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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Sains dan Teknologi TELKOMNIKA (Telecommunication Computing Electronics and Control) CESS (Journal of Computer Engineering, System and Science) Proceeding of the Electrical Engineering Computer Science and Informatics JOIN (Jurnal Online Informatika) SISFOTENIKA JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Pilar Nusa Mandiri Jurnal Mantik Penusa JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI ILKOM Jurnal Ilmiah Jiko (Jurnal Informatika dan komputer) JSiI (Jurnal Sistem Informasi) Jurnal Pengembangan Riset dan Observasi Teknik Informatika JURIKOM (Jurnal Riset Komputer) Jurnal Riset Informatika JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Building of Informatics, Technology and Science Jurnal Mantik Aisyah Journal of Informatics and Electrical Engineering INTI Nusa Mandiri Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Teknik Informatika C.I.T. Medicom Journal of Intelligent Decision Support System (IDSS) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Teknik Informatika (JUTIF) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI JPM: JURNAL PENGABDIAN MASYARAKAT Journal La Multiapp KLIK: Kajian Ilmiah Informatika dan Komputer International Journal of Basic and Applied Science JUSTIN (Jurnal Sistem dan Teknologi Informasi) PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer SAGA: Journal of Technology and Information Systems Journal International Journal of Teaching and Learning (INJOTEL) INTERNATIONAL JOURNAL OF SOCIETY REVIEWS (INJOSER) Journal of Blockchain, Nfts and Metaverse Technology
Agung Triayudi
Universita Nasional
Aerospace Engineering Humanities Astronomy Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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Journal : SAGA: Journal of Technology and Information Systems

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Evaluating Text Quality of GPT Engine Davinci-003 and GPT Engine Davinci Generation Using BLEU Score Heryanto, Yayan; Triayudi, Agung
SAGA: Journal of Technology and Information System Vol. 1 No. 4 (2023): November 2023
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v1i4.213

Abstract

The improvement of text generation based on language models has witnessed significant progress in the field of natural language processing with the use of Transformer-based language models, such as GPT (Generative Pre-trained Transformer). In this study, we conduct an evaluation of text quality using the BLEU (Bilingual Evaluation Understudy) score for two prominent GPT engines: Davinci-003 and Davinci. We generated questions and answers related to Python from internet sources as input data. The BLEU score comparison revealed that Davinci-003 achieved a higher score of 0.035, while Davinci attained a score of 0.021. Additionally, for the response times, with Davinci demonstrating an average response time of 4.20 seconds, while Davinci-003 exhibited a slightly longer average response time of 6.59 seconds. The decision of whether to use Davinci-003 or Davinci for chatbot development should be made based on the specific project requirements. If prioritizing text quality is paramount, Davinci-003 emerges as the superior choice due to its higher BLEU score. However, if faster response times are of greater importance, Davinci may be the more suitable option. Ultimately, the selection should align with the unique needs and objectives of the chatbot development project.
Application of Sentiment Analysis in the Reshot Method to Improve User Experience of the Hijra Bank Application Ma'arif, Ridwan Ahmad; Triayudi, Agung
SAGA: Journal of Technology and Information System Vol. 2 No. 1 (2024): February 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v2i1.240

Abstract

The first stage in simplifying User Experience (UX) using the RESHOT method is Refine the Challenge. This stage is carried out so that design practitioners know the problems or needs of application users through product research. However, the product research methods that can be carried out at this stage are very diverse and require time. This research aims to explain a product research method that can be used by design practitioners easily and quickly, namely the sentiment analysis method with the Naïve Bayes algorithm. Naive Bayes is a classification method based on simple probability. The results of this analysis will be used as a reference for improving UX using the RESHOT method on the Hijra Bank application. The results of product research using sentiment analysis obtained 2711 opinions originating from tweets on Twitter and user reviews of the Hijra Bank application on Google Play. Of the 2711 opinions, 149 had negative sentiment, with the most frequently mentioned opinions being "Customer" and "Data" with an analysis accuracy of 92%. The results of this analysis are converted into a hypothesis, which will later become a reference in designing interfaces using the RESHOT method.
Implementation of Naïve Bayes and K-NN Algorithms in Diagnosing Stunting in Children Wulan Widhari; Agung Triayudi; Ratih Titi Komala Sari
SAGA: Journal of Technology and Information System Vol. 2 No. 1 (2024): February 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v2i1.242

Abstract

Indonesia faces a huge potential risk of stunting, as revealed in the Indonesian Nutrition Status Analysis according to 2022 data, the stunting rate reached 24.22% in 514 districts / cities throughout Indonesia. To prevent stunting in children, early detection can be done. This research was conducted to compare the performance of two algorithms Naive Bayes and K-NN to predict stunting cases in children, to get a better picture of how classification algorithms predict stunting cases with a better level of accuracy and responsiveness, comparison experiments of several algorithms are needed using specific datasets to develop an optimal classification model. Based on the results of performance testing on the K-Nearest Neighbor and Naive Bayes methods in testing the performance of accuracy, precision, recall, and f1-score, the results of performance testing on the naïve bayes method obtained performance values on 30% testing data are accuracy of 71%, precision 71%, recall 76%, and f1-score 73%. The performance results of the K-NN method using the euclidean distance measurement obtained the best performance value, namely accuracy of 97%, precision of 98%, recall of 96%, f1-score of 97% at a value of k = 3. Based on the performance results of the comparison of the Naive Bayes and K-NN methods, it shows that the best classification method on the stunting dataset is the K-NN method because it gets better performance than the Naive Bayes method.
Combination of AES (Advanced Encryption Standard) and SHA256 Algorithms for Data Security in Bill Payment Applications Rais Rabtsani, Muhamad; Triayudi, Agung; Soepriyono, Gatot
SAGA: Journal of Technology and Information System Vol. 2 No. 1 (2024): February 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v2i1.250

Abstract

In the era of information technology development, digital payments and e-payments are becoming a dominant trend, supported by the crucial role of payment gateways such as Midtrans. Midtrans uses APIs to facilitate various online transactions, including debit cards. In this research, two cryptographic algorithms will be combined, namely Advance Encryption Standard (AES) with 256 bits and Secure Hash Algorithm (SHA) with 256 bits. The importance of data security in e-payments is recognized, with the application of cryptographic algorithms to protect sensitive transaction information. Yayasan Antero Prosesi Edukasi (YAPE) as an educational marketing consultant faced the challenge of time-consuming and inefficient manual payments. In an effort towards efficiency and security, YAPE plans to develop an online payment application with Midtrans Payment Gateway and the use of AES-256 and SHA-256 cryptographic algorithms. This step is expected to help the foundation keep up with technological developments, provide ease of payment, and achieve computerized efficiency. The results showed that the use of a combination of AES 256 bit and SHA256 encryption significantly increased security, making hacking attempts ineffective because encrypted data could not be accessed, with quite complicated calculation stages.
Inventory Management System for MSMEs Setiawan, Aan; Triayudi, Agung; Agus Iskandar
SAGA: Journal of Technology and Information System Vol. 2 No. 1 (2024): February 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v2i1.251

Abstract

This inquire about points to create a web-based stock framework that centers on reasonableness, user-friendliness, and usefulness custom-made to desires of Miniaturized scale, Little, and Medium Ventures (MSMEs). Through in-depth analysis of MSMEs' specific inventory management requirements, the system not only provides a comprehensive solution for stock management but also integrates the Apriori algorithm for associative analysis of inventory data. The system's development adopts an Agile approach, allowing flexible adaptation to changing needs throughout the development process. Key features include efficient stock management, intuitive Point of Sales (POS) transaction recording, and customizable inventory reporting. The implementation of this system is expected to enhance MSMEs' efficiency in inventory management, provide insightful data to support more informed decision-making, and positively contribute to strengthening competitiveness and growth in the dynamic and competitive business environment.
Implementation of K-Nearest Neighbour (KNN) Algorithm and Random Forest Algorithm in Identifying Diabetes Diranisha, Virly; Agung Triayudi; Ratih Titi Komalasari
SAGA: Journal of Technology and Information System Vol. 2 No. 2 (2024): May 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v2i2.253

Abstract

Diabetes, one of the noncommunicable diseases (NCDs), is currently a major health threat worldwide. So far, diabetes symptoms have only been diagnosed by people according to known physical characteristics without the support of factual evidence or other medical considerations. With the advancement of technology, it is possible to use algorithms to solve various kinds of problems. One of artificial intelligence (AI), machine learning, concentrates on creating systems that can learn from data. This research uses the K-Nearest Neighbor (KNN) and Random Forest algorithms that can be utilised as testing algorithms to identify diabetes. Classification is done based on training data that has been provided in the dataset. The purpose of this research is to determine the best classification in identifying diabetes with the K-Nearest Neighbor (KNN) algorithm and the Random Forest algorithm and is expected to provide more understanding of the implementation of machine learning models. comparing the two algorithms between the KNN algorithm and the Random Forest algorithm. By dividing the testing data and training data using a ratio of 20%: 80% randomised data 300 times. The results of the accuracy evaluation obtained from the Confusion Matrix show that the Random Forest Algorithm has the best accuracy value of 77%, Precision 89%, Recall 78% and F1-Score 83% with an estimator of 100 trees. While the KNN algorithm obtained accuracy of 73%, Precision 87%, Recall 73% and F1-Score 79% of the value of K = 7. Based on the comparison results of the two algorithms, it shows that the accuracy value obtained is greater than the Random Forest algorithm even though the value obtained is not much different.
Application of Academic Potential Test for New Student Admission Using Fisher-Yates Shuffle Algorithm Abdul Azis; Agung Triayudi; Endah Tri Esthi Handayani
SAGA: Journal of Technology and Information System Vol. 2 No. 1 (2024): February 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v2i1.254

Abstract

The selection process of new students in educational institutions, such as in Sekolah Menengah Kejuruan (SMK) Wisata Indonesia which still uses conventional methods using paper, has several challenges. One of the main challenges is test cheating, where prospective students may try to manipulate their test results to increase their chances of being accepted. In addition, another challenge faced by SMK Wisata Indonesia is that when the number of prospective students who register is very large, managing answers and exam results can become more complicated. This research aims to design and build an Android-based Academic Potential Test application by applying the Fisher-Yates Shuffle algorithm to randomize the order of questions. This research also uses the RUP (rational Unified Process) system development technique which has several phases, namely the Inception phase, Elaboration phase, Construction phase and Transition phase. The validation testing carried out obtained overall valid results so that the application that has been designed is in accordance with user needs. Meanwhile, usability testing in the Academic Potential Test Application using the SEQ method resulted in an average Likert score for students of 6.63 with a user-friendliness percentage of around 94%. As for teachers, the Likert average score is 6.53 with a percentage of ease of use of around 93%. This shows that the Academic Potential Test Application that has been built is EASY TO USE
Clustering of Generation X and Generation Y Communities in Cybersecurity Using the K-Means Algorithm (Case Study of Depok City, West Java) Wibowo, Adhitya Eka; Agung Triayudi
SAGA: Journal of Technology and Information System Vol. 2 No. 3 (2024): August 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v2i3.357

Abstract

This research aims to explore the differences in understanding and awareness of cybersecurity between Generation X and Generation Y in Depok City, West Java. The K-Means algorithm is used to group communities based on characteristics relevant to cybersecurity. The results of the study show that there are significant differences in understanding and behavior related to cybersecurity between the two generations. Generation X tends to be more cautious in using technology and has a better knowledge of cybersecurity risks, while Generation Y is more proficient in using digital devices and applications but pays less attention to security aspects. Factors that affect the level of cybersecurity awareness in both generation groups include knowledge of cyber threats, education, and demographic factors. The findings of this research can help stakeholders in increasing awareness and knowledge about cybersecurity and developing better solutions to protect users from cyber threats
Comparative Analysis of Performance of the Encryption and Decryption Times of Cryptography Made Yoga Mahardika; Agung Triayudi
SAGA: Journal of Technology and Information System Vol. 2 No. 3 (2024): August 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v2i3.359

Abstract

 Cryptography is the study of mathematical techniques to maintain information security, including the encryption process to protect data and decryption to return it to a readable form. The Rivest Shamir Adleman (RSA) algorithm and Elliptic Curve Cryptography (ECC) are two asymmetric key algorithms that are often used. RSA relies on large number factorization for security, while ECC uses elliptic curves that require more complex computation but are more efficient in resource usage. This study aims to compare the performance of the two algorithms in terms of encryption and decryption time, and analyze efficiency based on various key sizes and data amounts. The research method includes measuring encryption and decryption time with different data inputs using RSA and ECC at various key sizes. Experiments were conducted with data inputs of 128-bit to 512-bit and testing was conducted to measure the speed of each algorithm in the same situation. The results showed that RSA was faster in the encryption process than decryption, while ECC had a faster decryption time than encryption. However, the overall processing time for ECC is longer than RSA, especially when the key size is increased. These results provide insight into the advantages and disadvantages of each algorithm, which can be used as a basis for consideration in selecting algorithms for security applications that require high efficiency.
Jakarta Air Quality Classification Based On Air Pollutant Standard Index Using C4.5 And Naïve Bayes Algorithms Ramadhan, Duta Pramudya; Triayudi, Agung
SAGA: Journal of Technology and Information System Vol. 2 No. 4 (2024): November 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v2i4.395

Abstract

Increasing air pollution in DKI Jakarta has become an increasingly pressing environmental issue, which has a direct impact on public health and environmental sustainability. Therefore, it is very important to have a system that manages data-based air pollution levels. The purpose of this research is to classify air quality in DKI Jakarta through Air Pollutant Standard Index (ISPU) data. This data consists of parameters such as dust particles (PM10, PM2.5), sulfur dioxide (SO2), carbon monoxide (CO), surface ozone (O3), and nitrogen dioxide (NO2), as well as two classification algorithms used, namely C4.5 and Naïve Bayes. This research also seeks to compare the effectiveness of the two algorithms based on ISPU data collected in 15 Jakarta areas. The approach used in this research is to divide the data using three ratio scenarios, namely 70% : 30%, 80% : 20%, and 90%: 10%. In addition, performance assessment is carried out using accuracy, precision, recall and f1 score metrics. The experimental results showed better performance of C4.5, with an average accuracy of 95%, precision of 99%, recall of 94% and f1-score of 97%. In contrast, Naïve Bayes recorded an average accuracy of 81%, precision of 93%, recall of 73% and f1-score of 82%. These findings corroborate the validity of the C4. 5 algorithm is more effective in air quality classification based on ISPU, thus making it a reliable resource for air quality monitoring and management in DKI Jakarta, as well as supporting decision-making in air pollution control policies.
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Heryanto, Yayan Hidayat, Fajar Setiawan Hilman, Hilman Fikri Wijaya Hoga Saragih Ibnu Nur Khawarizmi Ikbal Danu Setiawan Iksal Iksal Iksal Iksal Imam Rizqi Imanuel Sinuraya Inastiana, Fardila indrawan indrawan ingsih, Andrian Ira Diana Sholihati Ira Diana Sholihati Ira Diana Solihati Ira Diana Solihati Iskandar Fitri Ismi Naili Qurrotul Aini Ismia Iwandini Jhiro Faran Juliana, Aji Jumpa Dorisman Rajagukguk Junior, Reza Phahlevi Kabeleke Melanesia L Kartika Salma Nadhiva Karyaningsih, Dentik Kiai Agus Priyaharto Mulia I Kodim Suparman Kusumaningtyas, Grasiella Yustika Rezka Talita Latif Arif Anggoro lia kamelia Lili Dwi Yulianto Listrina Turnip Ma'arif, Ridwan Ahmad Made Yoga Mahardika Mardiani, Eri Mauludani Muhammad Melati Indah Petiwi Melisa Theresia Mesran, Mesran Moh Dani Ariawan Muhamad Biyan Abdulah, Muhammad Andhika Maulana Muhammad Ariel Djamaludin Muhammad Aulia Hakam Muhammad Fadli Muhammad Faisal Abdillah Muhammad Faizal Muhammad Farhan Adistyra Muhammad Ilyas Sahputra Muhammad Jordy Muhammad Prabowo Chaniago Muhammad Rafi Fadhilah Muhammad Rizki Wardhana Muhammad Rizki Zidan Muhammad Rizky Hamdan Mutiara Mala Khairunnisa Nabilah Ananda Pratiwi Nadia Putri Ariyanti Nanda Fathi Rizky Nesha Putri Pratama Nifea Kusumawardhani Nofrisa, Dini Novi Dian Nathasia Novi Dian Nathasia Nur Hayati Nur Hayati Nur Hayati Nur Iskandar Zulkarnaen Nurfatanah Nurfatanah Nurfazriah Attamami Nurhadiyan, Thoha Oktaviani oktaviani Oktaviani Oktaviani Oky Triadi Sampurno Panjaitan, Fricia Oktaviani Penny Hendriyati Putra Dama Ramadhan Raffi Dima Sampurno Rafi Syahputra Rahmat Aji Santoso Raihan Abdi Negoro Rais Rabtsani, Muhamad Raka Alvianda Rama Setiawan Ramadhan, Duta Pramudya Ratih Mardianti Ratih Titi Komala Sari Ratih Titi Komalasari Repi, Viktor Vekky Ronald Resha Anjariansyah Reynaldo, Yohanes Reza Phahlevi Junior Riad Sahara Rian Aditia Rian Rasyidhi Rian Tineges Rian, Rian Hidayat Ricky Andri Widayat Riefand Fadhlurrohman Rifki Nur Apriyono Rima Tamara Aldisa Rima Tamara Aldisa Rima Tamara Aldisa Rio Al Dzahabi Yunas Ripin, Muhamad Riska Setiawati Riska Susilawati Rivaldi Okta Pratama Rizal Bagus Pambudi Rizal Toha, Muhammad Rizki Kurnia Rizky Setiawan Rodhi, Achmad Syaifudin Rosaima Situmorang Rosalina, Vidila Rudi Adityawan Sahputra, Muhammad Ilyas Sampurno, Raffi Dima Saragih, Nova Sari Ningsih Sawindri, Sawindri sawindri Seanand Sonia Shabrilianti Setiawan, Ikbal Danu Setiawati, Riska Setiono, Aji Shafira Shalehanny Shintia Mutiarani Sholihati, Ira Diana Simanjuntak, Handayani Simanungkalit, Racquel Terranova Singgih Yulianto Bastian Siti Nurhalizah Soepriyono, Gatot Solihati, Ira Diana Suginam Sugitha, I Kadek Agga Suhaimah, Atikah Suherman Suherman Sultana Namira Sumiati Sumiati Sumiati Sumiati Sumiati Sumiati Sumiati, Sumiati Suparman, Kodim Susilawati . Susilawati, Riska Sussolaikah, Kelik Syabana, Ulwi Syafrida Hafni Sahir Syavira Cahyaningsih Syirod, Achmad Thoha Nurhadiyan Titih Aji Kurniawan Titik Abdul Rahman Tiyas Asih Qurnia Putri Tobby Wiratama Putra Tyas Tono, Fikar Wahyu Untoroseto, Dedi Utami, Yulianti Pratiwi Vendy Blessing Gulo Vidila Rosalina Vivimaryati Vivimaryati Vivimaryati, Vivimaryati Wahid Al Jufri Wahyu Oktri Widyarto Wardhana, Muhammad Rizki Wibowo, Adhitya Eka WINARSIH Winarsih Winarsih Winarsih Winarsih Winarsih Winda Antika Putri Wiratama Putra, Tobby Wulan Kartika Murti Wulan Widhari Wulandari, Faras Tira Yana Tania Haryanto Yandi Makmur Yani Sugiyani Yanto Murnihati Waruwu Yohanes Reynaldo Yulianti Pratiwi Utami Yunan Fauzi Wijaya Zahrach Artamevia Zuraidah, Arika