,907,990/kW to Rp. 66,809,925/kW. Hence, the estimated costs for implementing the Cilampuyang Hydropower Plant project (2x15 MW) are substantial. Therefore, a financial analysis is crucial to determine the project's feasibility. This study aims to evaluate the economic viability and identify associated risks through the TPEM and LCOE investment feasibility analysis methods. Monte Carlo simulations were employed to assess project implementation risks. The research findings indicate that the TPEM and LCOE values for the Cilampuyang Hydropower Plant project are superior to the minimum required values. The NPV is Rp. 32,112,681,609,569, the IRR is 275%, and the LCOE is 0.013 USD/kWh. These results indicate that the investment in the Cilampuyang Hydropower Plant is financially viable. Furthermore, project implementation risks were measured using Mean NPV and minimum NPV parameters from 10,000 Monte Carlo simulations, yielding a Mean NPV of Rp. 33,867,831,000,000 and a minimum NPV of Rp. 26,331,417,000,000. In conclusion, the Cilampuyang Hydropower Plant presents a promising alternative for meeting the electricity needs in West Java while adhering to renewable energy policies. From an economic perspective, the investment in the Cilampuyang Hydropower Plant is feasible based on the favorable NPV, IRR, and LCOE values. However, project implementation risks should be considered based on known significant variables.

Audit Energy for Electricty Saving at PT XYZ

2023-11-14T09:47:11+00:00

PT XYZ is an integrated multinational engineering, procurement, construction, and installation company service provider. Production activities of PT XYZ require a very large amount of electrical energy. In 2022 electricity consumption will reach 35,459,867 kWh. The Commissioning Building + Deck erection area (Tr. 6D) Division is the area with the largest consumption, namely 8,720,628 kWh. The amount of electricity consumption has an impact on the increasingly expensive production costs. So, it is necessary to save electrical energy through an energy audit. Determination of Energy Saving Opportunities (PHE) in this study uses two calculations, namely Energy Consumption Intensity (IKE) and Specific Energy Consumption (KES). The data in this study is in the form of quantitative data obtained directly from PT XYZ which includes data on electrical energy, area, human resources, electrical installations, total energy consumption and total production in 2022 and during research from February 2023 to April 2023. After an energy audit was carried out and data on IKE and KES values obtained, then identify potential energy savings, which aims to determine the potential for Energy Saving Opportunities (PHE) electricity in the Division of Commissioning Building + Deck erection area (Tr. 6D) PT XYZ. Data analysis was carried out based on the results of energy audits and IKE and KES values. Saving electrical energy in the Division of Commissioning Building + Deck erection area (Tr. 6D) PT XYZ can save up to 15.14 % of electrical energy, so that it will have a significant impact on reducing production costs at the company.