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.
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274 Documents
<![CDATA[Standardization of Information Security Management in the Banking Sector using the ISO 27001:2022 Framework ]]>
<![CDATA[Ryanto, Kamil]]>;
<![CDATA[Tundjungsari, Vitri]]>
<![CDATA[ Journal La Multiapp Vol. 5 No. 4 (2024): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v5i4.1399
<![CDATA[This research discusses evaluations related to cyber security standardization in the banking sector at Bank Victoria International Tbk using qualitative methods and data collection techniques, interviews and focus group discussions. The focus of this research is evaluation related to Data Leaks, Threats of Attacks from outside, and Policies for preventing cybercrime in banking using the ISO 27001:2022 Framework. The location of this research was carried out at Bank Victoria International Tbk. The location for this research was chosen because Bank Victoria is one of the banks that is currently carrying out a preventive implementation process in preventing cybercrime by implementing ISO 27001:2022 related to Cyber Security. The problems that will be explained in this thesis research are First, how does PT. Bank Victoria is taking precautions regarding data leaks using the ISO 27001:2022 framework (1). Second, how does PT Bank Victoria carry out monitoring and monitoring related to external threats or attacks that could harm the bank using the ISO 27001:2022 framework (2). Third, how to comply with procedures, policies or regulators related to process flow and security controls for the use of information technology at PT. Bank Victoria uses the ISO 27001:2022 Framework (3). The conclusion of this research is that Bank Victoria International Tbk is still in the stage of improvement in terms of cyber security, although currently PT Bank Victoria is showing good preventive measures by forming a special organizational structure to handle legality issues and implementing cybercrime prevention applications, but this has not been stated in the Policy.]]>
<![CDATA[Bakery Bread Production System Analysis with Failure Mode and Effect Analysis Method: Case Study of the Armina Food Bread Business ]]>
<![CDATA[Pradana, Fauzi Yoga]]>;
<![CDATA[Indiyanto, Rus]]>
<![CDATA[ Journal La Multiapp Vol. 5 No. 3 (2024): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v5i3.1415
<![CDATA[Bread was first developed during the Mesopotamian culture in the Egyptian region 10,000-12,000 years ago. Bread is a food product processed from fermenting wheat flour with yeast or other rising agents, then baking. The development of bread in Egypt then spread to Greece until it finally spread throughout Europe. Armina Food Bread Business in Gresik is a business that operates in the field of bread production. However, Armina Food's bread business experienced problems in bread production which was not optimal and stable, especially in terms of bread sales which experienced a decline due to bread production defects. Research regarding the risks of bread production was carried out at Armina Food Bakery Business using the Failure Mode and Effects Analysis (FMEA) method. FMEA is an analysis technique that identifies production process failures and plans to prevent them from happening again. Bread production risk analysis is carried out by identifying and measuring the risks of fresh bread production. The FMEA method aims to identify risks by considering the criteria of Severity (S), Occurrence (O), and Determination (D). The research results show that the highest risk lies in raw materials (differences in the quality of raw materials from each supplier), production costs (damage to machinery and equipment), and products (competition with other products). Based on risk analysis of bread production using the FMEA method, it was found that the highest risks lie in raw materials, production costs and product.]]>
<![CDATA[Movie Success Prediction Based on Feature and Trailer Comments Using Ensemble+LSTM Model ]]>
<![CDATA[Nadya Sikana]]>;
<![CDATA[Purba, Ronsen]]>
<![CDATA[ Journal La Multiapp Vol. 5 No. 5 (2024): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v5i5.1417
<![CDATA[Predicting the success of a movie is a very important aspect due to the high risks involved in movie production. The challenge lies in the uncertainty within the movie industry and selecting the appropriate machine learning model. We can combine movie features and sentiment analysis from social media using machine learning techniques to achieve movie success prediction. The methods used for predicting based on movie features are Ensemble models (Random Forest + Gradient Boosting). Meanwhile, the methods used for sentiment analysis of trailer comments is LSTM. The evaluation of the models used is based on RMSE and accuracy calculation. The final prediction of success obtains an RMSE of 0,8807 and an accuracy of 91,19%. This represents an improvement from previous research. Further research is recommended to implement the model in the movie industry]]>
<![CDATA[Decision Support System for Determining Extracurricular Interest Using the Naive Bayes Method ]]>
<![CDATA[Azhar, Joehari]]>;
<![CDATA[Hasugian, Abdul Halim]]>
<![CDATA[ Journal La Multiapp Vol. 5 No. 3 (2024): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v5i3.1430
<![CDATA[The Decision Support System (SPK) is a tool that can help individuals make more effective and efficient decisions. In the context of education, SPK can be used to assist students in determining extracurricular specializations that suit their interests and talents. This research aims to develop an SPK to determine extracurricular specializations for students using the Naive Bayes method. The Naive Bayes method was chosen because of its ability to classify based on probability. The data used in this study include student profiles, academic scores, and student interest in various types of extracurriculars. The results of the study show that the SPK developed can provide recommendations for extracurricular specialization with quite high accuracy. In addition, the system is also easy to use and can help students make more informed decisions.]]>
<![CDATA[Numerical Study of Cavitation Phenomenon in a Venturi Tube ]]>
<![CDATA[Rachman, Muhammad Nanda Fatur]]>;
<![CDATA[Rhakasywi, Damora]]>;
<![CDATA[Fahrudin, Fahrudin]]>
<![CDATA[ Journal La Multiapp Vol. 5 No. 4 (2024): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v5i4.1432
<![CDATA[This research aims to understand and numerically analyze the cavitation phenomenon that occurs in Venturi tubes with variations in throat length and pressure changes. This research uses Ansys Fluent 2023 R2 numerical simulation with venturi tube geometries of 25 mm, 30 mm, and 35 mm and pressures of 300,000, 600,000, and 900,000 Pa. A multiphase flow model with water liquid and water vapor is applied to predict cavitation using a mixture model. RANS steady state conditions with the k-ε turbulence model are used to solve the continuity, momentum, energy and volume fraction equations. The Schnerr-Sauer cavitation model calculates the phase transition between water-liquid and water vapor. Geometry varies by reference journal with different converging and diverging angles, outlined in tables and figures. 2D simulations are carried out using a pressure based solver with specified boundary conditions, using the Presto! for pressure solutions, and upwind and Quick schemes for discretization. The results of this research show that 1) Length throat 25 mm has the most stable distribution compared to 30 and 35 mm geometries at a pressure of 600,000 Pa. 2) The cavitation phenomenon is influenced by changes in geometry where at 35 mm geometry greater cavitation occurs in the area near the wall inlet convergent. 3) At a pressure of 900,000 Pa, the cavitation area that forms becomes larger and becomes a critical point in this journal.]]>
<![CDATA[Image Quality Restoration on Historical Artifacts Using Histogram Equalization and Contrast Stretching Methods ]]>
<![CDATA[Aidilia, Yunda]]>;
<![CDATA[Sriani, Sriani]]>
<![CDATA[ Journal La Multiapp Vol. 5 No. 4 (2024): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v5i4.1442
<![CDATA[The aim of this research was to enhance the image quality of historical objects that undergo quality decline such as noise, low contrasting images, and poor sharpness. Contrast stretching and Histogram equalization are two methods of image enhancement which is used to expand and smooth out the grayscale of an image . The purpose of this study is to develop a system for enhancing the quality of images of historical heritage objects applying contrast stretching and histogram equalization techniques. Concerning the selection of the sample in this research, the data is RGB image data with a total of 10 test images in . mat file format and the process employed is in Matlab programming language The stimulation of neuron is in jpg format. The works on the contrast stretching and histogram equalization from the sample 1 to sample 10 image the results were highest on test image_citra_1 with the contrast stretching results on the base of PSNR = 32. DOS, = 61 dB and MSE = 35. 86 Db and PSNR = 19. 13 Db and MSE = 794 . 76 in histogram equalization calculations.]]>
<![CDATA[Real-Time Monitoring System for Peatland Fire Potential Based on Internet of Things ]]>
<![CDATA[Nawawi, Imam Khushthon]]>;
<![CDATA[Al Qibtiya, Mariya]]>;
<![CDATA[Al Azhima, Silmi Ath Thahirah]]>;
<![CDATA[Arief Hakim, Nurul Fahmi]]>
<![CDATA[ Journal La Multiapp Vol. 5 No. 4 (2024): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v5i4.1449
<![CDATA[This research aims to develop a real-time monitoring system for peatland fire potential based on the Internet of Things (IoT) with a focus on early detection of potential peatland fires. The main problem to be solved is the lack of an effective system in the early detection of potential peatland fires, which can cause serious environmental impacts. The method used involves the use of air temperature, air humidity, soil moisture, and fire detection sensors integrated with alarm-based alerts. Data collection is done in real-time to provide a deeper understanding of peatland conditions and potential fire risks. The research results show that the developed system is capable of providing accurate and fast information related to peatland conditions, thus helping to prevent and reduce the impact of peatland fires. With this system, it is expected to increase efficiency in early fire detection and minimize the losses caused by peatland fires.]]>
<![CDATA[Sentiment Analysis towards Full Movie Dirty Vote 2024 in X Using Support Vector Machine Method ]]>
<![CDATA[Azhari, Fajar]]>;
<![CDATA[R, Rakhmat Kurniawan]]>
<![CDATA[ Journal La Multiapp Vol. 5 No. 4 (2024): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v5i4.1459
<![CDATA[Intending to provide a sentiment of the general public towards the X’s “Dirty Vote 2024” movie, this study inspects 1500 tweets scraped from ‘Tweepy’ library using Support Vector Machine (SVM) method. The tweets were preprocessed by text mining process by tokenization, removal of stopwords and word weighting to categorize the tweets into positive and negative sentiments. While using the SVM model, the recognition rate was 86% which means that the model can successfully recognize sentiment patterns in the dataset. However, the model had a 14% overall misclassification rate especially when it came to assessing subtlety or ambiguity in expressions which indicate its weakness in handling complexities inherent in sentiment. Thus, the study affirms a high level of precision in SVM for sentiment analysis The study further pointed out the need to advance advanced natural language processing NLP approaches to enhance the accuracy of models particularly in different real world settings where language adaption is highly volatile. The study also has a relevance to filmmakers and marketers; given that it offered a better understanding of the public response that can help in framing future content creation and advertisement advertisements. Thus, for the increase of accuracy and simply to make the methods more resilient, the future studies should investigate the opportunities of using context-aware embeddings and a hybrid neural network model in the environment of social platforms.]]>
<![CDATA[Implementation of a Convolutional Neural Network Algorithm in Classifying Vegetable Freshness Based on Image ]]>
<![CDATA[Handira, Dysa]]>;
<![CDATA[Hasibuan, Muhammad Siddik]]>
<![CDATA[ Journal La Multiapp Vol. 5 No. 4 (2024): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v5i4.1461
<![CDATA[The purpose of this work is to apply CNN algorithm to a real problem of vegetable freshness identification using image data. Quantitative approach was used for this study and the data source was obtained from Kaggle; it is referred to as Fresh and Stale Images of Fruits and Vegetables with 2,604 images, four categories in total. The CNN model architecture consisted of a basic organization of four successive convolutional layers with associated max-pooling layers that aimed at capturing hierarchical feature representations of the input images. This model was trained using the Adam’s optimizer for 20 iterations with the batch size of 32. Pre-processing of data included image augmentations such as scaling, rotation, flipping which improved the performance of the model. The assessment was done using Confusion Matrix approach and the results show that the proposed system achieved an accuracy of 95%, with a precision of 94%, recall of 93% and F1-score of 93%. From this it can be concluded that the CNN model proposed has achieved the objective of distinguishing fresh and non-fresh vegetables with enough precision to assist in the automation of quality control in agriculture. The conclusion that can be drawn from this study is that AI especially CNNs could be of big help in increasing accuracy and decreasing human factors in the large scale production of food.]]>
<![CDATA[Prototype of Microcontroller Based Water Pump Control System for Lettuce Plants Using Fuzzy Tsukamoto ]]>
<![CDATA[Rifansyah, Mhd. Roji]]>;
<![CDATA[R, Rakhmat Kurniawan]]>
<![CDATA[ Journal La Multiapp Vol. 5 No. 4 (2024): Journal La Multiapp ]]>
Publisher : <![CDATA[Newinera Publisher ]]>
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DOI: 10.37899/journallamultiapp.v5i4.1462
<![CDATA[This research aims to design and implement a water pump control system for lettuce plants using a microcontroller based on the Tsukamoto fuzzy method. The system utilizes soil moisture sensors and DHT11 temperature sensors to monitor and control the water supply for optimal plant growth. The fuzzy logic control involves three stages: fuzzification, rule evaluation, and defuzzification. Experimental results demonstrate the system's effectiveness in maintaining the desired soil moisture levels, thus ensuring optimal conditions for lettuce plant development. The prototype includes components such as Arduino Uno, relays, water pumps, and LCD displays, all of which integrate seamlessly to achieve the desired control outcomes. The study concludes that the designed system can significantly aid in automating water supply processes, thus benefiting small-scale agricultural practices.]]>
