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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 of User Acceptance of the Mobile Application of National Health Insurance Using the UTAUT Model Yoga Anunggita; Suryadi, Akmal
Journal La Multiapp Vol. 5 No. 5 (2024): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v5i5.1463

Abstract

Development technology in the field health own positive impact. On the field Health services are available developed mobile applications Forgive Health services to public by online. The Mobile JKN Application has objective For give service health to community and make it easier power health For give service optimally. On research This analyze about reception user The Mobile JKN application uses the Unified Theory of Acceptance and Use of Technology (UTAUT). Respondent data obtained during spread questionnaire that is as many as 110 respondents. Respondent data Then analyzed using Structural Equation Model (SEM) research results This show that Performance Expectancy (PE) and Social Influence (SI) have an influence significant to Behavioral Intention (BI). However, for Effort Expectancy (EE) it is not influential significant to Behavioral Intention (BI) with t-test values are 2.224, 2.224, and 1.198 respectively. Third variable the can explain influence to Behavioral Intention (BI) was 34.3%. Whereas for Facilitating Conditions (FC) and Behavioral Intention (BI) influence significant towards Use Behavior (UB) with t-test values are 4.013 and 5.636 respectively. As well as second variable the can explain influence on Use Behavior (UB) of 59.3%. So on research explain reception user to use Mobile JKN application with using UTAUT.
Analysis of the Corpus with Naïve Bayes in Determining Sentiment Labeling Aulia, M. Arif; Hasibuan, Muhammad Siddik
Journal La Multiapp Vol. 5 No. 4 (2024): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v5i4.1465

Abstract

The raw form of data is also an issue that creates a lot of problems while attempting to extract useful insight, thus requiring the use of NLP algorithms for text mining. This paper discusses sentiment analysis, with emphasis on user comments regarding cars on the microblog X that was formerly known as Twitter, work which employs Naïve Bayes Algorithm in text categorisation. The steps involved are the formation of the corpus and use of InsetLexicon dictionary for sentiment analysis with the help of weighted keywords and then going through pre-processing of the text data that includes cleaning, normalization and tokenization. The Naive Bayes algorithm estimates the probability of text under positive or negative sentiment class. The work shows that the “Comfortable” component of car reviews obtained the highest score in terms of recall, precision, and F1-score, which equals 0.83, 0.85, and 0.563, and the second set consists of 87 instances overall including an overall data set accuracy of 71%. The result validates the use of lexicon-based sentiment analysis in specific domain and at the same time exposes the weakness of the Naive Bayes, especially with complex word dependencies. Further studies should incorporate more advanced models and suitable dictionaries which facilitate sentiment analysis in ever-shifting online media settings.
Measurement of Centroid Distance in Determining Stunting Clusters Lubis, Muhammad Taufik Hakim; Hasibuan, Muhammad Siddik
Journal La Multiapp Vol. 5 No. 3 (2024): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v5i3.1479

Abstract

This study evaluates the effectiveness of distance measurement methods in the K-Means clustering algorithm for determining stunting clusters by comparing Euclidean and Manhattan distances. The goal is to obtain optimal cluster centroids and the closest distances within each cluster. The study uses a sample of 552 records with 3 attributes. The process begins with applying the K-Means algorithm, followed by distance measurement using Euclidean and Manhattan methods. Iterations are performed until optimal results are achieved. Evaluation is conducted using Sum of Squared Errors (SSE) to assess the total error within clusters and Mean Squared Error (MSE) to calculate the average nearest distance within clusters. The results indicate that both SSE and MSE methods are effective in identifying cluster quality and provide insights into the accuracy and effectiveness of Euclidean and Manhattan methods in clustering.
Key Factors of Urban Public Transportation Services Implementation in Indonesia: A Knowledge Management Perspectives Adhitama, Raihansyah Yoga; Giffari, Rafi; Sensuse, Dana Indra; Eitiveni, Imairi; Hidayat, Deden Sumirat; Indria, Sofi
Journal La Multiapp Vol. 5 No. 5 (2024): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v5i5.1481

Abstract

It is well-recognized that the availability of public transportation has a significant impact on urban transportation networks. In Indonesia, the government is still having difficulties to establish a reliable public transportation system. One important aspect that can be utilized in establishing a reliable public transportation system is to utilize knowledge management in its services. This study aims to identify key factors from knowledge management perspectives related to the implementation of public transportation services. To achieve this objective, this study conducted qualitative research on 12 users of public transportation services in Indonesia. The results of this study indicate that there are several key factors related to the implementation of public transportation services from knowledge management perspectives, such as Real-Time Information, Digital Accessibility, User Engagement and Trust, Platform Functionality and Quality, Digital Inclusive Strategy, Knowledge Dissemination Method, Help Desk Reliability, and Knowledgeable Officer.
Classification of Crude Palm Oil Quality Eligibility Using Support Vector Machine Algorithm Rafiqah, Intan Nur; Sriani, Sriani
Journal La Multiapp Vol. 5 No. 4 (2024): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v5i4.1486

Abstract

The study focuses on an examination of the applicability of the Support Vector Machine (SVM) algorithm and its implication for the classification of the quality of the Crude Palm Oil (CPO) produced by PT. PP London Sumatra Indonesia Tbk. The authentic quality parameters: Water (VM), Dirt, and Free Fatty Acid (FFA) were chosen to train the SVM model which was tested on the data of 2020–2022 and containing 1,095 records. The research utilized Google Colab Python Notebooks for the analysis of data, resulting to an accuracy of 84. 15%. This indicates that SVM is a reliable technique to work with complicated, multi variet data,; which can be quite helpful in the CPO quality classification, where traditional algorithms may not be efficient. Data preprocessing including normalization and outlier detection has been cited as some of the ways that would improve the performance of the model as highlighted in this study. Comparing the results with other machine learning algorithms such as Random Forest and Neural networks proved the efficiency of SVM even though there were misclassification made. The result also suggests that SVM has a strong capability to support the quality assurance activities in the palm oil industry by eliminating human intervention and increasing the working productivity. Further study could continue in the directions of incorporating the SVM model with other methods of machine learning for even better enhancement of the CPO quality assessment.
Application of Design Thinking Method in Designing the User Interface Prototype for the Website of the Informatics Engineering Study Program at Dian Nuswantoro University Mahardika, Pramesthi Qisthia Hanum; Luthfiarta, Ardytha
Journal La Multiapp Vol. 5 No. 5 (2024): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v5i5.1501

Abstract

In today's era, with the rapid development of technology such as the internet, human work can be significantly aided. This advancement positively impacts the education sector in terms of teaching, learning, and information dissemination. This development increases the use of websites, making the user interface an essential aspect of user comfort. The website of the Informatics Engineering study program at Dian Nuswantoro University has some deficiencies in its user interface. Therefore, the researcher has designed a user interface prototype to facilitate user interaction with the website, using the design thinking method. The designed user interface prototype is expected to address existing problems, meet user needs, and enhance campus services.
Integrating Social Support into the TAM Framework: Effects on ‎E-Learning Usage and Acceptance Wighneswara, Alifiannisa Alyahasna; Yuhana, Umi Laili
Journal La Multiapp Vol. 5 No. 5 (2024): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v5i5.1505

Abstract

This research explores the role of social support in the context of the TAM model in relation to usage and acceptance of e-learning by high school learners as well as a technical usability assessment of e-learning environment. By employing cross sectional survey design and Partial Least Squares Structural Equation Modeling (PLS-SEM analytical technique, we explore the interconnection of social support with perceived usefulness, perceived ease of use, behavioral intention and actual usage. Specifically, the work finds that social support partially mediates students’ reception of e-learning from their perspective of perceived usefulness and its ease of use and that perceived usefulness is deeply seated in behavioral intention on the chosen platform. From the technical analysis, load testing, content delivery and security was examined to determine the effectiveness of the platform. An addition of a content delivery network streamlined page load time and minimized latency issues while on security the implementation of SSL and two factor authentication advanced the security of data. These are tangible technical enhancements accompanied by social support systems which increase the e-learning derived adoption as well as the retention ratios. The implications of the results put emphasis on both social and technical aspects in e-learning system that must be taken into consideration for educators and developers creating efficient and large-scale e-learning system.
Evaluation of Information Technology Governance Maturity Using COBIT 2019: A Case Study on the IT Security Industry Hidayat, Rachmad Syarul; Indrajit , Richardus Eko; Dazki , Erick
Journal La Multiapp Vol. 5 No. 4 (2024): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v5i4.1514

Abstract

This study aims to evaluate the maturity of IT governance in the IT security industry using COBIT 2019. The assessment covered 13 COBIT 2019 domains, namely APO03—Managed Enterprise Architecture, APO07—Managed Human Resources, APO12—Managed Risk, APO13—Managed Security, APO14—Managed Data, BAI02—Managed Requirements Definition, BAI03—Managed Solutions Identification & Build, BAI05—Managed Organizational Change, BAI06—Managed IT Changes, BAI07—Managed IT Change Acceptance and Transitioning, BAI09—Managed Assets, BAI10—Managed Configuration, and BAI11—Managed Projects. The research methodology included observation, domain-based question formulation, RACI interviews, data collection, and question validation testing, with maturity calculation performed using appropriate formulas. Results indicate that most domains are at Level 2 (Managed), with significant contributions to maturity at Levels 3 and 4. Significant gaps were found between the current state and the desired maturity targets for many domains, such as APO03 and BAI03. The percentage contribution from Level 2 is the highest, while contributions from Levels 3 and 4 vary, with very low contributions from Level 5. The total maturity score is 2.49, with percentage contributions from Levels 2, 3, 4, and 5 being 74%, 26%, 11%, and 3%, respectively. Recommendations include improving processes to achieve Levels 3 and 4 across more domains and investing in training and development for relevant teams.
Analysis of Calorific Value of Biopellet Diameter Variations through Proximate Test Asrianti, Nadia Putri; Fahrudin, Fahrudin; Rhakasywi, Damora; Martana, Budhi
Journal La Multiapp Vol. 5 No. 4 (2024): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v5i4.1516

Abstract

This study aims to evaluate the quality of biopellets as biomass energy fuel, focusing on physical and chemical characteristics based on the SNI 8021:2014 standard. The research method used is experimental with a non-factorial Completely Randomized Design (CRD). The raw materials used are a mixture of rambutan wood waste (Nephelium lappaceum L) and bintaro (Cerbera manghas) with tapioca flour as an organic binder. Testing includes proximate analysis (moisture, ash, volatile matter, and fixed carbon) and calorific value using an oxygen bomb calorimeter. The results show that the produced biopellets meet several parameters of the SNI 8021:2014 standard, such as moisture content, volatile matter, and fixed carbon. However, there is significant variation in ash test results among different diameters of biopellets tested. ANOVA test results indicate that mold diameter has a notation that has a significantly affect several biopellet characteristics, such as density and calorific value. This study also observed the potential for increased combustion efficiency of the produced biopellets. The results indicate that the raw material mixture used can reduce pollutant emissions during combustion. The conclusion of this study is that the use of a mixture of rambutan wood waste and bintaro with tapioca flour as an organic binder can produce biopellets with quality that meets standards for biomass energy applications.
Sentiment Analysis of Support for the DPR's Right to Inquiry on the Issue of 2024 Election Fraud Using the Support Vector Machine Method Sephia, Putri Aisyah; Zufria, Ilka
Journal La Multiapp Vol. 5 No. 5 (2024): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v5i5.1523

Abstract

This research aims to analyze public sentiment towards supporting the DPR's right to inquiry in the 2024 Election fraud issue using the Support Vector Machine (SVM) method. Data was obtained from the social media application X which has a wide user base and is relevant to the issue under study. Comments on the application are classified into positive and negative sentiments after going through the pre-processing stage. The SVM method was chosen because of its high ability in text classification based on appropriate kernels. This research shows how much influence the X application has in identifying public sentiment and the effectiveness of the SVM method in sentiment classification. It is hoped that the research results will provide in-depth insight into public sentiment regarding the issue of fraud in the 2024 elections and support better decision making in the context of politics and democracy in Indonesia.

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