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Bulletin of Artificial Intelligence
Published by CV. Graha Mitra Edukasi
ISSN : -     EISSN : 29623944     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering
The field of study of the Bulletin of Artificial Intelligence journal, in the field of Artificial Intelligence, includes: 1) Decision Support Systems, 2) Data Mining, 3) Expert Systems, 4) Big Data, 5) Text Mining, and 6) Natural Language Processing. But does not rule out the possibility of publishing manuscripts in the field of Computer Science.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 26 Documents
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Penerapan Metode K-Means Dalam Pengelompokkan Buku Untuk Menentukan Minat Baca Pada Perpustakaan Daerah Kota Medan Harefa, Misael Oktavianda; Aripin, Soeb
Bulletin of Artificial Intelligence Vol 3 No 1 (2024): April 2024
Publisher : Graha Mitra Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62866/buai.v3i1.129

Abstract

The library is a facility that functions as an information center, a source of various knowledge, research, recreation and cultural preservation. The Medan City Regional Library is a library organized by the regional government using general funds which aims to serve the public in obtaining comprehensive information without distinguishing gender, religion, race, age, occupation and position. In 2021 the Medan city regional library has 28 thousands of titles books in several categories. Of the many books contained in the library, a system must be needed where the system is useful for both the library and the reader in maximizing grouping of books and searching books easily by the reader, therefore the K-Means Clustering method is used, where the method This is a method in data mining that processes clustering data that is grouped into one or more clusters. In this study, 100 samples of book category data were used in the Medan City library. This study groups the data categories into 3 clusters, namely the most desirable, desirable and least desirable. The results of this method process will find out the most popular book category data so that in the future it will be a consideration for the librarian to increase the collection of books at the Medan City regional library. The process of calculating the K-Means method in grouping books is only carried out until the 2nd iteration because iteration -3 gets the same value. In Cluster 1 (Most Interested) choose 6 categories of books including Category 020-Library and Information, 070-Mass Media, Journalism and Publication, 050-Psychology, 420-Indonesian, 600-Technology, 650-Management. In Cluster 2 (Desired) choose 16 categories of books including 000-General Publications and General Information, 030-Encyclopedias and Books, 040-Biography, 050-Magazines and Journals, 090-Manuscripts and Rare Books, 210-Islamic Religion, 300-Science Social, 320-Political Science, 330-Economics, 410-Indonesian, 510-Mathematics, 620-Technical Sciences, 770-Photography and Photos, 780-Music, 910-General Travel Geography, 930-Old World History. And in cluster 3 (Less Interested) 78 categories of books were selected. 10 of them 010-Bibliography, 060-Association of Organizations and Museums, 080-Quotes, 100-Philosophy and Psychology, 110-Mathematics, 120-Epistimology, 030-Parapsychology and Occultism, 040-Philosophical Thought, 060 Logical Philosophy, 070-Ethics.
Penerapan Algoritma K-Means Dalam Mengelompokkan Jumlah Penerimaan Sinyal Telepon Seluler Di Sumatera Utara Sitompul, Wati Rizky Pebrianti; Solikhun, Solikhun; Saputra, Widodo; Oktaviani, Selli; windarto, agus perdana
Bulletin of Artificial Intelligence Vol 2 No 2 (2023): October 2023
Publisher : Graha Mitra Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62866/buai.v2i2.137

Abstract

The purpose of this study was to cluster the number of cell phone signal reception in North Sumatra. The source of the data used is obtained from BPS. The variable used is the number of cell phone reception signals in North Sumatra. This research uses Data Mining Technique with K-means algorithm. It is hoped that the results of this study can provide input to the North Sumatra Province in order to determine the reception of cellular telephone signals, so as to increase the growth and development of telephone signal reception in North Sumatra. And 4G/LTE data obtained that there are 4 high clusters, namely (Mandailing Natal, Simalungun, Deli Serdang, Padang Lawas), 17 medium clusters, namely (Nias, South Tapanuli, Labuan Batu, Humbang Hasundutan, West Pakpak, Samosir, Labuhan Batu, South , Labuhan Batu Utara, North Nias, West Nias, Sibolga, Tanjung Balai, Pematangsiantar, Tebing Tinggi, Binjai, Padang Sidempuan, Gunung Sitoli), and there are 2 low clusters (Central Tapanuli, North Tapanuli, Toba, Asahan, Dairi, Karo , Langkat, South Nias, Serdang Bedagai, Batu Bara, North Padang Lawas, Medan).
Penerapan Metode Certainty Factor Dalam Mendiagnosa Penyakit Otitis Eksterna Manik, Lastri; Saragi, Naomi Labora; Utomo, Dito Putro
Bulletin of Artificial Intelligence Vol 3 No 1 (2024): April 2024
Publisher : Graha Mitra Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62866/buai.v3i1.138

Abstract

Otitis externa is a common ear problem that often requires an accurate diagnosis for effective treatment. The Certainty Factor Method is an artificial intelligence approach used to support the diagnostic process. This research aims to apply the Certainty Factor Method in diagnosing otitis externa. Patient data, including symptoms, medical history, and examination results, are used to build a knowledge base that is then utilized in the diagnostic process. This method allows for improved accuracy in determining diagnoses by considering the confidence level associated with each symptom and examination result. Experimental results show that the application of the Certainty Factor Method can assist doctors in diagnosing otitis externa with higher accuracy compared to conventional methods. With this approach, diagnoses are made with higher confidence levels, which can aid in providing accurate and prompt treatment for patients suffering from otitis externa. The Certainty Factor Method has the potential for use in other medical contexts and can make a positive contribution to problem-solving in the healthcare field. This research underscores the importance of technology in supporting ear disease diagnosis and providing more reliable solutions for managing otitis externa. By leveraging the Certainty Factor approach, doctors can be more efficient and effective in responding to patients' conditions, thus reducing the risk of complications and enhancing healthcare quality. Therefore, this study offers a valuable contribution to the fields of medicine and computer science in improving the diagnosis of ear diseases, such as otitis externa, so that patients can receive better and faster care.
Sistem Pakar Diagnosa Paget's Disease dengan Menerapkan Algoritma Teorema Bayes Saragih, Rico Albert; Marbun, Desika; Mesran, Mesran
Bulletin of Artificial Intelligence Vol 3 No 1 (2024): April 2024
Publisher : Graha Mitra Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62866/buai.v3i1.139

Abstract

Paget's Disease, also known as Paget's Disease of the bone, is a bone disorder that typically arises in the elderly, particularly after the age of 40. The risk of this disease increases with advancing age. Aging and genetic factors are believed to play a role in the development of this condition. Symptoms include bone pain, bone fragility, abnormal bone growth, changes in bone shape, decreased hearing, as well as symptoms such as headaches, dizziness, and joint complaints. Expert systems or artificial intelligence draw inspiration from the knowledge of experts to analyze situations. With algorithms like the Bayes theorem, this system provides solutions to emerging issues. In this context, expert systems aid doctors in identifying diseases without face-to-face consultations. The Bayes theorem serves as the foundation for this mechanism, emulating expert abilities. This research applies the Bayes theorem for an efficient and objective diagnosis of Paget's Disease. The results indicate a strong likelihood of patients having Paget's Disease at 73.87%. Consequently, the use of expert systems has the potential to enhance efficiency and objectivity in handling cases, assisting doctors in formulating diagnoses based on presenting symptoms.
Sistem Pendukung Keputusan Rekomendasi Hotel Bintang Tiga Menggunakan Kombinasi Entropy dan Combine Compromise Solution Wahyudi, Agung Deni; Sumanto, Sumanto; Setiawansyah, Setiawansyah; Yudhistira, Aditia
Bulletin of Artificial Intelligence Vol 3 No 1 (2024): April 2024
Publisher : Graha Mitra Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62866/buai.v3i1.142

Abstract

Three Star Hotels are lodging places that offer the perfect balance between comfort, adequate facilities, and affordable prices. With a friendly atmosphere and professional service, the hotel welcomes guests from various backgrounds warmly. One of the problems in choosing a Three Star Hotel is confusion due to variations in quality and facilities among hotels that have similar ratings. Although they share the same categories, the standards and services offered can vary greatly. This can make potential guests find it difficult to choose the right hotel that suits their preferences and needs. In addition, some hotels may not meet guest expectations due to issues such as poor cleanliness or facilities that do not function properly, which can generate dissatisfaction. The combination of Entropy weighting and the Combine Compromise Solution method can be a powerful approach in providing three-star hotel recommendations to potential guests. By combining these two methods, it can produce more informed and objective three-star hotel recommendations. Entropy weighting helps in assessing the relative importance of each criterion, while the Combine Compromise Solution allows us to reach a compromise solution that blends different preferences and criteria. The result is recommendations that are more accurate and tailored to potential guests' needs and preferences. The recommendation results showed that AN Hotel with a value of 1,782 got 1st place, AL Hotel with 1.271 got 2nd place, and YN Hotel with 1,145 got 3rd rank.
Implementation of the Preference Selection Index (PSI) Method in Determining the Best Coffee Shop Windarto, Agus Perdana; Mesran, Mesran; Saidah, Fatiyah; Ambarsari, Erlin Windia
Bulletin of Artificial Intelligence Vol 3 No 1 (2024): April 2024
Publisher : Graha Mitra Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62866/buai.v3i1.145

Abstract

The decision support system can be claimed to be a personal computer capable of running data into information so that when taking a semi-structured or problem-specific decision, A coffee shop is a place that prioritizes the sale of coffee with a variety of brewing methods, ranging from cold brew, percolator, Turkish coffee, automatic drip, moka pot, tubruk, Arabica, and many more. In this study, the authors used the PSI (preference selection index) method so that the selection of the best coffee shop was carried out by making a decision matrix, normalizing the decision matrix, calculating the mean value of normalized data, determining the variation of preferences, determining storage in preference values, determining the weight of the criteria, and calculating the PSI value so as to find the best alternative. The criteria used in the selection of coffee shops are five: food, drink, service, entertainment, and parking. Then the final result of the best alternative value is A6 as the best coffee shop in Tanjung Morawa, with a result of 3.702 using the PSI method

Page 3 of 3 | Total Record : 26

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