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Journal La Multiapp
Published by Newinera Publisher
ISSN : 27163865     EISSN : 27211290     DOI : https://doi.org/10.37899/journallamultiapp
Core Subject : Engineering,
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture 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.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 274 Documents
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Analysis Defect Products in Silencers Using the New Seven Tools Method Annandita, Alifia Rizky; Rochmoeljati, Rr.
Journal La Multiapp Vol. 6 No. 2 (2025): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v6i2.1986

Abstract

Quality is important for a product so that it can have more value than other products. To maintain quality, quality assurance (quality) is required. As is the case with silencer products produced by CV. Nyoto Plastik, silencer is a product that must maintain its quality value. Therefore, many defects in silencer products must be repaired by analyzing the causes of the defects. Based on research, the average defect in this silencer product reaches 10% within one year. New Seven Tools is a method for finding out the causes of defects based on humans, methods, materials, machines or the environment by using the seven tools contained in it. Therefore, this research aims to help maintain the quality of silencers by analyzing the causes of defects and providing suggestions for improvements to minimize defects that occur using the New Seven Tools method.
Analysis of Waste in the Production System with the Approach Lean Manufacturing Method Utomo, Prastyo; Pudji, Endang
Journal La Multiapp Vol. 6 No. 2 (2025): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v6i2.1999

Abstract

Improving the production process needs to be done continuously and continuously in order to minimize all activities that consume time but do not contribute directly to the value of the products produced. PT Cipta Oggi is a manufacturing company that makes furniture products which has a major problem, namely the low value of Process Cycle Efficiency, which the company should have a PCE value of at least 50%. The use of lean manufacturing methods with the help of VSM is used to reduce waste in order to increase the PCE value. There are 22 non-added value activities with a time range of 427 minutes that can be cut. Where the production time was originally 1353 minutes to 926 minutes which had an impact on increasing Process Cycle Efficiency which was originally 46.8% to 68.4%. Based on Failure Mode and Effect Analysis (FMEA), it is known that the main root cause that has the highest RPN value is the Overprocessing waste with a score of 420 and the proposed improvements in order to reduce this waste are the need for safe storage management that can reduce the risk of damage to goods which requires additional processes, namely rework and additional human resources are needed in the inspection process in order to reduce the number of rework.
Sentiment Analysis of Bamboo Charcoal: Comparing Machine Learning Algorithms for Effective Insights Agustine, Giovanni Ega; Jayadi, Riyanto
Journal La Multiapp Vol. 6 No. 2 (2025): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v6i2.2010

Abstract

This research aims to analyze sentiments toward bamboo charcoal on social media, with a focus on public perception in the global market in English. Using data collected from the social media platform X, this study applies various machine learning algorithms, including Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Deep Learning, Naïve Bayes, Decision Tree, and Gradient Boosted Trees, with TF-IDF as the text representation. The analysis reveals that the SVM model achieved the most accurate result of 92.33%, demonstrating its effectiveness in sentiment detection. The study also found that the KNN model performed well, achieving an accuracy of 92.26%, although slightly lower than SVM. These findings highlight the growing interest in bamboo charcoal as a sustainable product, reflecting positive sentiments in the data. Additionally, the Deep Learning model also showed promising results, although it was slightly less effective than SVM and KNN. However, there were also notable concerns regarding the environmental impact of bamboo harvesting, which were primarily expressed in posts. The Decision Tree model, while useful, did not perform as well as the other models, indicating the need for further refinement. Future research could explore a broader range of social media platforms, models, and languages to gain a more comprehensive understanding of global perceptions. Furthermore, integrating sentiment analysis with real-time monitoring could help stakeholders respond more effectively to shifts in public opinion.
Design of a Web-Based Citizen Complaint System in Increasing Citizen Participation in the Village Development Process Ningrum, Diah Ayu Cahya; Riadi, Aditya Akbar; Susanto, Arief
Journal La Multiapp Vol. 6 No. 2 (2025): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v6i2.2039

Abstract

Jekulo Village faces challenges in managing citizen complaints and grievances due to limited physical infrastructure and time. The conventional complaint mechanism is often ineffective in accommodating citizen aspirations in a transparent and responsive manner. The manual complaint recording and resolution process also causes complaint handling to be slow and less organized. This paper aims to discuss the importance of implementing a web-based citizen complaint system to increase community participation in village development. This system is designed so that residents can submit complaints, grievances, and suggestions more easily and efficiently, while also allowing the village government to respond to complaints more quickly and accurately. With a technology-based system, communication between residents and the village government can run more transparently, and increase accountability in handling complaints. The results of the development of a web-based citizen complaint system in Jekulo Village show increased efficiency in handling public complaints. This system accelerates the process of receiving, verifying, and resolving citizen complaints, so that problems can be handled more quickly and accurately. In addition, transparency in resolving complaints increases, which has an impact on increasing citizen trust in the village government. With the real-time complaint status monitoring feature, residents feel more involved in the village development process. The system also provides data that can be analyzed to identify patterns of problems that often occur, so that village governments can take preventive steps to resolve recurring issues. Overall, the system is an effective tool in strengthening community participation and building villages that are more inclusive and responsive to the needs of their citizens.
Posyandu Information System in Payaman Village to Optimize Web-Based Health Services for Toddlers and the Elderly Sugiarto, Elmalia Risma Putri; Riadi, Aditya Akbar; Susanto, Arief
Journal La Multiapp Vol. 6 No. 2 (2025): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v6i2.2042

Abstract

The information system at Payaman Village Posyandu is currently still done manually by recording data using paper, making it vulnerable to errors in data processing and storage. This approach is less efficient, especially in managing registration data for toddlers and the elderly, as well as recording health history which is often not well documented. To overcome this problem, a website-based information system was developed which aims to increase efficiency and accuracy in the Posyandu administration process. This system is designed to make it easier to register participants, monitor the growth of toddlers and the health of the elderly in a more structured and well documented manner and carried out well by staff. The main users of this system are posyandu officers and village midwives who have access to health data and patient examination history. This system was built using the Waterfall software development method, with PHP and MySQL-based technology as the database. This system allows online registration to be carried out by Posyandu officers, central management of health data, and automatic creation of health history recapitulation reports. With this system, the Posyandu service process can be carried out more effectively, efficiently and transparently. In addition, the data stored in the system can be used for more accurate analysis of village community health. The implementation of this system is expected to improve the quality of health services at the Payaman Village Posyandu, reduce the risk of recording errors, and provide benefits for health workers in monitoring patient conditions on an ongoing basis.
Implementation of Machine Learning-Based Classification Model in Employee Recruitment Decision Prediction Adillah, Muhammad Fauzan Nur; Suakanto, Sinung; Utama, Nur Ichsan
Journal La Multiapp Vol. 6 No. 2 (2025): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v6i2.2050

Abstract

Employees are vital assets for any organization, and accurate recruitment decision-making is crucial for the organization's long-term success. Incorrect decisions can lead to high costs due to re-hiring processes, onboarding, and decreased productivity. This study aims to develop a recruitment decision prediction model using data obtained from the Final Results of the 2024 CPNS Recruitment in the Ministry of Finance. The data includes attributes such as educational background, age, GPA, SKD Score, and SKB Score. To understand the relationships between variables, correlation analysis was conducted using a correlation matrix and heatmap visualization. Additionally, data exploration was performed using histograms to show the influence of attributes on recruitment decisions. This study employs five machine learning algorithms for prediction: Linear Support Vector Machine, Decision Tree (C5.0), Random Forest, k-Nearest Neighbor (k-NN), and Naïve Bayes Classifier. The results indicate that some attributes significantly influence recruitment decisions, and machine learning models can identify candidates who are more suitable for the available positions. Among the five models tested, Naïve Bayes proved to be the most effective, achieving an accuracy of 88% and an AUC of 0.97, demonstrating its strong performance in distinguishing positive and negative classes. The key factors contributing to the model's success include relevant feature selection, data quality, as well as appropriate preprocessing and validation techniques. This model is expected to enhance objectivity, efficiency, and accuracy in employee recruitment processes, thereby assisting organizations in making more precise and fair decisions.
Prediction of Electrical Energy Needs for Capital City of Central Java Based on Backpropagation and Linear Regression Akbar, Alfin Aulia; Haddin, Muhammad
Journal La Multiapp Vol. 6 No. 2 (2025): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v6i2.2061

Abstract

This study discusses the prediction of electricity needs according to population growth. The model is determined by knowing the population and electricity needs. The parameters determined include: population, number of electricity consumers, energy consumption growth and electricity load factor for eleven years (2012-2023). The back propagation (BP) method and linear regression are used to help predict electricity needs for the next five years (2025-2030) with the BP architecture determined by three hidden layers and the number of neurons 12, 10 and 1. The object of the study was determined to be Semarang City, Indonesia. The results show that BP and linear regression can be used to predict electricity consumption needs in various sectors accurately. This is evidenced by the MAPE value below 10% and the MSE value of 2,65 x10-10 in the household sector, MSE 3,83 x 10-10 in the business sector, MSE 2,41 x 10-7 in the industrial sector, and MSE 3,6 x 10-12 in the public sector. The BP model produces predicted outputs of electrical energy in 2030 in the household sector of 1.104.140 MWH, the business sector of 843.757 MWH, the industrial sector of 1.027.790 MWH and the public sector of 375.974 MWH. The predicted increase in all sectors of electrical energy results in a total percentage of 54.21% for power sufficiency in 2030, so a thorough planning study is needed to meet electrical energy needs in that year.
PROMETHEE Method for Prioritization of Electrical Energy Audit In Industry Agiantoro, Gellen Twin; Haddin, Muhamad; Marlyana, Novi
Journal La Multiapp Vol. 6 No. 2 (2025): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v6i2.2070

Abstract

The problem of electricity in industry is the increasing consumption of electrical energy which results in increasing electricity consumption costs. The solution is how to reduce electrical energy consumption in the factory. The first step is to conduct an electrical energy audit. This research discusses electrical energy audits in industry with the aim of providing recommendations for electrical energy efficiency. The model is determined as an industrial electrical system complete with an electrical loading system. Parameters determined: production machinery, lighting systems, office support equipment, clean water pumps and air conditioners. The PROMETHEE method was used for prioritization in selecting from several alternative energy-saving opportunities. The research stages began with an initial energy audit, calculation of energy consumption intensity (IKE), recapitulation of electrical energy consumption, determination of energy saving opportunities, and PROMETHEE calculation. The PROMETHEE method used with 3 (three) alternatives, namely energy saving opportunities at no cost, low costs energy saving opportunities and high costs energy saving opportunities. As the research object, only the production building at PT Hop Lun Indonesia (HLI), Semarang, Indonesia was determined. The results show that PROMETHEE can be used for electrical energy audits in industry. This is evidenced by the prioritisation of the best recommendation results from the three alternatives, namely the first order in low-cost energy saving opportunities by replacing the type of LED lamp that has the potential to save energy by 2,723 KWH/day, the second order of energy saving opportunities at no cost by socializing to all employees regarding energy savings and conducting periodic maintenance and the last order in high-cost energy saving opportunities by replacing AC Inverters which have the potential to save energy by 390 KWH/day and replacing motors on sewing machines using servo motors which have the potential to save energy by 38,286,400 KWH/day.
A Study of Rain Station Network Distribution Using Artificial Neural Networks Putri, Aradila Tiara; Dermawan, Very; Wahyuni, Sri
Journal La Multiapp Vol. 6 No. 2 (2025): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v6i2.1896

Abstract

Hydrological analysis is an important component in water resources management, especially for planning and controlling water infrastructure. This study evaluates the effectiveness of the rain station network in the Upper Ciliwung Watershed and identifies rain station with maximum accuracy in representing the study area conditions. Rainfall and discharge data were tested using statistical tests to ensure the absence of trends, stationary, persistence, and outliers. The evaluation of the rain station network density was conducted based on WMO guidelines, which determined the Upper Ciliwung Watershed met the criteria with a density of 37.981 km² per rain station. Analysis of rain station network distribution patterns using Artificial Neural Networks (ANN) was conducted with three data divisions (70-20-10, 60-25-15, 50-30-20) and tested at 100, 500, and 1000 epochs. The best results were obtained at 70-20-10 composition with 1000 epochs, showing the smallest relative error of 9.880% and NSE value of 0.983. The most effective rain station combinations are Gadog, Cilember, and Gunung Mas. This research provides recommendations in rain station network optimization to improve the accuracy of hydrological data.
A Survey of Soft Robot Actuation, Sensing, and Application Abdulshaheed, Areej Ghazi; Mahdi, Suhair Ghazi
Journal La Multiapp Vol. 6 No. 3 (2025): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v6i3.1924

Abstract

Because of their fundamentally high adaptability, high compliance, excellent flexibility, and safe and natural interactive features, soft robotics technologies are pointing the path toward robotic capabilities that are essential for a wide range of applications, including manufacturing, manipulation, gripping, human-machine interaction, locomotion, and more. Soft robots are incredibly versatile and lightweight, making them ideal for interacting with delicate things and navigating unstructured spaces. Soft robots have not yet reached their full potential, though; in many aspects, including manipulation and movement, nature still possesses considerably greater sophistication. Future research should concentrate on comprehending the concepts behind the design and operation of soft robots in order to identify what constrains the way they function and impedes their transfer from the lab to real-world settings. Through an analysis of the operation of sophisticated actuation and sensor technologies, this paper offers a current overview of the area. Lastly, examples of the different soft actuators and possibilities for future development are reviewed, along with a number of prospective implementations.

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