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INDONESIA
Jurnal Sains Dan Teknologi (SAINTEKBU)
Published by Universitas KH. A. Wahab Hasbullah
ISSN : 19797141     EISSN : 25411942     DOI : https://doi.org/10.32764/saintekbu.v10i1.157
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Library & Information Science
JURNAL SAINTEKBU adalah Jurnal ilmiah yang mewadahi hasil penelitian bidang informatika, ilmu komputer, teknologi komputer yang diterbitkan oleh Universitas KH. A. Wahab Hasbullah (UNWAHA)
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 293 Documents
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YouTube Comment Sentiment Analysis on Deddy Corbuzier and BEM UI’s Podcast Using TF-IDF and Naïve Bayes Al Basyary, Muhammad Rafi
SAINTEKBU Vol. 16 No. 02 (2024): Vol. 16 No. 02 August 2024
Publisher : KH. A. Wahab Hasbullah University

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Abstract

The development of technology and the popularity of digital platforms such as Youtube have had a significant impact on the dissemination of information, especially related to the idea of a presidential candidate in the 2024 election. For example, Deddy Corbuzier actively uploads a podcast video on his Youtube channel, together with the chairman of BEM UI, to discuss the ideas of each presidential candidate. In this study, sentiment analysis was carried out on more than 2.6 million Youtube user comments on the video using the Naïve Bayes Classifier algorithm. This algorithm has proven effective in previous studies, showing high accuracy in classifying people's sentiments. The research methodology includes data labeling, text preprocessing, word weighting with TF-IDF, data validation using k-fold cross validation, and data testing. The results of the sentiment analysis revealed that more than fifty percent of the comments were positive, while some remained neutral. The data visualization process using word cloud provides a clear picture of the topics most talked about by the public, with the word "Leader" dominating. Although the accuracy of the Naïve Bayes Classifier in this study reached 57.6%, this study provides valuable insights into the public's view of the idea of a presidential candidate. Further development may involve the use of other algorithms as comparators to improve the accuracy of sentiment analysis.
Analyzing Public Sentiment on COVID-19 Using TF-IDF and K-Nearest Neighbors (K-NN) on Twitter Data ., Arip; Kalifia, Dina
SAINTEKBU Vol. 16 No. 02 (2024): Vol. 16 No. 02 August 2024
Publisher : KH. A. Wahab Hasbullah University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32764/saintekbu.v16i02.4353

Abstract

The coronavirus outbreak that occurred in almost all countries in the world has had an impact not only on the health sector, but also on other sectors such as tourism, finance, transportation, etc. This has given rise to various kinds of sentiments from the public with the emergence of the coronavirus as a trending topic on social media Twitter. Twitter was chosen by the public because it can disseminate information in real time and can see the market's reaction quickly. In this study, "tweet" data or public tweets related to the "Coronavirus" were used to see how the polarity of sentiment emerged. Text mining techniques and K-Nearest Neighbour (K-NN) machine learning classification algorithms were used to build a tweet classification model on sentiment whether it has a positive, negative, or neutral polarity. The test results were produced by the algorithm with an average result for a precision value of 57.93% and for an average recall niali of 55.21% with an accuracy value of 64.52%
Forecasting the Palm Oil Market: A Comparative Study of LSTM and Bi-LSTM Models for Price Prediction Pieter, Franky Bryan; Suharjito
SAINTEKBU Vol. 16 No. 02 (2024): Vol. 16 No. 02 August 2024
Publisher : KH. A. Wahab Hasbullah University

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Abstract

This study underscores the critical need for accurate palm oil price predictions amid market volatility, driven by factors like demand shifts and supply disruptions. Employing advanced neural network models, specifically Long Short-Term Memory (LSTM) and Bidirectional LSTM (Bi-LSTM), the research spans May 2007 to December 2022 using Market Insider data. Evaluation metrics, including RMSE 0.000083 and MAPE 0.76%, highlight Bi-LSTM's superior predictive prowess. Beyond immediate benefits for decision-making, the study emphasizes broader impacts on market stability, reducing volatility and fostering sustainability in the palm oil industry. Overall, this paper showcases the efficacy of Bi-LSTM in enhancing palm oil price prediction accuracy, offering practical insights, and contributing to industry sustainability.
Fault Analysis of Power Distribution Network Using FTA and FMEA: A Study at PT PLN WASKITA, FARID
SAINTEKBU Vol. 16 No. 02 (2024): Vol. 16 No. 02 August 2024
Publisher : KH. A. Wahab Hasbullah University

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Abstract

PT. PLN is a supplier of electrical energy in Indonesia which plays an important role in providing sufficient electricity for daily activities, industry and other sectors. UPDK Kapuas is a power plant in Pontianak City. Based on SAIDI and SAIFI data, the duration and frequency of blackouts in 2021 is 14.85 hours per customer per year and 14.5 times per customer per year, while in 2022 it will be 16.85 hours per customer per year and 17.16 times per customer. This has increased every year. Then the average loss value in 2022 will be 11% and the average Energy Not Supplied (ENS) value will be 26,265 kWh/month. Based on the Fault Tree Analysis method, there are 25 causes of network disruption from internal and external. Of the 25 causes of network disruption, it was reduced based on the minimum Cut Set results to 5, namely, damage caused by natural disturbances, animals, humans, installation errors, and electrical component disturbances. The highest RPN value result was caused by electrical cables amounting to 11638 which needed to be a priority repair by UPDK Kapuas. Recommendations for improvement include carrying out routine maintenance and maintenance of the network to prevent damage and adding Thermovision tools to identify and detect network damage more quickly and precisely.
Web-Based Inventory Information System at PT. Tunas Tasik Kurnia, Okto; Muchammad Wahabi; Daldiri, Daldiri
SAINTEKBU Vol. 16 No. 02 (2024): Vol. 16 No. 02 August 2024
Publisher : KH. A. Wahab Hasbullah University

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Abstract

The complexity of the company, driven by changes in the very dynamic environment, needs to be supported by a new design for the processing of stock data at PT. Tunas Tasik is still done manually, so efforts are being made to implement a special application system for the management of goods data; therefore, a responsive web-based information system is needed that can speed up the process of managing goods data. The methods used in this study are observation and interview methods. From the results of the analysis of the web-based goods data management application, which will be described using UML (Unified Modelling Language) notation, Activity Diagram and ERD, to be further implemented using the PHP programming language and database using MySQL. so that it can further improve work effectiveness and provide information quickly and accurately.
Quality Control Using the SPC Method to Reduce Defective Products in Finished Garments At VYO Factory Convection Puspita, Della Ayu
SAINTEKBU Vol. 16 No. 02 (2024): Vol. 16 No. 02 August 2024
Publisher : KH. A. Wahab Hasbullah University

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Abstract

CV.Vyo Factory, which is located at Kebakkramat, Karanganyar, Solo, is a manufacturing industry that operates in the convection industry. The problem raised in this research is the increase in defects in the production produced. As a result, companies continue to produce products that are defective in production. The results of initial observations in the field showed that there were many defective products from production at CV. Vyo Factory. It can be seen that the number of damaged products from February 2023-February 2024 continues to increase. The method used in this research is the Statistical Process Control method, attribute data and variable data collection is carried out at CV. Vyo Factory was obtained by observing the population of t-shirt products that experienced defects at the time of the research from 01 May 2024 to 30 June 2024. This is based on a control chart calculation graph (c-chart), which shows that defective t-shirt products exceed control limits, so improvements or evaluation of quality control need to be carried out. Based on the results of the analysis, it is known that using a Check Sheet, it can be seen that there are 3 categories of product damage, namely material defects, stitching defects and finishing defects, with the number of each material defect being 48 pcs, stitching defects being 275 pcs and finishing defects being 7 pcs. fruit. fruit. With a total of 330 damaged products produced, the monthly average is 1.68%.
Human-Computer Interaction Enhancement for Linux Cli Application using Telegram Bot Piping Wicaksono, Herlambang; Azzahra, Fadel; Setiawan, Hermawan
SAINTEKBU Vol. 16 No. 02 (2024): Vol. 16 No. 02 August 2024
Publisher : KH. A. Wahab Hasbullah University

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Abstract

This paper proposes an innovative method to enhance Human-Computer Interaction (HCI) for Linux Command Line Interface (CLI) applications by integrating Telegram bot piping. Despite the power of CLI, its complexity often deters users, particularly those less experienced with technology. We introduce a solution leveraging Telegram bots to provide a more intuitive and accessible interface for interacting with CLI tools. Users can issue commands via Telegram, receiving real-time feedback and executing tasks without extensive CLI knowledge. Our study includes design, implementation, and evaluation phases, demonstrating high user satisfaction with the Telegram bot integrated CLI applications. The approach significantly improves usability, reduces the learning curve, and broadens the accessibility of Linux systems. The user feedback indicated high satisfaction with the Telegram bot integrated CLI applications, with users finding it effective, user-friendly, and preferable over traditional CLI interfaces, with a user satisfaction score of 95.3%
Comparative Analysis of Data Mining Classification Methods in Predicting Credit Payments Khansa Raefa, Nabila; Ayu Kamila, Diah; Wahyunengsih
SAINTEKBU Vol. 16 No. 02 (2024): Vol. 16 No. 02 August 2024
Publisher : KH. A. Wahab Hasbullah University

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Abstract

Credit activities in the form of saving money from members, providing loans to members and managing existing funds are still intuitive and can cause errors in the credit process. So that this crediting process does not occur and can run smoothly, a payment prediction using data mining is needed. Therefore we conducted this research. The research method we use is the knowledge discovery in database process model, where this process is divided into several stages, namely selection, pre-processing or cleaning, transformation, data mining and evaluation.
Redesigning the Production Facility Layout Using the Systematic Layout Planning (SLP) Method: A Case Study at CV. Vyo Factory Rahmadani, M. Ibnu; Nur Diansari, Brillian; Filemon Waluyono, Garnet
SAINTEKBU Vol. 17 No. 01 (2025): Vol. 17 (01) January 2025
Publisher : KH. A. Wahab Hasbullah University

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Abstract

This research was conducted to design a facility layout using the SLP method, accompanied by a comparison of the efficient time between the initial layout and the proposal, as well as the results of direct observations of the production flow and activities in the CV production area. The Vyo factory has problems with irregular production flows, back-and-forth material movement (backtracking). This problem can have an impact on the enormous distances that material is moved irregularly due to relationships between departments that are far apart. Additionally, there is the issue of placing facilities that are not connected, as some facilities must be located near the production process. To overcome layout management problems, a method that can be employed is Systematic Layout Planning, which can be implemented using SketchUp software by redesigning the facility layout using this method. Based on the proposed alternative layout design using the SLP method, it can be seen that the best layout for shirt production on line 1 is starting with the storage warehouse, leading to the cutting for pattern cutting, after completion, it continues with a sewing process combining the front and back chest patterns, and sleeve sewing. The results of the design carried out using the SLP method, with SketchUp software, obtained a proposed layout to eliminate backtracking. The results of the analysis of effectiveness and efficiency during the production process can optimize the production process to be more orderly and utilize space more efficiently, allowing for a more streamlined workflow from incoming raw materials to finished products. Implementing this proposed layout can resolve layout issues in the production area, thereby eliminating backtracking.
A Literature Review on the Role of Mathematics in Enhancing Cyber Security Through Data Encryption Laily Shodiq , Nur; Hawari, Ammar; Putri, Nabilla Andini; Nurul Faizah, Maira; Wahyunengsih
SAINTEKBU Vol. 17 No. 01 (2025): Vol. 17 (01) January 2025
Publisher : KH. A. Wahab Hasbullah University

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Abstract

This article discusses the important role of mathematics in enhancing cyber security in the data encryption process. The research problem investigates the benefits of applying mathematical principles in maintaining data security amid increasingly complex cyber threats. The study focuses on four main criteria: protecting sensitive information, verifying user identity, preventing intrusions, and protecting network integrity. Mathematical algorithms, binary numbers, and boolean algebra are essential in effectively encrypting data. They not only protect sensitive information from unauthorized access but also verify user authenticity, preventing identity theft and unauthorized system access. By utilizing mathematical theories and algorithms, binary numbers, and boolean algebra, cyber security systems can guarantee data confidentiality, integrity, and availability. In conclusion, the integration of mathematics in cyber security systems is essential to mitigate risks and protect critical digital assets from increasingly sophisticated cyber threats.

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