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Tri A. Sundara
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The Indonesian Journal of Computer Science
Published by STMIK Indonesia Padang
ISSN : 25497286     EISSN : 25497286     DOI : https://doi.org/10.33022
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Engineering
The Indonesian Journal of Computer Science (IJCS) is a bimonthly peer-reviewed journal published by AI Society and STMIK Indonesia. IJCS editions will be published at the end of February, April, June, August, October and December. The scope of IJCS includes general computer science, information system, information technology, artificial intelligence, big data, industrial revolution 4.0, and general engineering. The articles will be published in English and Bahasa Indonesia.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 1,170 Documents
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Voice Recognition Based on Machine Learning Classification Algorithms: A Review Sarbast, Hajin
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.4110

Abstract

One essential component of biometric identity is voice recognition technology, which uses speech pattern analysis to authenticate people. With an emphasis on machine learning classification techniques, this review article thoroughly examines the field of speech recognition. We examine the effectiveness of random forest (RF), multilayer perceptrons (MLP), k-nearest neighbours (KNN), and support vector machine (SVM) classifiers via painstaking analysis and empirical evaluation. Utilizing a collection of Sepedi speech audio files, our results demonstrate the remarkable accuracy of 99.86% that RF is capable of producing. Aside from visual aids for better understanding, assessment indicators like as accuracy, precision, recall, F-measure, and root mean square error (RMSE) clarify the effectiveness of the model. The research highlights how machine learning algorithms, especially reinforcement learning (RF), have the capacity to revolutionize speech recognition technology in a variety of contexts.
Agile Readiness Assessment of IT Audit Function at Indonesia’s State-Owned Bank Dedi Kurniawan; Raharjo, Teguh; Nur Fitriani, Anita
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4111

Abstract

Recently, there has been increased interest in using Agile methodologies in auditing to improve efficiency and adaptability. This study examines whether Bank XYZ in Indonesia is ready to adopt Agile for IT auditing, marking a first for the country's banks. The need for Agile is driven by a significant reduction in audit staff, increased demands from management, and higher fraud risks, all of which call for a more effective and responsive audit process. The research employed both surveys based on the CA Agile Framework and qualitative analysis. It found that Bank XYZ is moderately ready to adopt Agile, showing strengths in commitment to user research, organizational culture, and training support. However, challenges such as utilizing past Agile experiences and enhancing governance must be addressed. The study recommends a gradual adoption of Agile, focusing on building a supportive Agile culture, enhancing training for auditors, and improving governance structures. This step-by-step approach will help Bank XYZ effectively integrate Agile into its IT auditing practices to better meet management's expectations for more business-focused auditing.
PENERAPAN FUZZY LOGIC DALAM SISTEM PEMANTAUAN VITAL SIGN BERBASIS INTERNET OF THINGS Rahmatulloh, Muhammad Rafy; Indroasyoko, Narwikant; Khoirunnisa, Hilda
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4112

Abstract

The development of the Internet of Things (IoT) has brought innovations in healthcare, especially in vital sign monitoring, crucial for detecting physiological changes and supporting disease diagnosis. Outpatient vital sign monitoring is often neglected due to time and equipment constraints. Previous research, such as using Bluetooth technology, showed range limitations, while other solutions couldn't classify patient conditions. This study develops an IoT-based vital sign monitoring device with four parameters: blood pressure, body temperature, heart rate, and oxygen saturation, accessible online. The device uses fuzzy logic to classify patient status. Test results show accuracy rates of 96.4% and 91.3% for blood pressure, 98% for heart rate, 98% for oxygen saturation, and 98% for body temperature readings. Patient classification tests showed 9 out of 10 samples had the same risk output as the NEWS assessment.
Analysis and Design of e-Commerce Application “PALMARKET” based on Mobile Android as a Media for Selling Quality Palm Seeds and Seeds Maudy Hellena Harlyn; Fajar Maulana; Ardila; Ratu Mutiara Siregar; Amru Yasir; Tuty Ningsih; Friska Anggraini Barus; Rahmad Dian
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4113

Abstract

In this digital era, the use of e-commerce mobile applications is very useful to reach sales and purchases widely and is easy, fast and convenient to use for the community. Until now, there has not been found e-commerce that is devoted to selling seeds and plant seeds, especially oil palm plants that can be trusted. In fact, there are many farmers who buy the wrong seeds, resulting in long-term problems in the oil palm plantation industry whose production is decreasing. Therefore, the sale of seeds and plant seeds needs support through a trusted e-commerce Mobile Application so that farmers do not need to be afraid to buy quality oil palm seeds. The development method used in this research uses the Waterfall method. The results of this study are in the form of e-commerce Mobile Application as a means of buying and selling oil palm seeds and seeds that are easy and reliable throughout the region
Pengaruh Load Balancing Pada Ser Pengaruh Load Balancing Pada Serangan DDoS Menggunakan Nginx: Pengaruh Load Balancing Pada Serangan DDoS Menggunakan Nginx Satrya Bhayangkara, Dimas; Miftahul Ashari, Wahid
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4118

Abstract

DDoS (Distributed Denial of Service) attacks are one of the most common cyberattacks. This attack can make a server experience an error. Various methods have been used to overcome this attack, one of which is load balancing. Load balancing is responsible for dividing the workload among various servers evenly. In this study, we used Nginx load balancing. The research was conducted by sending 100000, 300000, 400000, and 500000 requests. Throughput after using load balancing shows superiority, with an average of 9,581 kb/s compared to not using load balancing. Response time using load balancing is also better than not using load balancing, with an average of 4507.23 ms. However, the packet loss shows no packet loss, which is 0% after using load balancing and before using load balancing. The effect of load balancing on Nginx can prevent DDoS attacks with a load balancing algorithm that is still good enough to use.
OPTIMASI TEKNIK VOTING PADA SENTIMEN ANALISIS PEMILIHAN PRESIDEN 2024 MENGGUNAKAN MACHINE LEARNING Kharisma Rahayu; M. Khairul Anam; Lusiana Efrizoni; Nurjayadi; Triyani Arita Fitri
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4119

Abstract

The presidential election is an important event in the democratic system of the Unitary State of the Republic of Indonesia or NKRI held every five years. There are many pros and cons of the presidential election, especially on social media Twitter or X. X is one of the media platforms where people leave positive, neutral, and even negative comments. Therefore, this research aims to build a sentiment analysis model to classify the sentiment of the 2024 presidential election. This research uses the Support Vector machine, Naïve Bayes and Decision Tree algorithms in performing classification with the addition of the Syntethic Minority Over-Sampling and Ensemble Voting methods. The test results show that public sentiment towards the presidential election dominates negative sentiment of 5008 positive 3582 and neutral 1411 sentiments. Then the results of data processing SVM, NB and DT algorithms plus SMOTE and ensemble voting optimization, provide 92.8% accuracy, 93% precision, 93% recall and 93% F1-Score. This research can make a significant contribution by classifying public sentiment towards the 2024 presidential election data.
Prediksi Penempatan Pegawai Menggunakan Algoritma Supervised Machine Learning dan Rules Based Experts: Studi Kasus di Institusi Pendidikan Romdhoni, Bayu Suciono; Denny
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4120

Abstract

Education plays a crucial role in shaping the future of a nation. To maintain the quality of education, effective human resource management is essential in educational institutions. This study addresses the challenges of employee’s placement under the Educational Institution. According data from December 2021 to May 2024, only 2,452 out of 41,722 employees were reassignment, which is significantly below the target set by regulation. This study evaluates several supervised machine learning algorithms, including Gaussian Naive Bayes, Decision Tree, Support Vector Machine, and Random Forest. Random Forest emerges as the most suitable algorithm due to its superior accuracy, precision, recall, and F1 Score. Following the evaluation of the chosen algorithm, the deployment phase includes comprehensive data preprocessing steps, such as handling missing values, data normalization, and categorical feature encoding. This system integrates with Google API for geospatial data, ensuring accurate and efficient decision-making.
Faktor-faktor yang Memengaruhi Perilaku Knowledge Sharing di Kalangan Software Developer di Indonesia Ringgi Cahyo Dwiputra; Ariq Naufal Satria; Dana Indra Sensuse; Sofian Lusa; Damayanti Elisabeth
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4125

Abstract

Knowledge sharing is a crucial element for enhancing efficiency in the software development process. However, it proves to be a challenging and complicated task in practice, particularly due to the insufficient knowledge and experience of software developers. The aim of this research is to pinpoint key success factors in knowledge sharing behavior among software developers. Based on Social Cognitive Theory (SCT), the research divides components into three categories: behavioral, environmental, and personal. For a more complete picture, an additional organizational aspect is included. The partial least squares structural equation model was utilized to analyze the data collected from 198 software developers in Indonesia. The findings reveal that motivation, trust, social interaction, organizational culture, reward, and management support positively influence knowledge sharing behavior, while geographical distance has a negative impact. This research contributes by filling a gap in previous research that utilized SCT, broadening the model to identify determinant factors explaining knowledge sharing behavior within an organizational context.
Uncovering the Reasons Behind Abstain Voters' Stances in the 2024 Indonesian Presidential Election: Social Media X Study Cases Putri, Irzanes; Insani, Faiz Nur Fitrah; Budi, Indra; Santoso, Aris Budi; Putra, Prabu Kresna
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4126

Abstract

The Indonesian Government expects the participation of all Indonesian people in holding General Elections. However, according to the 2019 Political Statistics by BPS, there were 34.75 million people who did not exercise their right to vote or were abstain voters (golput) in the 2019 Election. This research aims to analyze individual attitudes towards abstaining voters using stance analysis and topic modelling. From 9,045 collected tweets, subsequent manual annotation revealed 2,566 pro stances, 5,264 neutral stances, and 1,215 contra stances. The classification models utilized are Random Forest, Decision Tree, Logistic Regression, Support Vector Machine, K-Nearest Neighbor, and Gradient Boosting. The classification outcomes will be analyzed by comparing the accuracy, precision, recall, and F1-score results based on their algorithms and n-grams. The results obtained from the stance analysis show that Random Forest achieved the highest accuracy and precision scores, with values of 84% and 83%, respectively. The discussion topic among those supporting golput due to low trust in the presidential and vice-presidential candidates. Other topics mentioned public feels dissatisfied with the pairs of candidates.
Pengendalian Level Air pada Coupled Tank dengan Metode PID Berbasis PLC dan IoT Fitria Suryatini; Abyanuddin Salam; Selena Natasha
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4127

Abstract

There are many advanced technological discoveries in industry, including the coupled tank. Coupled tanks are several tanks connected to each other. One of the quantities that is often controlled in the industry is the control of water levels. Water level control in a PLC and IoT-based coupled tank system is a medium for controlling and monitoring water levels remotely in real-time. The sensor used is a Differential Pressure Transmitter (DPT) with a pump motor actuator which is connected to an Omron PLC using an inverter. There is a disturbance in the form of setting the control valve opening. The control method used is the PID method with Ziegler-Nichols tuning and trial and error. Both methods analyzed which performance of the system response characteristics was better. It is proven that PID tuning is suitable for water level control of coupled tank systems.

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