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All Journal JURNAL SISTEM INFORMASI BISNIS EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi CESS (Journal of Computer Engineering, System and Science) JURNAL PENGABDIAN KEPADA MASYARAKAT Jurnal Ilmiah KOMPUTASI Sistemasi: Jurnal Sistem Informasi Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JURNAL MEDIA INFORMATIKA BUDIDARMA SMARTICS Journal Indonesian Journal of Artificial Intelligence and Data Mining IJIS - Indonesian Journal On Information System JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Teknik Informatika UNIKA Santo Thomas JurTI (JURNAL TEKNOLOGI INFORMASI) Jiko (Jurnal Informatika dan komputer) ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA JISTech (Journal of Islamic Science and Technology) JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Teknologi Sistem Informasi dan Aplikasi IJISTECH (International Journal Of Information System & Technology) JOURNAL OF SCIENCE AND SOCIAL RESEARCH Simtek : Jurnal Sistem Informasi dan Teknik Komputer Jurnal Dedikasi Pendidikan Jurnal Teknologi Terpadu EDUMATIC: Jurnal Pendidikan Informatika METIK JURNAL Jurnal Mantik Progresif: Jurnal Ilmiah Komputer Jurnal Ilmiah Sains dan Teknologi (SAINTEK) Zonasi: Jurnal Sistem Informasi Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jatilima : Jurnal Multimedia Dan Teknologi Informasi Journal of Intelligent Decision Support System (IDSS) G-Tech : Jurnal Teknologi Terapan JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) INFOKUM Jurnal Sistem Komputer dan Informatika (JSON) TIN: TERAPAN INFORMATIKA NUSANTARA Brahmana : Jurnal Penerapan Kecerdasan Buatan Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Journal of Computer Networks, Architecture and High Performance Computing IJISTECH Journal La Multiapp Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Instal : Jurnal Komputer Jurnal Info Sains : Informatika dan Sains Journal of Dinda : Data Science, Information Technology, and Data Analytics Jurnal Mandiri IT Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Algoritma Edu Society: Jurnal Pendidikan, Ilmu Sosial dan Pengabdian Kepada Masyarakat SENTRI: Jurnal Riset Ilmiah Malcom: Indonesian Journal of Machine Learning and Computer Science STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer International Journal of Science and Environment SmartComp VISA: Journal of Vision and Ideas Da'watuna: Journal of Communication and Islamic Broadcasting Future Academia : The Journal of Multidisciplinary Research on Scientific and Advanced The Indonesian Journal of Computer Science Teknologi : Jurnal Ilmiah Sistem Informasi
Rakhmat Kurniawan R
State Islamic University Of North Sumatra
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Sentiment Analysis of Public Comments on Coldplay Concerts on Twitter Using the Naïve Bayes Method Dwisyahputra, Achmad Adbillah; Kurniawan, Rakhmat
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4202

Abstract

Social media platform Twitter had become one of the most popular platforms for communication and information sharing. In the context of entertainment events such as music concerts, Twitter became a bustling place with various comments and opinions from the public regarding their experiences attending a concert. Many fans shared their experiences about Coldplay concerts on Twitter. These comments were highly varied and required a thorough understanding to interpret the overall public sentiment. Event organizers and Coldplay's band managers needed to understand public feelings about their concerts. This information was crucial for the evaluation and improvement of future events. Comments on Twitter were often brief and diverse, making manual data processing inefficient and necessitating automated tools to understand the sentiment within them. Sentiment analysis, or opinion mining, was the process used to understand, extract, and process text data automatically to gather information about the sentiment contained in opinion sentences. Research on sentiment analysis frequently focused on opinions that contained positive or negative sentiments. To classify these positive and negative sentiments, the Naive Bayes (NB) classification method was employed. The purpose of this study was to analyze the sentiment of public comments about Coldplay concerts on Twitter using the Naive Bayes method. The expected outcome was to provide insights into public sentiment towards Coldplay concerts, which would be valuable for event organizers and the band's managers in evaluating and improving future events.
Penggunaan Algoritma K-Means Clustering untuk Mengelompokkan Pemain Berdasarkan Gaya Bermain Pada Battle Royale Call of Duty Mobile Qasthari, Mohd. Wildan; Kurniawan, Rakhmat
Future Academia : The Journal of Multidisciplinary Research on Scientific and Advanced Vol. 2 No. 3 (2024): Future Academia : The Journal of Multidisciplinary Research on Scientific and A
Publisher : Yayasan Sagita Akademia Maju

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61579/future.v2i3.177

Abstract

Penelitian ini fokus pada game Call of Duty Mobile karena kompleksitas dan popularitasnya. Tujuan utama penelitian adalah menginvestigasi pola permainan dan preferensi pemain untuk mengembangkan fitur game yang lebih adaptif. Metode Elbow digunakan untuk menentukan jumlah cluster optimal dalam proses clustering, menghasilkan tiga cluster: Rusher, Camper, dan Support Players. Hasil K-Means Clustering menunjukkan karakteristik sebagai berikut: Cluster 1 (Rusher) dengan gaya bermain agresif, rata-rata MVP = 217, Kill = 4223, Menang = 241, Damage = 1011,45, Akurasi = 20,99%; Cluster 2 (Camper) dengan gaya bermain pasif, rata-rata Kill = 4660, Menang = 119, Damage = 1229,51, Akurasi = 27,25%; Cluster 3 (Support Players) dengan fokus pada dukungan tim, rata-rata MVP = 206, Kill = 3541, Menang = 287, Damage = 1265,51, Akurasi = 13,59%. Kesimpulan menunjukkan pemain dapat dikelompokkan menjadi tiga klaster utama dengan karakteristik yang berbeda, yaitu Rusher, Camper, dan Support, yang membantu dalam pengembangan game yang lebih inovatif dan sesuai kebutuhan pasar.
Penerapan Algoritma Support Vector Machine Untuk Mendeteksi Autisme Khoiriah, Miftahul; Kurniawan, Rakhmat
Journal of Computer System and Informatics (JoSYC) Vol 5 No 4 (2024): August 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i4.5692

Abstract

Autism is a type of developmental disorder that can cause a neurological condition to disrupt brain function and impact a person's growth process, communication skills and social interaction abilities. In general, autism spectrum disorders can be detected in babies as early as 6 months. Things that interfere with a child's development occur because the structure of brain function is disturbed. This widespread disability is described as a spectrum disorder due to the considerable variation in how an individual manifests symptoms and their severity. By carrying out this detection, it can make it easier for parents to know whether their child has autism or not so they know what action to take. This research was conducted using a quantitative research methodology, where the research approach focuses on collecting and analyzing data that can be measured in numerical form using statistical techniques to obtain numbers and generalize. This approach involves the relationship between phenomena and cause and effect using a larger sample. After the previous stages are completed, then continue testing the prediction results using testing and accuracy data to obtain classification results. From the classification results above, the resulting classification value reaches 100% using test data and using accuracy values. Support Vector Machine (SVM) algorithm ) with a linear kernel has been applied to a dataset of autism in children. This model succeeded in separating classes well, showing that SVM is an effective algorithm for this classification problem.
Sentiment Analysis Of Public Comments On Quick Response Code Indonesian Standard (Qris) On Twitter Social Media Using The Naïve Bayes Classifier Method Fahri, Muhammad; Kurniawan, Rakhmat
Brahmana : Jurnal Penerapan Kecerdasan Buatan Vol 5, No 2 (2024): Edisi Juni
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/brahmana.v5i2.398

Abstract

Nowadays, technological developments have an inevitable impact on various aspects of human life. One real example of the development of E-Wallet which is very easy to access on a smartphone. However, the large variety of e-wallets available can be confusing for users because they need to download and manage many applications on their cellphones, therefore Bank Indonesia has found a solution for faster retail transactions, namely with a QR code or known as a Quick Response Code Indonesian Standard (QRIS). The use of QRIS has become a positive trend in the business and consumer world, this is due to the benefits of more efficient non-cash transaction processing. Even though QRIS is considered easy to use and brings benefits to many parties, not everyone responds positively. Some people also have negative comments regarding the QRIS payment system. To see their various views and opinions regarding the implementation of QRIS, researchers took one of the social media platforms, namely Twitter. Therefore, a public sentiment analysis was carried out to understand how the public responded to QRIS, whether it included positive or negative sentiment? In order to achieve this goal, researchers use the Naïve Bayes Classifier method, where this method analyzes a problem with a good level of accuracy and can help in evaluating concerns that need to be corrected, in order to obtain appropriate and accurate comparison results of negative and positive sentiment in analyzing sentiment. public comments on QRIS on Twitter social media using the Naïve Bayes Classifier method
Sentiment Analysis towards Full Movie Dirty Vote 2024 in X Using Support Vector Machine Method Azhari, Fajar; R, Rakhmat Kurniawan
Journal La Multiapp Vol. 5 No. 4 (2024): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v5i4.1459

Abstract

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.
Prototype of Microcontroller Based Water Pump Control System for Lettuce Plants Using Fuzzy Tsukamoto Rifansyah, Mhd. Roji; R, Rakhmat Kurniawan
Journal La Multiapp Vol. 5 No. 4 (2024): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v5i4.1462

Abstract

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.
IMPLEMENTATION OF THE FUZZY TIME SERIES METHOD FOR FORECASTING BLOOD NEEDS IN THE INDONESIAN RED CROSS (PMI) MEDAN Harahap, Rina Syafiddini; R, Rakhmat Kurniawan
JIKO (Jurnal Informatika dan Komputer) Vol 7, No 2 (2024)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v7i2.8614

Abstract

The primary issue faced by PMI (Indonesian Red Cross) about blood requirements is often associated with insufficient blood supplies to satisfy the demand of patients, particularly during emergencies or significant catastrophes such as natural calamities. Hence, it is essential to use appropriate methodologies to forecast blood requirements accurately and determine the quantity of blood bags required in the future. When forecasting calculations using fuzzy time series, the interval length is established at the start of the calculation procedure. The duration of the gap significantly affects the establishment of fuzzy associations, which in turn affects the difference in forecast computation outcomes. The investigation reveals that Group AB has the lowest Root Mean Square Error (RMSE) value of 136.90, indicating that your model demonstrates superior accuracy in predicting blood group AB compared to other blood groups. The RMSE score for Group O is 819.5, which suggests that your model's accuracy in predicting blood group O is lower compared to other blood groups
Implementasi K-Means Clustering dalam Mengklasifikasi Pengaruh Les Terhadap Prestasi Siswa dengan Metode Elbow Habibie, Alief Fathul; R, Rakhmat Kurniawan
Journal of Computer System and Informatics (JoSYC) Vol 6 No 1 (2024): November 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v6i1.6201

Abstract

Student achievement and ability are very important perspectives to consider. In this regard, Madrasah Ibtidaiyah Swasta (MIS) Al-Falah Medan is an educational institution that has a good reputation in both religious and other sciences. This study aims to analyze the influence of tutoring on student achievement at Madrasah Ibtidaiyah Swasta (MIS) Al-Falah Medan using the K-Means Clustering method and the Elbow technique to determine the optimal number of clusters. The data used in this research involves 514 students from classes 1A to 6B, with the analyzed variables including semester exam scores, participation in additional tutoring, and extracurricular activities. The analysis results show that students who participate in additional tutoring have higher average scores compared to those who do not. The average score of students in the semester exams is 87.71, while the average score for students participating in tutoring and extracurricular activities is 87.12. The clustering process results in four groups of students, with the highest performing group in cluster 2, while the lowest performing groups are in clusters 3 and 4. This research provides important information for the school in understanding the impact of tutoring on students' academic performance and can be used to improve learning strategies at MIS Al-Falah Medan.
Implementasi Metode Vikor Dalam Perekrutan Pegawai Tetap dan Cadangan Pada Mandali Packaging Lubis, Farhan Rusdy Asyhary; Kurniawan, Rakhmat
Journal of Computer System and Informatics (JoSYC) Vol 6 No 1 (2024): November 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v6i1.6290

Abstract

Today's technological advances are rapidly expanding, which opens up a huge opportunity for entrepreneurs to implement and develop a recruitment system for prospective employees as an effective and efficient means of promoting performance. Decision-making using technology makes the decision-making process run faster and more accurate. Mandali Packaging is a business model that moves in the field of creative industries, precisely in the sablon service that still implements the recruitment process of staff manually. The aim of this research is to implement and develop a decision support system using the VIKOR method to improve the effectiveness and objectivity of the recruitment process in Mandali Packaging. The method is used because it has the ability to solve multi-criterion problems, provide optimal solutions based on the preference of the established criteria, and also help reduce the bias of subjectivity that often occurs in manual decision-making. The ranking results show that Ali Imron Lubis received the 1st rank with the lowest score of 0 because in the VIKOR method, the lower the score, the higher the rank. This research demonstrates that the VIKOR method has the potential to provide more accurate and objective recommendations.
Classification of The Level of Public Satisfaction With the Use of Water Tourism Jetski in Balai Ujung Tanjung Using the Naïve Bayes Algorithm Fatwa, Nursalimah Isnaina; Kurniawan, Rakhmat
Indonesian Journal of Artificial Intelligence and Data Mining Vol 7, No 2 (2024): September 2024
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v7i2.32761

Abstract

Jetski water tourism is one of the attractions that is often visited by the public compared to other attractions. One of the factors causing this is because there is no fee charged to visitors. The source of funds used in this tourist attraction is from the local government budget. Be it in terms of assessment to improve facilities, or even comments on whether the Jetski Water Tourism facility is good or bad. Certainly, with the public comments, it will help the government in improving its services to the community, especially in the management of this water tourism Jetski.The sentiment data collected from visitors to this Water Tourism Jetski can be used as a benchmark for the government in improving this Water Tourism Jetski facility. Both in terms of scope and the Jetski media used. By knowing the responses and comments of the community regarding Jetski Wisata Air, the government can evaluate in order to support visitor satisfaction and so that Jetski Wisata Air can last long and compete with other tourist attractions. The Naïve Bayes Algorithm has often been used in a study in the form of sentiment analysis. The Naïve Bayes model shows that the level of public satisfaction with Jetski Water Tourism in Ujung Tanjung Hall, Tanjungbalai City can be predicted with an accuracy of 75%. This indicates that the model is quite effective in identifying the level of user satisfaction, although there is a 25% possibility of inaccuracy in prediction. With this accuracy, the model can provide useful insights for the evaluation and improvement of jetski tourism services, but it should be considered to conduct further analysis to improve accuracy and get a more comprehensive picture of community satisfaction
Co-Authors Abdul Halim Hasugian Agung Firmansyah Agung Pratama Ahmad Fauzi Ahmad Taufik Al Afkari Siahaan Aidil Halim Aidil Halim Lubis Aidil Halim Lubis Aidil Halim Lubis Alhafiz, Akhyar Alwy Azyari Harahap Amelia, Dara Andre Gusli Agus Riadi Annabil, M Haziq Armansyah Armansyah Armansyah Armansyah Arrafiq, Muhammad Sunni Asnawi, Azi Ayyina, Ayyina Nurhidayah Azhari, Fajar Azka El Husein Lubis, Sultan Bahari, Mhd Raja Doly Bayhaqi, Abdullah Bisri, Cholil Br Rambe, Indri Gusmita Dandi, Muhammad Khairil Dasopang, Buyung Satrio Dwisyahputra, Achmad Adbillah Eva Darwisah Harahap Fadiga, Muhammad Fahrul Afandi Fakhriyah, Mardhiyah Fakhrizal, Fiqri Fatwa, Nursalimah Isnaina Fikri Aulia Habibie, Alief Fathul Haliem, Alexander Hanafi, Muhammad Rizky Harahap, Nita Maharani Harahap, Rina Syafiddini Harahap, Shopiah Henni Melisa Hidayat, Zulfy Hidayatullah, Catur HP, Kiki Iranda Hsb, Khoiri Sutan Ibsan, Muhammad Hanafi Ilham Rizki Ananda Ilka Zufria Imam Zaki Husein Nst Ivan Prayuda Julianti, Miranda Jusli, Dara Taqa Assajidah Kesuma Dwi Ningtyas Khairin Nadia Khairunissabina, Khairunissabina Khoiriah, Miftahul Krisdantoro, Rino Lubis, Fahrian Zibran Lubis, Farhan Rusdy Asyhary M. Teguh wijaya Masdaliva, Fita Maulana, Fahmi Meilina, Indah Mey Hendra Putra Sirait Mhd Furqan Mhd Furqan Mhd. Furqan Furqan Mhd.Furqan Muhammad Abi Muzaki Muhammad Fahri, Muhammad Muhammad Ikhsan Muhammad Ikhsan Aji Muhammad Rizki Madani Muhammad Siddik Hasibuan Nasution, Fitri Handayani Nasution, Raihan Hafiz Nazry Luthfy, Fadhlun Noor Azizah Novita Jambak, Indah Nur Aini, Sakina Nurjanah, Trya Nurwana Nazla Saragih Padang, Bermiko Kasah Pravda, Michellia Delphi Isfahan Prayoga, Dio Putri Hanifah Putri, Raissa Ramanda Qasthari, Mohd. Wildan Rafli Bima Sakti Ramadhan, Alfan Ramadhan, Nuzul Ramadhan, Rio Fadli Ramadhan, Rizky Syahrul Ratna Dewi, Sri Reza Muhammad Rifansyah, Mhd. Roji Rifqi Alwanu Akmal Rina Filia Sari Rini Halila Nasution Rizki Ananda Putra Fajar Rizky Pratama Putra Rudi Riyandi Salsabillah, Ayna Sandira, Sri Delwis Saragih, Khoirul Azmi Saragih, Rafif Aprizki Sari, Desliana Sihombing, Rizki Andika Silva Ukhti Filla Silvi Joya Arditna Br Bukit Sinaga, Imam Adlin Sinaga, Muhammad Nabil Siregar, Muharram Soleh Siti Afifah Siregar Siti Ayu Hadisa Siti Nurul Aini, Siti Nurul Siti Sarah Harahap Siti Sumita Harahap Sri Marwah Badrin Sriani Sriani Sriani Sriani, S Stephani Silalahi Suhardi Suhardi Suhardi Suhardi, Suhardi Syahira, Melani Alka Syahputra, Pii Syahputra, Zidhane Syarifudin, Zaini Tbn, Ahmad Fauza Anshori Triase Triase Triase Triase, Triase Wahyu Kurniawan wijaya, M. Teguh Wini Istya Sari Lubis Yahya, Arfigo YENI SAFITRI Yudha, Muhammad Yudha Pratama Zahron, Almeranda Haryaveda Nurul