Journal La Multiapp
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
<![CDATA[Literature Review on Vehicle Routing Problem: Approaches, Algorithms and Current Challenges ]]>
<![CDATA[Pangaribuan, Mery Andani]]>;
<![CDATA[Hidayati, Juliza]]>;
<![CDATA[Nasution, Harmein]]>
<![CDATA[ Journal La Multiapp Vol. 6 No. 6 (2025): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v6i6.2382
<![CDATA[The Vehicle Routing Problem (VRP) is one of the basic combinatorial optimization problems that takes a central place in the sphere of logistics, transportation, and supply-chain management. A systematic literature review (SLR) of VRP scholarship dated 2000 to 2025 is conducted herein, where over 500,000 publications are analyzed to carry out the study of VRP solutions evolution and methodological advancements as well as their practical use. The results highlight the current popularity of metaheuristic algorithms, such as Ant Colony Optimization (ACO), Genetic Algorithms (GA), and Particle Swarm Optimization (PSO), in solving complex variants of VRP, in particular, the Capacitated Vehicle Routing Problem (CVRP) and the Vehicle Routing Problem with Time Windows (VRPTW). The combination of real-time data streams, machine-learning methods and adaptive algorithms represents a revolutionary track, and helps to develop more active and responsive VRP models. Moreover, increased attention to sustainability and green logistics has triggered the development of the eco-efficient VRP models, which combine the use of electric vehicles (EVs) and energy-consumption optimization. The spread of autonomous vehicles presents new opportunities and threats to future VRP solutions, particularly in the area of urban freight and last-mile delivery. In conclusion, the review outlines future streams of research, highlighting the need to find adaptive, sustainable, and autonomous VRP models that can resolve the growing complexities in the modern world of logistics.]]>
<![CDATA[Application of SVM and Naive Bayes with PSO for the Classification of Saloka Amusement Park Reviews ]]>
<![CDATA[Putri, Indira Alifia]]>;
<![CDATA[Umam, Khothibul]]>;
<![CDATA[Handayani, Maya Rini]]>;
<![CDATA[Mustofa, Hery]]>
<![CDATA[ Journal La Multiapp Vol. 6 No. 6 (2025): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v6i6.2505
<![CDATA[Visitor opinions on tourist destinations can be evaluated through sentiment analysis based on textual reviews. This study aimed to compare the performance of Support Vector Machine (SVM) and Naive Bayes (NB) algorithms in classifying visitor sentiments toward reviews of Saloka Theme Park, while also assessing the impact of parameter optimization using Particle Swarm Optimization (PSO). A total of 740 reviews were collected from the Traveloka platform and underwent text preprocessing. The optimization process targeted key parameters of each algorithm to improve the F1-score. Experimental results showed that the unoptimized SVM achieved an accuracy of 89 percent, while NB reached 86 percent. After applying PSO, SVM's accuracy dropped to 84 percent, whereas NB improved to 85 percent with more balanced classification across sentiment classes. These results recommend the integration of Naive Bayes with Particle Swarm Optimization as a potential approach for sentiment classification of tourism reviews, particularly in the case study of Saloka Theme Park.]]>
<![CDATA[Cost Optimization Through Value Engineering and Risk Analysis in Industrial Building Retrofitting Projects ]]>
<![CDATA[Trisamiyanto, Ferdinandus Danu]]>;
<![CDATA[Susetyo, Budi]]>
<![CDATA[ Journal La Multiapp Vol. 6 No. 6 (2025): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v6i6.2515
<![CDATA[Retrofitting projects in industrial facilities are often prone to delays and cost overruns due to various technical, logistical, and operational risks. These challenges include limited working access, delayed material delivery, and regulatory constraints, all of which can significantly affect project efficiency and cost performance. This study aims to optimize project costs by integrating value engineering and risk analysis methods in retrofitting construction. A mixed-method approach was employed, combining case studies with statistical analysis using Structural Equation Modeling – Partial Least Squares (SEM-PLS). Data were collected through surveys, expert interviews, field observations, and project documentation. The findings indicate that the integration of value engineering and risk analysis effectively reduces project costs without compromising quality. The application of value engineering resulted in an alternative solution using fire-rated drywall, which led to a cost saving of approximately IDR 5.36 billion or 9.63 percent of the original estimated cost. Additionally, the Life Cycle Cost (LCC) analysis showed that this alternative provided a more economical long-term solution, with a life cycle cost difference of 13.73 percent compared to the baseline material. These results highlight the practical benefits of integrating VE and risk management, offering a structured and data-driven framework for achieving cost-effective and sustainable outcomes in complex industrial retrofitting projects.]]>
<![CDATA[Transforming Building Infrastructure into Communication Systems for Smart City: A Conceptual Analysis of Metallic Structures as Antennas ]]>
<![CDATA[Zain, Nurmayanti]]>;
<![CDATA[Arifin, Farhan Rezki]]>;
<![CDATA[Emakarim, Lompo Ramos]]>
<![CDATA[ Journal La Multiapp Vol. 6 No. 6 (2025): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v6i6.2431
<![CDATA[The transformation of building infrastructure into intelligent communication systems is a key enabler of smart city development. This paper investigates the feasibility of utilizing metallic structural elements such as steel reinforcement bars, hollow sections, and galvanized steel as embedded antenna within building frameworks. To provide validated evidence, this work incorporates full-wave electromagnetic simulations using Ansys HFSS to analyze resonance behavior, impedance matching, radiation patterns, and gain performance in the sub-GHz band, particularly around 700 MHz for IoT applications. The simulation results demonstrate that selected building materials can achieve stable resonance and nearly omnidirectional radiation characteristics, with realized gains up to 0.47 dBi and bandwidths sufficient for LPWAN technologies such as NB-IoT and LoRaWAN. These findings confirm the dual functionality of structural metals, offering both mechanical strength and communication capability. The study provides a validated basis for future experimental prototyping and integration of antenna- embedded infrastructures in smart building environments.]]>
<![CDATA[Analysis of Furniture Product Defects Using Fault Tree Analysis and Root Cause Analysis Methods ]]>
<![CDATA[Anasari, Sofia Fitri]]>;
<![CDATA[Rochmoeljati, Rr.]]>
<![CDATA[ Journal La Multiapp Vol. 6 No. 6 (2025): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v6i6.2227
<![CDATA[PT WW is a furniture company that uses teak wood as its main material. Factory 1 often experiences product defects because it handles the initial production stage. This study focuses on the SP-15 chair, the company’s best-selling product, which has a defect rate of 15.2%, far above the company tolerance of 5%. The research aims to reduce these defects using the Fault Tree Analysis (FTA) method and provide improvement recommendations. Observations revealed three defect categories with eleven basic causes. The most dominant defect is rupture, with 2726 units and a probability of 0.0085 or 0.85%. Meanwhile, the lowest defect type is incorrect process, with 835 units and a probability of 0.0034 or 0.34%. Because rupture has the highest probability, improvement efforts are urgently needed. Proposed corrective actions include developing and applying SOPs for wood processing, installing visual guides in the work area, establishing standard work procedures, and providing short operator training. Additional recommendations include routine technical training and competency tests, guidelines for machine pressure settings based on wood type, and operator instruction on adjustment. Regular maintenance schedules should also be established, with visual operation guides placed near machines to ensure operators follow correct steps. These efforts are expected to reduce defects and improve the quality of SP-15 chair production at PT WW.]]>
<![CDATA[Productivity Analysis of Production Department with Objective Matrix Method ]]>
<![CDATA[Lumban Gaol, Kristine]]>;
<![CDATA[Aryanny, Enny]]>
<![CDATA[ Journal La Multiapp Vol. 6 No. 6 (2025): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v6i6.2234
<![CDATA[PT XYZ is one of the international branded manufacturing companies engaged in the shoe industry and produces various brands of shoes. In 2024 the company's production on line 7 which produces Brooks brand shoes experienced a decrease in production results which caused the production target not to be achieved. From the production target of 526,624 units of Brooks brand shoes that have been targeted, line 7 production is only able to produce 473,405 units of shoes so that there is a decrease in the production of Brooks shoes by 10.10%. This research method used is Objective Matrix (OMAX). The results showed that the level of partial productivity in the production unit fluctuated with an increase and decrease in each period. Proposed improvements to increase productivity on line 7 are the establishment of a raw material inspection division with an analysis report (LA), integration of manufacturing information systems and ERP, and utilization of AI and IoT sensors for production efficiency.]]>
<![CDATA[Product Defect Analysis of PDH Shirts Using Fault Tree Analysis and Failure Mode and Effect Analysis ]]>
<![CDATA[Siregar, Rendi Robintang]]>;
<![CDATA[Aryanny, Enny]]>
<![CDATA[ Journal La Multiapp Vol. 6 No. 6 (2025): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v6i6.2235
<![CDATA[CV. Graha Konveksindo Sidoarjo is a manufacturing company that produces garments, with PDH shirts as one of its products. Problems identified at CV. Graha Konveksindo include defects in PDH shirts, totaling 891 pieces, with a defect rate of 12.95 %. This study aims to determine the types and causes of defects and provide suggestions for improvement. The methods used are Fault Tree Analysis (FTA) and Failure Mode and Effect Analysis (FMEA). Based on the study results, four types of defects were found: reverse embroidery with an occurrence probability of 3.53%, untidy stitches with an occurrence probability of 3.34%, off-center emblems with an occurrence probability of 2.36%, and stains with an occurrence probability of 3.13%. Across these defect types, 15 root causes were identified as contributing factors. From the FMEA calculation results, the highest Risk Priority Number (RPN) was found in untidy stitch defects at 252, followed by the reverse embroidery defects emblem defects at 240, off center emblem defects at 210, and stain defects at 160. Some recommended improvement proposals to reduce product defects include providing operator training, conducting briefings before production, and routinely checking sewing and embroidery machines.]]>
<![CDATA[Waste Analysis In CPO Production Using Lean Six Sigma ]]>
<![CDATA[Nababan, Yohanes]]>;
<![CDATA[Rochmoeljati, Rochmoeljati]]>
<![CDATA[ Journal La Multiapp Vol. 6 No. 6 (2025): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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<![CDATA[PT XYZ is a manufacturing company engaged in the production of Crude Palm Oil (CPO). In its production process, a significant amount of waste due to product defects is still found. This can be seen from the production parameters recorded from January to June 2024. Based on 137 samples taken over six months, 132 samples did not meet the company's established standards across four parameters. This study aims to determine the types of waste occurring in the CPO production process, assess the sigma level, provide waste reduction recommendations, and minimize non-value-added activities. The study uses the Lean Six Sigma method. It begins by identifying waste in the CPO production process, with the most dominant forms being defects, overproduction, and waiting. The sigma level of the CPO production process at PT XYZ was found to be 2.20, with a DPMO (Defects Per Million Opportunities) of 240,277.8, which falls into the "good" category based on the average performance of the palm oil industry in Indonesia. Further analysis was conducted to identify the root causes of defects using a fishbone diagram. Improvement proposals were developed using the Failure Mode and Effect Analysis (FMEA) tool. With the design of Process Activity Mapping (PAM) and Big Picture Mapping, the lead time was successfully reduced from 807.22 minutes to 728.88 minutes.]]>
<![CDATA[Analysis of Waste in the 3 Kg LPG Gas Delivery Process Using the Lean Distribution Method ]]>
<![CDATA[Inrianto, Priyatna Septedi]]>;
<![CDATA[Pulansari, Farida]]>;
<![CDATA[Dewi, Sinta]]>
<![CDATA[ Journal La Multiapp Vol. 6 No. 6 (2025): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v6i6.2254
<![CDATA[This study aims to identify waste in the 3 kg LPG delivery process at PT Nahatolu Miragas Prima and provide improvement proposals to improve distribution efficiency. The main problem is the delivery lead time that exceeds the estimated ideal time, causing delays to distribution partners. The method used is lean distribution with steps such as data collection of the distribution process, process flow mapping using Value Stream Mapping, and identification of waste based on 8 types of waste. Weighting was done through a questionnaire to determine the most dominant waste, followed by cause analysis using fishbone diagrams and formulation of improvement proposals using the 5W+1H approach. The results showed that the main wastes were in the waste activities of waiting, excess processing, and non-utilized talent. The application of future stream mapping shows the potential to significantly reduce distribution time by reducing the lead time of the distribution process from 732 minutes to 574 minutes. In conclusion, the lean distribution method is effectively used to identify and reduce waste in the LPG distribution flow by increasing the activity of the 3 Kg LPG distribution process by 21,5%.]]>
<![CDATA[Study of Material Flow Analysis Mapping in Supply Management Chain for the Management of Non Functional Device Transformers ]]>
<![CDATA[Syafitri, Annisa Maudi]]>;
<![CDATA[Pulansari, Farida]]>
<![CDATA[ Journal La Multiapp Vol. 6 No. 6 (2025): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v6i6.2277
<![CDATA[This research investigates the optimization of supply chain management for Non-Functional Device (NFD) transformers at PT XYZ through the integration of Material Flow Analysis (MFA) and Analytic Hierarchy Process (AHP). The study addresses the issue of material accumulation and environmental impact arising from inefficient management of decommissioned transformers. MFA to model and evaluate three management scenarios based on mass flow and carbon emissions, while AHP facilitated decision-making by prioritizing five key criteria and eleven sub-criteria. Data were collected through interviews, questionnaires, and internal company records. The results show that Scenario 3 eaturing transformer oil regeneration and component reuse yielded the lowest carbon emissions (101.981 kg CO₂/month) and the highest priority score (0.628) in AHP analysis, with regulatory compliance emerging as the most critical factor. This indicates that Scenario 3 offers the most sustainable and efficient strategy, enabling the company to reduce emissions, recover material value, and improve overall supply chain performance]]>
