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All Journal JIK Jurnal Ilmu Komputer Jurnal Simetris Majalah Geografi Indonesia JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika JEMA: Jurnal Ilmiah Bidang Akuntansi dan Manajemen IKRA-ITH Informatika : Jurnal Komputer dan Informatika Jurnal Pengabdian Masyarakat AbdiMas Aptisi Transactions on Technopreneurship (ATT) Jurnal Mantik Jurnal Abdimas Madani dan Lestari (JAMALI) JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI Journal Sensi: Strategic of Education in Information System Jurnal Algoritma, Logika dan Komputasi Jurnal Ilmu Komputer dan Informatika Journal of Social Research Ilmu Komputer untuk Masyarakat Jurnal Locus Penelitian dan Pengabdian Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Jurnal Indonesia Sosial Teknologi Jurnal Indonesia Sosial Sains Journal of Accounting Research, Organization and Economics (JAROE) Eduvest - Journal of Universal Studies Jurnal Ekonomi, Teknologi dan Bisnis Media Abdimas Jurnal Pengabdian Masyarakat Bangsa Infact: Jurnal Sains dan Komputer Asian Journal of Social and Humanities INOVTEK Polbeng - Seri Informatika
Widodo, Agung Mulyo
Universitas Esa Unggul
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Journal : Asian Journal of Social and Humanities

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Analysis of Data Mining Applications for Determining Credit Eligibility Using Classification Algorithms C4.5, Naïve Bayes, K-NN, and Random Forest Yessy Oktafriani; Gerry Firmansyah; Budi Tjahjono; Agung Mulyo Widodo
Asian Journal of Social and Humanities Vol. 1 No. 12 (2023): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v1i12.119

Abstract

This study aims to enhance the credit evaluation process within Credit Union (CU) Karya Bersama Lestari (KABARI). The study leveraged four distinct algorithms, namely Decision Tree C4.5, Naive Bayes, K-Nearest Neighbors (K-NN), and Random Forest, to predict the suitability of extending loans to potential borrowers. Rapid Miner was employed as a tool to maximize accuracy by analyzing the Confusion matrix. Testing was conducted on a dataset consisting of 459 member loan submissions. The results of the analysis revealed that the K-Nearest Neighbors (K-NN) algorithm achieved the highest accuracy among the evaluated algorithms. Specifically, the Decision Tree algorithm demonstrated an accuracy rate of 95.65%, along with a precision and recall of 94.12%. The Naive Bayes algorithm achieved an accuracy rate of 95.65%, supported by precision and recall values of 100% and 88.24%, respectively. The K-Nearest Neighbors algorithm displayed the highest accuracy rate of 97.83%, accompanied by 100% precision and 94.12% recall. Meanwhile, the Random Forest algorithm exhibited an accuracy rate of 93.48%, complemented by precision and recall values of 100% and 82.35%, respectively. The study's conclusions bear relevance for refining loan approval processes and fostering improved lending practices within financial institutions like CU KABARI.  
Performance Evaluation of Business Continuity Plan in Dealing with Threats and Risks in Cilegon Companies Use ISO 22301:2019 & NIST Sp 800-30 R1 Frameworks Case Study: PT. X Hendaryatna Hendaryatna; Gerry Firmansyah; Budi Tjahjono; Agung Mulyo Widodo
Asian Journal of Social and Humanities Vol. 1 No. 12 (2023): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v1i12.120

Abstract

This research was conducted at PT.X which is located in Cilegon, Merak-Banten. Seeing the geographical location of PT.X which is in a disaster-prone area, the company must ensure an effective business continuity process. In accordance with government regulations on Electronic-Based Government Systems (SPBE) related to corporate and government business activities, companies must be able to ensure business continuity in every condition that poses a threat and risk, but with no specific obligation that is the basis for the company's business continuity if it does not have a Business Continuity Plan (BCP) process, it will get a sanction. The purpose of this research is to evaluate the existing BCP process at PT X Cilegon and provide recommendations for a standardized BCP framework in the company to ensure business continuity as the company's Business Continuity Management System (BCMS) to avoid all threats and risks. BCP has standards regulated in ISO 22301: 2019 as its framework, and in BCP there is a risk analysis process and this research will be carried out using the NIST SP 800-30 Revision 1 method as its best practice. The evaluation results show that the previous BCP process at PT X Cilegon was not in accordance with the standards and the risk analysis carried out was still based on the ISO that the company had implemented but not ISO 31000 which is the risk management standard, so this study provides recommendations for a BCP framework that is in accordance with the standards and risk analysis with risk analysis methods that produce risk priorities.
Analysis of School Community Sentiment towards Personal Data Protection Law Using Support Vector Machine (SVM) Method Gusti Fachman Pramudi; Gerry Firmansyah; Budi Tjahjono; Agung Mulyo Widodo
Asian Journal of Social and Humanities Vol. 1 No. 12 (2023): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v1i12.121

Abstract

This research aims to analyze the awareness status of the school community regarding the right to personal data protection, test and analyze the sentiments of the school community towards the implementation of the Personal Data Protection Law and as a means of outreach regarding personal data protection laws in the world of education, especially school community besides that to find out whether the Support Vector Machine method can be used as a method in conducting Sentiment Analysis research. The results of this study can be concluded that only 38% of the school community knows about this regulation while the other 62% still don't know much about this rule. Then for the use of the Support Vector Machine method which has been carried out five (5) trials using different variations of training data and test data produces an average accuracy rate of 85.97% with the highest results on training data and test data 50% - 50% that is equal to 88.00% and the lowest result is in the experiment of training data and test data of 90% - 10% which is equal to 84.44%. For the school community's sentiment towards the Personal Data Protection Act, it was 56% or as many as 496 of 887 words. which shows a neutral response and 8% or as many as 72 out of 887 sentiment words show a negative response.
Emotional Classification Based on Facial Expression Recognition Using Convolutional Neural Network Method Arif Pami Setiaji; Gerry Firmansyah; Habibullah Akbar; Budi Tjahjono; Agung Mulyo Widodo
Asian Journal of Social and Humanities Vol. 1 No. 12 (2023): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v1i12.139

Abstract

In recent years, the development of human-computer interaction technology has reached remarkable levels, particularly in the field of facial expression recognition. This technology utilizes human facial images to identify and classify emotional expressions such as happiness, sadness, fear, and more through computer image processing. Active research in facial expression recognition yields substantial benefits for individual and societal advancement, especially in the context of its application within Smart City environments. This study demonstrates that well- configured Convolutional Neural Network (CNN) models empowered by TensorFlow exhibit higher accuracy compared to models utilizing PyTorch. The TensorFlow model achieves the highest accuracy of 93% in recognizing emotional expressions, whereas the PyTorch model achieves 69% accuracy. The TensorFlow model also displays lower accuracy loss and shorter training times compared to the PyTorch model. In the context of calculating happiness indices within Smart City environments, the appropriate choice of technology significantly influences measurement accuracy and efficiency. Therefore, the TensorFlow platform, proven to deliver superior performance in this study, can be a strategic choice for integrating facial expression detection technology into happiness index measurements in such locations
Utilization of LSTM (Long Short Term Memory) Based Sentiment Analysis for Stock Price Prediction Muhammad Fajrul Aslim; Gerry Firmansyah; Budi Tjahjono; Habibullah Akbar; Agung Mulyo Widodo
Asian Journal of Social and Humanities Vol. 1 No. 12 (2023): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v1i12.141

Abstract

This study aims to utilize sentiment analysis in predicting stock price movements. Sentiment analysis can provide information to investors to understand market sentiment. This study uses a text-based approach by pre-processing data, constructing a sentiment analysis model and evaluating model performance. The collected data is analyzed to identify the text's positive, negative, or neutral sentiments. The approach used in scoring sentiment analysis is the Text blob approach and the Lexicon approach. Differences in the results of the accuracy of the two Sentiment Analysis approaches with the LSTM model have an influence on the prediction results with a better increase in accuracy using the Lexicon Sentiment Analysis approach. Then the LSTM model is implemented to classify texts into the desired sentiment categories. The results of this study are insight into the use of sentiment analysis in predicting stock price movements. The implemented sentiment analysis model can be a useful predictive tool for investors and stock practitioners in making investment decisions.
Comparative Performance of Learning Methods In Stock Price Prediction Case Study: MNC Corporation Rifqi Khairurrahman; Gerry Firmansyah; Budi Tjahjono; Agung Mulyo Widodo
Asian Journal of Social and Humanities Vol. 2 No. 5 (2024): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v2i5.252

Abstract

Shares are a popular business investment, the development of information technology now allows everyone to buy and sell shares easily online, investment players, both retail and corporate, are trying to make predictions. The purpose of this study is to find out comparative performance of learning methods in stock price prediction. There are currently many research papers discussing stock predictions. using machine learning / deep learning / neural networks, in this research the author will compare several superior methods found in the latest paper findings, including CNN, RNN LSTM, MLP, GRU and their variants. From the 16 result relationships and patterns that occur in each variable and each variable is proven to show its respective role with its own weight, in general we will summarize the conclusions in chapter V below, but in each analysis there are secondary conclusions that we can get in detail. The variable that has the most significant effect on RMSE is variable B (repeatable data) compared to other variables because it has a difference in polarity that is so far between yes and no. The configuration of input timestep (history)=7 days and output timetep (prediction)=1 day is best for the average model in general.
Analysis of Knowledge Management Strategies for Handling Cyber Attacks with the Computer Security Incident Response Team (CSIRT) in the Indonesian Aviation Sector Lingga Dwiaji; Agung Mulyo Widodo; Gerry Firmansyah; Budi Tjahyono
Asian Journal of Social and Humanities Vol. 2 No. 6 (2024): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v2i6.261

Abstract

Cyber attacks are one of the genuine threats that have emerged due to the evolution of a more dynamic and complex global strategic environment. In Indonesia, several cyber attacks target various government infrastructure sectors. The National Cyber and Crypto Agency (BSSN) predicts Indonesia will face approximately 370.02 million cyber attacks in 2022. The majority of cyber attacks target the government administration sector. The National Cyber and Crypto Agency (BSSN) officially formed a Computer Security Incident Response Team (CSIRT) to tackle the rampant cybercrime cases. CSIRT is an organization or team that provides services and support to prevent, handle, and respond to computer security incidents. The current CSIRT does not have a data storage process and forensic preparation. CSIRT will repeat the procedure, and so on. This is a repeating procedure; the attack will occur once, and only a technical problem will arise. Therefore, the research entitled "Analysis of Knowledge Management Strategies for Handling Cyber Attacks with the Computer Security Incident Response Team (CSIRT)" is expected to implement this Knowledge Management Strategy to manage existing knowledge so that it can make it easier for the CSIRT team to handle cyber attacks that occur.
Assessment of the level of student understanding in the distance learning process using Machine Learning Adilah Widiasti; Agung Mulyo Widodo; Gerry Firmansyah; Budi Tjahjono
Asian Journal of Social and Humanities Vol. 2 No. 6 (2024): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v2i6.272

Abstract

As technology develops, data mining technology is created which is used to analyse the level of understanding of students. This analysis is conducted to group students according to their ability to understand and master the subject matter. This research can provide guidance and insight for educators, as well as artificial intelligence, machine learning, association techniques, and classification techniques. Researchers and policymakers are working to optimise learning and improve the quality of student understanding. This study aims to analyse the level of student understanding in simple and structured terms. Using the Machine learning method to analyse the level of student understanding has the potential to impact the quality of education significantly. In addition, machine learning categories are qualified to be applied to the concept of data mining. The data mining techniques used are association and classification. Association techniques are used to determine the pattern of distance student learning. The following process of classification techniques is used to determine the variables to be used in this study using the Logistic Regression model where data that have been classified are grouped or clustered using the K-Means algorithm into three, namely the level of understanding is excellent, sound, and lacking, based on student activity, assignment scores, quiz scores, UTS scores, and UAS scores.
Evaluation of IT Service Level Infrastructure In Organizations Using ITIL (Information Technology Infrastructure Library) Version 3 Standardization Achmad Randhy Hans; Gerry Firmansyah; Budi Tjahyono; Agung Mulyo Widodo
Asian Journal of Social and Humanities Vol. 2 No. 12 (2024): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v2i12.393

Abstract

The rapid development of business and advancements in information technology today are highly significant, especially in supporting the progress of ongoing businesses. Many businesses, particularly startups, make information technology the backbone supporting every main business process to achieve their business goals. Startups that operate 24/7 require sufficiently robust information technology, which must always be ready to provide the needed services to support the business. IT service assessment is an activity commonly carried out within an organization to eval_uate the level of information system services it possesses. An assessment, particularly an IT service assessment, can be conducted independently if the organization has adequate tools and is equipped with the correct standards. The eval_uation of information system services can be carried out using various standards, such as ITIL. In this research, the researcher will conduct an assessment using ITIL standards in the form of a website, which can serve as a tool. This website assessment application focuses on the domains of Service Management and Service Delivery, with the expectation that the services provided by PT Loyal.id will improve further.
Analysis of Information Technology Proficiency Levels For Academic Services Using The Cobit 2019 Framework: Case Study of SMP Negeri 102 Jakarta Ismiyati Meiharsiwi; Gerry Firmansyah; Agung Mulyo Widodo; Budi Tjahjono
Asian Journal of Social and Humanities Vol. 2 No. 12 (2024): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v2i12.394

Abstract

This research intends to analyze the level of capability of information technology (IT) in academic services at SMP Negeri 102 Jakarta using the COBIT 2019 framework. The background of this research is the important role of information technology in increasing the efficiency and effectiveness of the learning process in educational institutions. COBIT 2019 was chosen as a framework because it is a best practice in IT governance that can help institutions achieve their strategic goals. This research focuses on the IT governance process implemented at SMP Negeri 102 Jakarta, the maturity level of existing information system governance, and recommendations for improving IT governance. The case study method is used with limitations on the domain within Align, Place and Organize (APO) 09 dan Deliver, Service and Support (DSS) 01 the COBIT 2019 framework. Research findings show that IT governance at SMP Negeri 102 Jakarta is at a certain level of capability that needs to be improved. This research provides recommendations for improving academic services through improving IT governance. It is hoped that the results of this research can become a reference in determining IT policies at SMP Negeri 102 Jakarta and contribute to the development of knowledge in the field of information technology governance.
Co-Authors Achmad Fansuri Achmad Randhy Hans Adhi Fernandes Gamaliel Adhikara, M. F. Arrozi Adilah Widiasti Ahmad Musnansyah Ahmad Mutedi Akbar , Habibullah Akbar, Habibullah Alivia Yufitri Andriana, Dian Annazma Ghazalba Ari Widatama, Yohanes Bagas Arif Pami Setiaji Bambang Irawan Bambang Irawan Bambang Irawan Bayu Sulistiyanto Ipung Sutejo Binastya Anggara Sekti Budi Aribowo Budi Tjahjono BUDI TJAHJONO Budi Tjahjono Budi Tjahyono Budi Tjahyono Budi Tjahyono Cahya Darmarjati Deni Iskandar Deni Iskandar Dewi, Riris Septiana Sita Doni Antoro Dulbahri Dulbahri Dwiaji, Lingga Eko Prasetyo Endang Ruswanti Endang Ruswanti Erry Yudhya Mulyani Erry Yudhya Mulyani Erry Yudhya Mulyani Euis Heryati Fadlilatunnisa, Fanny Fatonah, Nenden Siti Fikri Saefullah Firmansyah, Gerry Gerry Firmansyah Gerry Firmansyah Gerry Firmasyah Gusti Fachman Pramudi Habibullah Akbar Hadi, Muhammad Abdullah Hadjarati, Panji Ramadhan Yudha Putra Hani Dewi Ariessanti Hartono Hartono Haryoto, Iin Sahuri Hendaryatna Hendaryatna Heri Wijayanto I Gede Pasek Suta Wijaya Ichwani, arief Ichwani, Arief Ipung Sutejo, Bayu Sulistiyanto Ismiyati Meiharsiwi Iwan Setiawan Izhar Rahim Joniwan Joniwan Karisma Trinanda Putra Kartini Kartini Krisogonus Wiero Baba Kaju Kundang Karsono Juman Kundang Karsono Juman Kundang Karsono Juman Kus Hendrawan Muiz Lingga Dwiaji Lisdiana Lisdiana Martin Saputra, Martin Massie, Julius Ivander Maulana, Syaban Meria, Lista Muhamad Bahrul Ulum Muhamad Bahrul Ulum Muhammad Azzam Robbani Muhammad Fajrul Aslim Muhammad Hadi Arfian Muttaqin, Naufal Hafizh Nainggolan, Restamauli br Nina Nurhasanah Nindyo Artha Dewantara Wardhana Nixon Erzed Nixon Erzed Nizirwan Anwar Nizirwan Anwar Nurfilael, Gagas Nurfilae Nurhayati, Ety Pratama, Fajar Prayitno Purwano SK Rahaman, Mosiur Rian Adi Pamungkas Rifqi Khairurrahman RILLA GANTINO Rizki Faro Khatiningsih Rizky Aulia Roesfiansjah Rasjidin Sholeh Gunawan Simorangkir, Holder Suardana, Made Aka Sularso Budilaksono Sulistyo, Catur Agus Sunardi, Sunardi Tardiana, Arisandi Langgeng Tartila, Gilang Romadhanu Tjahjono, Budi Tyara Regina Nadya Putri Ulum, Muhamad Bahrul Ummanah Ummanah, Ummanah Vitri Tundjungsari Wahid Abdul Azis Wardhana, Nindyo Artha Dewantara Widiasti, Adilah William Nugraha Wisnujati, Andika Yanathifal Salsabila Anggraeni Yessy Oktafriani Yulhendri Yulhendri