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Urfan Taghiyev
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INDONESIA
Journal La Multiapp
Published by Newinera Publisher
ISSN : 27163865     EISSN : 27211290     DOI : https://doi.org/10.37899/journallamultiapp
Core Subject : Engineering,
International Journal La Multiapp peer reviewed, open access Academic and Research Journal which publishes Original Research Articles and Review Article, editorial comments etc in all fields of Engineering, Technology, Applied Sciences including Engineering, Technology, Computer Sciences, Architect, Applied Biology, Applied Chemistry, Applied Physics, Material Engineering, Civil Engineering, Military and Defense Studies, Photography, Cryptography, Electrical Engineering, Electronics, Environment Engineering, Computer Engineering, Software Engineering, Electromechanical Engineering, Transport Engineering, Mining Engineering, Telecommunication Engineering, Aerospace Engineering, Food Science, Geography, Oil & Petroleum Engineering, Biotechnology, Agricultural Engineering, Food Engineering, Material Science, Earth Science, Geophysics, Meteorology, Geology, Health and Sports Sciences, Industrial Engineering, Information and Technology, Social Shaping of Technology, Journalism, Art Study, Artificial Intelligence, and other Applied Sciences.
Articles 322 Documents
Causal Structure of Toll Road Tariff Determination in Public Private Partnership Projects: A System Dynamics Approach Wicaksono, Anggito Adji; Rachmawati, Farida
Journal La Multiapp Vol. 7 No. 2 (2026): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v7i2.3007

Abstract

The Solo Yogyakarta Yogyakarta International Airport Toll Road is a national strategic infrastructure project in Indonesia developed under a public private cooperation scheme using a build operate transfer arrangement. In this scheme, toll tariffs function as the primary mechanism for investment recovery, making tariff determination a critical factor influencing traffic demand and project feasibility. This study aims to develop a system dynamics based model to explain the structural relationships governing toll tariff determination in toll road projects implemented through public private cooperation. The research applies a quantitative modeling approach using system dynamics, following stages of problem formulation, development of a dynamic hypothesis, and construction of a causal loop diagram. Key variables are identified through literature review, expert judgment, and secondary data analysis, including toll tariffs, average daily traffic, user affordability, operational costs, and financial performance indicators. The analysis focuses on identifying cause effect relationships and feedback structures that influence traffic demand and revenue behavior. The results show that toll tariff determination is governed by interacting reinforcing and balancing feedback loops, with traffic volume emerging as a central variable linking tariff policies to revenue and financial performance. Higher tariff levels may increase unit revenue while simultaneously reducing traffic demand due to affordability constraints, whereas economic growth and service improvements support reinforcing demand effects. This study concludes that toll tariff determination should consider dynamic interactions among demand, affordability, and financial variables rather than relying solely on static cost-based approaches.
Feasibility Analysis of the 40 MWp Tembesi Floating Solar Power Plant Development Project Putra, Muhammad Ariansyah; Prabowo, Eri
Journal La Multiapp Vol. 7 No. 2 (2026): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v7i2.3017

Abstract

This study aims to analyze the feasibility of the Tembesi Floating Solar Power Center (PLTS) construction project with a capacity of 40 MWp in the Batam - Bintan electricity system. The financial feasibility includes calculation of investment costs, operation and maintenance costs, and cost benefit analysis using indicators such as Net Present Value (NPV), Internal Rate of Return (IRR), and Payback Period. The operational feasibility analysis includes alternatives to achieving goals, assessment of how to achieve goals, scope of work, and conclusions of the operational feasibility study. The results showed that the construction of a floating solar power plant in Tembesi Reservoir is technically feasible. The proposed design and technology are capable optimal performance of the floating solar PV system, ensuring effective and efficient operations. Financial analysis, including consideration of sensitivities and assumptions, shows that the project is financially viable. The project has an internal rate of return (IRR) that meets the investment feasibility requirements. The rates are 8.82 cUSD/kWh if the power is evacuated through 150 kV lines, and 7.96 cUSD/kWh if evacuated through 20 kV lines. Based on the analysis, the construction of 40 MWp Tembesi Floating Solar Power Plant electricity system is declared feasible to be implemented.
An Analysis of the Effectiveness of the SI-PAL Application in Hospital Quota Management within the Medical Professional Study Program Using the PIECES Method Arsan, Edy Hidayat; Muslim, Aries; Sinuraya, Amri
Journal La Multiapp Vol. 7 No. 2 (2026): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v7i2.3025

Abstract

This study aims to analyze the effectiveness of the SI-PAL Application in hospital quota management in the Medical Profession Study Program, with a focus on optimizing coordination between the Study Program and Komkordik and equalizing the distribution of student clinical rotations. The research method used a quantitative approach with an evaluative model based on the PIECES Framework, which includes the dimensions of Performance, Information, Economy, Control, Efficiency, and Service. The relationship between variables was tested using the Partial Least Square-Structural Equation Modeling (PLS-SEM) method, involving a sample of 202 respondents consisting of program directors, administrators, and students. The analysis results show that the SI-PAL application has a significant effect on the effectiveness of quota management, with a path coefficient value of 0.982 and a coefficient of determination ($R^2$) of 0.964. This finding indicates that SI-PAL is capable of improving response speed, data exchange reliability, and proportionality of rotation distribution, particularly through automatic plotting mechanisms and concurrency techniques. Evaluation across the six PIECES dimensions also demonstrated the system's superior performance, particularly in terms of information quality, operational efficiency, and user satisfaction.Overall, this study confirms that SI-PAL is an effective digital instrument in supporting clinical rotation management and improving the quality of institutional coordination. However, approximately 3.6% of the variability in quota management performance is influenced by external factors such as network stability, user readiness, and resistance to digital change, thus requiring mitigative strategies to improve overall performance.
Identification of Critical Factors Influencing Lean Construction Performance in Construction Projects Candraningtyas, Devita; Wiguna, I Putu Artama
Journal La Multiapp Vol. 7 No. 2 (2026): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v7i2.3038

Abstract

The Indonesian construction sector continues to face persistent problems related to inefficiency, material waste, schedule delays, and cost overruns, despite increasing interest in adopting Lean Construction principles. These challenges indicate that lean implementation has not been fully supported by well-defined organizational and managerial foundations. This study aims to identify and validate the indicators that form the Critical Success Factors influencing Lean Construction Performance in high-rise building projects in Indonesia. This research uses quantitative methods. The research population consists of construction professionals involved in high-rise building projects, including contractors, consultants, and project management teams. A total of 360 questionnaires were distributed, of which 155 responses were returned. After data screening, 125 valid responses were used for further analysis. Data analysis was conducted using Structural Equation Modeling with the Partial Least Squares method through SmartPLS 3.0, focusing on the evaluation of the measurement model. The results indicate that the proposed constructs are formed by valid and reliable indicators after eliminating indicators with outer loadings below 0.70. The validated indicators represent management commitment and involvement, human resource development, communication and collaboration, internal client focus, and planning techniques and continuous improvement. These findings provide empirical evidence on the key indicator structure of Critical Success Factors relevant to Lean Construction Performance.
Mode Choice Analysis between Executive Rail and Sleeper Bus on the Surabaya – Jakarta Corridor Using Binary Logit Regression Wahyudi, Slamet; Widyastuti, Hera
Journal La Multiapp Vol. 7 No. 2 (2026): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v7i2.3043

Abstract

Surabaya and Jakarta are two major cities in Indonesia that serve as national centers of business, economic activity, and government administration, resulting in high intercity mobility between them. The operation of the Trans‑Java Toll Road has accelerated the growth of sleeper bus services, while executive rail remains a preferred mode due to its stable comfort and reliability. This study aims to identify passenger characteristics, analyze the probability of mode choice based on factors such as fare affordability, travel time, comfort, calmness, and safety, and propose service improvements for both modes. A revealed preference survey was conducted with two hundred respondents who had already selected either executive rail or sleeper bus for their Surabaya–Jakarta trip. The data were analyzed using binary logistic regression to model the probability of choosing each mode. The results show that most passengers belong to the choice‑user category at 65.5 percent and are predominantly private‑sector employees at 52.5 percent. The key determinant for selecting executive rail is the importance placed on calmness and comfort, yielding a predicted probability of 78.52 percent. In contrast, the dominant factor influencing sleeper bus selection is safety consideration, with a predicted probability of 96.52 percent. These findings indicate that executive rail attracts passengers seeking a quiet and comfortable travel environment, while sleeper buses appeal to travelers prioritizing safety and time efficiency supported by toll‑road connectivity. The study concludes that service improvements should focus on enhancing comfort and safety to strengthen the attractiveness of both premium land transport modes along the Surabaya–Jakarta corridor.
Systematic Review of Hyperparameter Adjustment and Evaluation Metrics in Bert-Based Sentiment Analysis Bahari, Aris Rifki Setiya; Utomo, Fandy Setyo; Berlilana, Berlilana
Journal La Multiapp Vol. 7 No. 2 (2026): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v7i2.3046

Abstract

The development of sentiment analysis towards Aspect-Based Sentiment Analysis (ABSA) has made significant progress thanks to deep learning technology, especially through the Bidirectional Encoder Representations from Transformers (BERT) architecture. Despite its increasing popularity, a comprehensive synthesis of global research patterns and optimal model configurations is still urgently needed. This study presents a Systematic Literature Review (SLR) combined with bibliometric analysis to examine BERT-based ABSA research indexed in Scopus. Using the PRISMA and VOSviewer frameworks for visualization, a total of 62 eligible articles up to mid-2025 were analyzed. The results of the study show a strong upward trend of publications with a peak in 2024, where China, India, and Indonesia emerged as the major contributors in this domain. Further, the review identified a critical technical standard for effective model training: the Adam optimizer was the most dominant choice, typically paired with a learning rate between 1e-5 to 2e-5 and a batch size of 16. Regarding performance evaluation, Accuracy and F1-Score are set as de facto standard metrics. These findings provide strategic guidance for researchers to optimize BERT implementation and identify future directions in more in-depth sentiment analysis tasks.
Assessment and Prioritization of Contractor Internal Schedule Delay Risks in Phnom Penh High-Rise Building Projects Using Relative Importance Index Method Haitin, Res; Wiguna, I Putu Artama
Journal La Multiapp Vol. 7 No. 2 (2026): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v7i2.3054

Abstract

The rapid expansion of high-rise building projects in Phnom Penh has been accompanied by persistent schedule delays that significantly impact project performance. While external factors are often emphasized, contractor internal risks represent controllable factors requiring systematic assessment and prioritization. This study aims to identify and prioritize contractor internal delay risk factors in high-rise building projects in Phnom Penh through quantitative analysis of expert perceptions. A mixed-methods approach was employed, combining qualitative data collection through structured questionnaires with quantitative analysis using the Relative Importance Index (RII). Data were collected from 97 construction professionals involved in high-rise projects (exceeding 10 floors) in Phnom Penh during 2020–2025. Seventeen internal risk factors were assessed across probability (RII-P) and impact (RII-I) dimensions. Analysis identified three critical risks with Risk Scores ≥ 0.60: Poor Planning and Scheduling (RII-P: 0.81, RII-I: 0.83, Risk Score: 0.68), Cash Flow Problems (RII-P: 0.76, RII-I: 0.83, Risk Score: 0.64), and Ineffective Monitoring and Control (RII-P: 0.79, RII-I: 0.79, Risk Score: 0.62). Fourteen additional risks were classified as Medium Priority (Risk Scores: 0.46–0.56). Managerial and financial factors dominate internal delay risks in Phnom Penh's high-rise construction, suggesting contractors should prioritize planning systems, financial management, and monitoring controls to improve schedule performance. These findings have implications for similar developing construction markets, particularly in Indonesia.
Performance Evaluation of Drainage Systems in Coastal Areas Using Storm Water Management Model: Case Study Milad, Tandya Afilda; Maulana, Mahendra Andiek; Savitri, Yang Ratri
Journal La Multiapp Vol. 7 No. 2 (2026): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v7i2.3055

Abstract

This study analyzes the performance of the urban drainage system in the Sringin Watershed, Semarang City, in response to rainfall runoff and evaluates the effectiveness of pump operation for flood mitigation. The assessment was carried out using a hydrologic and hydraulic modeling approach based on the Storm Water Management Model, supported by rainfall frequency analysis and spatial data processing. Design storms with ten‑year and twenty‑five‑year return periods were developed and applied to simulate system behavior under scenarios without pumps and with pump capacities of ten cubic meters per second and twenty‑five cubic meters per second. The results show that both return periods produce similar hydrologic responses, with peak inflow discharges ranging from fifty‑two to fifty‑five cubic meters per second and maximum storage volumes without pumping reaching forty‑six to forty‑seven percent of total capacity. The operation of a ten cubic meter per second pump effectively maintains water levels below the full‑storage elevation, while a twenty‑five cubic meter per second pump primarily accelerates drainage without significantly improving peak‑level control. These findings indicate that the ten‑year return period combined with a ten cubic meter per second pump provides the most efficient and practical design basis for current conditions, whereas the twenty‑five‑year return period is more suitable for evaluating extreme scenarios and long‑term resilience needs.
Leaf Type Recognition System Using Image Processing Method Using Convolutional Neural Network Algorithm Kolauw, Evan; Hasibuan, Alfiansyah; Kumajas, Sondy C
Journal La Multiapp Vol. 7 No. 2 (2026): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v7i2.3057

Abstract

A digital image-based leaf recognition system is one of the modern solutions in the fields of botany and agriculture to identify plants automatically. This study developed a leaf recognition system using image processing methods and Convolutional Neural Network (CNN) algorithms. CNN was chosen because of its ability to independently extract features through convolution layers, thus capturing important visual patterns such as shape, edges, textures, and leaf veins without requiring manual feature engineering processes. The research dataset consists of a collection of leaf images from several types of plants obtained through direct photo-taking and public dataset sources. Each image goes through a pre-processing stage, including cropping, resizing, image quality enhancement, and pixel normalization to ensure data consistency before entering the training stage. The CNN model is designed with several convolutional layers, pooling, activation functions, and fully connected layers to produce optimal classification performance. Model training is carried out by dividing training and testing data, as well as augmentation techniques to increase image variation. System performance is evaluated using accuracy, precision, recall, and confusion matrix. The test results show that the CNN model is able to recognize leaf types with a high level of accuracy and is stable under various test conditions, including variations in lighting and shooting angles. Overall, this study proves that CNN is an effective and reliable approach in building an automatic leaf recognition system. This system has the potential to be applied in the fields of precision agriculture, mobile application-based plant identification, and botanical research that require speed and accuracy in plant classification.
Multivariate Water Stress Index Model for Predicting Water Vulnerability Pattiraja, Agustinus Haryanto; Seran, Srisanti LMF; Nurdin, Hamdan; Sulistiowati , Sulistiowati; Seran, Stefanus G Engky; Tokan, Fransiska Adinda B
Journal La Multiapp Vol. 7 No. 2 (2026): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v7i2.3072

Abstract

Sabu Raijua Regency is a semi-arid island region with limited water resources and increasing water demand pressure, thus potentially experiencing high water vulnerability. This study aims to develop a multivariate Water Stress Index (WSI) model to analyze the dominant factors causing water stress and predict the level of water vulnerability in the medium to long term on Sabu Island. The study uses a predictive quantitative approach by combining multivariate regression analysis and spatial analysis based on Geographic Information Systems (GIS). The WSI value for the base year 2023 and the projection for 2033 were calculated using the Water to Availability (WTA) method which has been validated through the reliable discharge from the FJ Mock simulation results and field data. Eight independent variables were analyzed, including population density, water demand, dry spell and wet spell conditions, water availability, and clean water service coverage. The analysis results show that water demand (X3) is the most dominant factor in increasing the WSI value, while water availability (X7) plays a significant role in reducing water stress. Seasonal climate variables and clean water service coverage show relatively weak statistical effects. Spatial analysis identified West Sabu District as the area with the highest and persistent water stress, while Central Sabu and Sabu Liae Districts were at medium vulnerability levels, and Hawu Mehara and East Sabu were relatively lower.

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