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
274 Documents
<![CDATA[Prediction of Mental Health of Elementary School (SD) Students using the Decision Tree Algorithm with K-Fold CV testing in Bone Bolango Regency, Gorontalo Province. ]]>
<![CDATA[Liputo, Salahuddin]]>;
<![CDATA[Tupamahu, Frangky]]>
<![CDATA[ Journal La Multiapp Vol. 5 No. 1 (2024): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v5i1.853
<![CDATA[Mental health is a fundamental component of the WHO definition of health, which means not only being free from disease but also being physically, mentally and socially healthy. Currently, mental health has become a major issue in modern society because if it is good it will enable us to realize our own potential, overcome the normal stresses of life, work productively, and be able to contribute to the society in which we live. In Indonesia, problems related to mental health are related to the lack of mental health detection tools. Meanwhile abroad, much research has been developed regarding mental health detection based on innovative technology using Machine Learning. This research aims to predict mental health using the Social Emotional Health Survey-Secondary (SEHS-S) as a prediction evaluation criterion using Machine Learning with the Decision Tree algorithm method with K-Fold CV testing. The sample in this research was elementary school students in Bone Bolango Regency, Gorontalo Province.]]>
<![CDATA[Effectiveness of the Online Service Management Information System (SIMPONIE) Application in Online Business Licensing Services ]]>
<![CDATA[Gloria Erysa Meilinda Situmorang]]>;
<![CDATA[Muhammad Ganesha Putra]]>;
<![CDATA[Sura Fabio Mangaraja]]>;
<![CDATA[Andi Muhammad Rafi]]>
<![CDATA[ Journal La Multiapp Vol. 4 No. 2 (2023): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v4i2.856
<![CDATA[This research discusses the effectiveness of the SIMPONIE application in improving public services in South Tangerang City according to the information system success measurement developed by William H. Delone and Ephraim R. Mclean (2016). This application is the result of a joint initiative between the Department of Investment and One Stop Integrated Services (DPMPTSP) and the Department of Communication and Information (Diskominfo) of South Tangerang City. SIMPONIE is designed with a number of features that aim to support the licensing process digitally, with the main aim of providing easy access for the public in obtaining business permits, increasing efficiency in the licensing process, and increasing the capability of government departments in serving the public. The features offered by SIMPONIE include the ability to register and apply for business permits online, tracking application status, payment of licensing fees online, notifications and communication between applicants and authorities, as well as electronic data archiving for documentation and reporting. According to research results, the SIMPONIE application has received a positive response from the people of South Tangerang City for many years. This positive reception reflects success in overcoming the challenges faced in business licensing services at the regional level. This success provides a concrete example of how information technology innovation can be used to improve efficiency, transparency and service to the community.]]>
<![CDATA[Enhancing User Authentication with Facial Recognition and Feature-Based Credentials ]]>
<![CDATA[Mohialden, Yasmin Makki]]>;
<![CDATA[Hussien, Nadia Mahmood]]>;
<![CDATA[Ali, Doaa Muhsin Abd]]>
<![CDATA[ Journal La Multiapp Vol. 4 No. 6 (2023): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v4i6.903
<![CDATA[This research proposes a novel and trustworthy user authentication method that creates individualized and trusted credentials based on distinctive facial traits using facial recognition technology. The ability to easily validate user identification across various login methods is provided by this feature. The fundamental elements of this system are face recognition, feature extraction, and the hashing of characteristics to produce usernames and passwords. This method makes use of the OpenCV library, which is free software for computer vision. Additionally, it employs Hashlib for secure hashing and Image-based Deep Learning for Identification (IDLI) technology to extract facial tags. For increased security and dependability, the system mandates a maximum of ten characters for users and passwords. By imposing this restriction, the system increases its resilience by reducing any possible weaknesses in its defense. The policy also generates certificates that are neatly arranged in an Excel file for easy access and management. To improve user data and provide reliable biometric authentication, this study intends to create and implement a recognition system that incorporates cutting-edge approaches such as face feature extraction, feature hashing, and password creation. Additionally, the system has robust security features using face recognition.]]>
<![CDATA[Impact of Supply Chain Integration in Enterprise Resource Planning Systems that Affect Company Performance ]]>
<![CDATA[Zalfa, Dhia]]>
<![CDATA[ Journal La Multiapp Vol. 4 No. 3 (2023): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v4i3.912
<![CDATA[PT Sumber Graha Sejahtera, Way Kanan, Lampung often experiences unfulfilled production targets and customer demands. Many customers give complaints because the number of products sent by the company does not match the desired amount. The purpose of this study was to determine the direct effect of the ERP system on company performance, and the indirect effect of the ERP system on company performance mediated by supplier integration, internal integration, and customer integration. This research uses quantitative methods. The population in this study were all employees at PT Sumber Graha Sejahtera, Way Kanan, Lampung, totaling 340 people. The sample size was calculated using the Yamane and Isaac formula which resulted in 184 employees. Samples were taken using purposive sampling technique. The data analysis technique used is Structural Equation Modeling (SEM)-Partial Least Square (PLS). The results of the study show that ERP has a direct, significant effect on firm performance. In addition, ERP has no significant effect on firm performance through supplier integration, internal integration and customer integration. PT Sumber Graha Sejahtera must improve the management of management resources well, increase performance improvement, and build business innovation, so that corporate decision making can be effective for all related parties. With the implementation of good resource planning, the company will no longer receive complaints from customers.]]>
<![CDATA[Artificial Intelligence and the Silent Pandemic of Antimicrobial Resistance: A Comprehensive Exploration ]]>
<![CDATA[Al Marjani, Mohammed F.]]>;
<![CDATA[Mohammed, Rana K.]]>;
<![CDATA[Ahmed, Ziad O.]]>;
<![CDATA[Mohialden, Yasmin Makki]]>
<![CDATA[ Journal La Multiapp Vol. 5 No. 1 (2024): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v5i1.952
<![CDATA[The rise of antimicrobial resistance (AMR) in the 21st century has made it a worldwide disaster. Due to the fast spread of AMR illnesses and the lack of novel antimicrobials, the silent pandemic is well known. This issue requires a fast and meaningful response, not just speculation. To address this dilemma, deep learning (DL) and machine learning (ML) have become essential in many sectors. As a cornerstone of modern research, machine learning helps handle the many aspects of AMR. AI helps researchers construct clinical decision-support systems by collecting clinical data. These methods enable antimicrobial resistance monitoring and wise use. Additionally, AI applications help research new drugs. AI also excels at synergistic medicine combinations, providing new treatment methods. This paper summarizes our extensive study of AI and the silent epidemic of antibiotic resistance. Through deep learning and machine learning applications across multiple dimensions, we hope to contribute to the proactive management of AMR, moving away from its presentation as a future problem to present-day solutions.]]>
<![CDATA[Analysis of Blended Learning Development in Distance Learning in Variation of Borg & Gall and Addie Models ]]>
<![CDATA[Untoroseto, Dedi]]>;
<![CDATA[Triayudi, Agung]]>
<![CDATA[ Journal La Multiapp Vol. 4 No. 6 (2023): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v4i6.973
<![CDATA[With the success of blended learning and the use of online media on learning outcomes and from article search results, it shows that there have been many articles that contain blended learning and various media uses, and reviews are needed about it by reviewing existing articles or commonly called literature reviews. Borg & Gall and ADDIE models. The Borg & Gall model and ADDIE are two teaching models used in colleges and universities. ADDIE stands for Analyze, Design, Development, Implementation, and Evaluation. In the Borg & Gall model, the steps taken are research and information. Research and information is used to collect information about the need for learning evaluation instruments for learning media development courses for students. In the ADDIE model the steps taken are the same as the original which includes aspects of Analyze, Design, Development, Implementation, and Evaluation. Thus, what is needed in this development is a reference about the product procedure to be developed. The description of the development model of Borg and Gall, described as follows; Educational research and development (R&D) is the process used to develop and validate educational products. The validity of interactive blended learning is: (1) according to expert reviews the content of metrics shows a good category (92%), (2) according to expert reviews learning design is in the good category (88%), (3) according to expert reviews learning media shows a good category (86%), Thus, this interactive blended eLearning does not need to be revised and can be used for further research.]]>
<![CDATA[Design of Forecasting for Perishable Product with Artficial Neural Network ]]>
<![CDATA[Sabhira, Chintya Salwa]]>
<![CDATA[ Journal La Multiapp Vol. 5 No. 1 (2024): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v5i1.1000
<![CDATA[Raw materials are an important part of the manufacturing industry, especially for raw materials that do not last long or have a lifespan. To be able to produce good products, the raw materials used must be of good quality. This happened to company XYZ which operates in the cereal and snack food industry. Inventory control is quite a big challenge for companies. In this year the company experienced losses due to a shortage of finished snacks products, due to finished goods being obsolete due to a lack of accuracy in forecasting snack demand. The research raised forecasting using the Artificial Neural Network method. ANN is known to be able to produce good accuracy values in predicting sales.]]>
<![CDATA[Prediction of Elementary School Students' Mental Health using Decision Tree Algorithm with K-Fold Cross-Validation in Bone Bolango Regency, Gorontalo Province ]]>
<![CDATA[Liputo, Salahuddin]]>;
<![CDATA[Tupamahu, Franky]]>;
<![CDATA[Hasyim, Wahyudin]]>;
<![CDATA[Sabiku, Sri Ariyanti]]>;
<![CDATA[Parman, Rahmawaty]]>;
<![CDATA[Hanapi, Aan]]>
<![CDATA[ Journal La Multiapp Vol. 4 No. 6 (2023): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v4i6.1005
<![CDATA[Mental health is a fundamental component of the World Health Organization's definition of health, encompassing not only freedom from illness but also well-being in physical, mental, and social dimensions. In today's modern society, mental health has become a paramount issue, as its soundness enables individuals to realize their own potential, cope with normal life pressures, work productively, and contribute effectively to their communities. In Indonesia, mental health-related challenges are associated with the absence of a reliable mental health detection tool. Conversely, abroad, there has been a substantial amount of research focused on innovative technology-based mental health detection using Machine Learning. This study aims to predict mental health using the Social Emotional Health Survey-Secondary (SEHS-S) as the evaluation criterion for prediction through Machine Learning. The Decision Tree algorithm is employed, and the prediction model is tested using K-Fold Cross-Validation, resulting in 8 folds with an accuracy rate of 78.61%.]]>
<![CDATA[Algorithm for Detecting Acoustic Traces of Neutrino Decay ]]>
<![CDATA[Belyakov, Askold]]>
<![CDATA[ Journal La Multiapp Vol. 5 No. 2 (2024): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v5i2.1006
<![CDATA[In the articles "Doppler Effect and Acoustic Trails of Neutrinos" and "Neutrinos above the Earth's surface", published in the journal "LA MULTIAPP" on February 25, 2022 and July 12, 2023, I was forced to touch on the astrophysical topic when, in the flow of data obtained in the process Monitoring acoustic noise with a recorder with a Nyquist frequency of 5 kHz, at a depth of 1000 m in the earth's crust, events began to be frequently observed, the shapes and frequencies of which are not typical for seismology and geophysics, and had not previously been observed by anyone. The shape of some events was very similar to the traces of neutrino decay, such as the bipolar pulse and the “diamond”, recorded by acoustic detectors in seawater. Subsequently, when recording high-frequency acoustic processes on the Earth's surface with a recorder with a Nyquist frequency of 50 kHz, events were discovered that were even more similar to traces of neutrino decay. At the same time, a “strange” association of some events of unknown origin with the field extrema of the power electrical network of a large city was discovered. To avoid erroneous conclusions, it is necessary to understand the origin of this “strangeness”.]]>
<![CDATA[Bitcoin Price Prediction Model Development Using Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) ]]>
<![CDATA[Cahyadi, Jonathan]]>;
<![CDATA[Zahra, Amalia]]>
<![CDATA[ Journal La Multiapp Vol. 5 No. 2 (2024): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v5i2.1070
<![CDATA[Cryptocurrency is a virtual currency that can be used as a financial or economic standard, foreign currency reserve, and as a means of payment in some countries. The value that goes up and down every time is not easy to predict using logic. This is a problem for investors, besides that investors lack knowledge about the direction of crypto money movement. In addition, there is no system that can predict the price of Bitcoin, so this can cause investors to take the wrong steps in transactions and can cause losses. To avoid this risk, a system is needed that can predict bitcoin prices using data mining techniques, namely forecasting, the algorithms used are CNN and LSTM. The data used is Bitcoin closing price data from January 1, 2017, to April 26, 2023. The data is divided into 80% training data and 20% testing data. The prediction results are evaluated using MAPE which gets a MAPE value of 0.037 or 3.7% in the CNN algorithm, while the LSTM algorithm gets a value of 0.065 or 6.5%. The MAPE results of the two algorithms are in the MAPE range <10%, so it can be said that the ability of the forecasting model is very good so that it can be used as a reference to determine the prediction of bitcoin prices in the next few periods.]]>
