Bulletin of Artificial Intelligence
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.
Articles
26 Documents
<![CDATA[Peramalan Nilai Penjualan Gas Elpiji 3 Kg di Sumatera Utara dengan bantuan Analisis Metode Jaringan Saraf Tiruan ]]>
<![CDATA[Maulidya Rahma Siregar]]>;
<![CDATA[Adinda Putri Azhari]]>;
<![CDATA[Dedy Hartama]]>;
<![CDATA[Agus Perdana Windarto]]>
<![CDATA[ Bulletin of Artificial Intelligence Vol 1 No 2 (2022): October 2022 ]]>
Publisher : <![CDATA[Graha Mitra Edukasi ]]>
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<![CDATA[This research is related to forecasting the sales value of 3 Kg LPG in North Sumatra. The level of sales is influenced by customer satisfaction, service and customer needs. The purpose of this study is to determine the level of sales of 3 Kg LPG in North Sumatra and can overcome problems and overcome the amount of LPG demand in North Sumatra. So this research is needed using an artificial neural network method with a backpropagation algorithm to find the best sales results. The data used is divided into 2 parts, namely training and test data. The best network is taken from the Mean Square error (MSE) value and the smallest test. The experiments carried out in this study used a data rotation pattern, with 6 training and testing models. The experimental results of the 3-10-1 model are tests with the highest accuracy value, which is 100% and the MSE test is 0.00100005]]>
<![CDATA[Perbandingan Algoritma Sequitur dan RLE Dalam Kompresi Teks ]]>
<![CDATA[Rian Syahputra]]>
<![CDATA[ Bulletin of Artificial Intelligence Vol 1 No 1 (2022): April 2022 ]]>
Publisher : <![CDATA[Graha Mitra Edukasi ]]>
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<![CDATA[Information on a news blog is not small if we look at the amount of information that will be conveyed in a news story. A news blog also uses a lot of storage memory in the database because of the large amount of information in the form of text that is stored, and also affects the speed of data transmission. Compression techniques aimed at reducing data can be used to reduce stored text and save storage media and speed up the data transmission process. Using the Sequitur algorithm is better with a compression ratio of 80.95% of the initial size, because the sequitur algorithm removes symbol pairs that appear more than once with a new symbol. While the RLE algorithm in this study cannot be used because it does not meet the RLE algorithm so that the compression process does not occur due to the absence of the same characters appearing successively, this is a weakness of the RLE algorithm]]>
<![CDATA[PENGAMANAN FILE TEKS DENGAN ALGORITMA ENKRIPSI POHLIG-HELLMAN DAN STEGANOGRAFI EZSTEGO PADA FILE AUDIO ]]>
<![CDATA[Herwansyah Herwansyah]]>
<![CDATA[ Bulletin of Artificial Intelligence Vol 2 No 1 (2023): April 2023 ]]>
Publisher : <![CDATA[Graha Mitra Edukasi ]]>
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<![CDATA[Pada kriptografi proses enkripsi dilakukan dengan cara merubah data tersebut ke dalam bentuk data yang lain yang tidak dapat dimengerti dan dipahami maknanya. Namun dengan bentuk lainnya data tersebut dapat menimbulkan kecurigaan, maka setelah data tersebut dienkripsi, perlu adanya melakukan penyembunyian data kedalam sebuah objek tanpa merubah bentuk objek tersebut dengan teknik steganografi. Proses dengan double pengamanan file teks dilakukan dengan teknik kriptografi menggunakan algoritma Pohlig-Hellman yang kemudian hasil enkripsi berupa chipertext disisipkan kembali kedalam objek audio menggunakan algoritma Ezstego. Dari hasil analisa, karakter chipertext yang telah di enkripsi menggunakan algoritma Pohlig-Hellman, dapat disisipkan dengan akurat kedalam objek audio tanpa memrubah bentuk audio tersebut menggunakan algoritma Ezstego]]>
<![CDATA[Sistem Pendukung Keputusan Pemberian Sanksi Pelanggaran Kedisiplinan Guru Dalam Proses Belajar Mengajar Menggunakan Metode Elemination And Choice Translation Reality ]]>
<![CDATA[Aulia Husna]]>
<![CDATA[ Bulletin of Artificial Intelligence Vol 2 No 1 (2023): April 2023 ]]>
Publisher : <![CDATA[Graha Mitra Edukasi ]]>
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<![CDATA[Sanctions are actions (punishments) in order to force someone to follow the rules or to comply with the provisions of the law. The imposition of sanctions at SMKN 1 Lubuk Pakam is adjusted to the number of violations committed by the teacher by looking at the data that has been collected. Many problems occurred during the process of imposing sanctions, such as data on violations that were forgotten in the data, teachers who committed violations were not recorded because of family relationships or double data violations. This will give the impression that the sanctions are selective so that the sanctions given are not in accordance with the violations committed by the teacher. The solution that can be done to this problem is to build a decision support system to assist in sanctioning violations of teacher discipline in the on-target teaching and learning process using the method of elimination and choice translation reality. The results of this study can simplify and accelerate in determining the imposition of sanctions, so that this system can be used to assist the SMKN 1 Lubuk Pakam in making decisions to impose sanctions on teacher disciplinary violations in the teaching and learning process that are on target and are expected to overcome all weaknesses in determining the imposition of sanctions.]]>
<![CDATA[Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik Dengan Menggunakan Metode MABAC ]]>
<![CDATA[Toni Aman Waruwu]]>
<![CDATA[ Bulletin of Artificial Intelligence Vol 2 No 1 (2023): April 2023 ]]>
Publisher : <![CDATA[Graha Mitra Edukasi ]]>
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<![CDATA[1001 Mart is a minimarket which is engaged in selling basic daily needs such as rice, sugar, cooking oil, milk, baby diapers and others. The leadership of 1001 Mart always holds the best employee selection every year, the selection of the best employees is done to increase motivation or morale for employees to work even harder. The problem that occurs in this case is that it is difficult for 1001 Mart to make decisions in selecting the best employees. In this research, to solve the problems experienced by the 1001 Mart, the author designed a decision support system for selecting the best employees at 1001 Mart using the MABAC method. The design of this application uses the php programming language and the MySQL database as data storage media into the system. This decision support system will later assist 1001 Mart in determining the best employees based on predetermined criteria. The MABAC method is also expected to give accurate decision results so that no more mistakes will occur in selecting the best employees at 1001 Mart.]]>
<![CDATA[Jaringan Syaraf Tiruan Untuk Klasifikasi Penyakit Demam Menggunakan Algoritma Backpropagation ]]>
<![CDATA[Dwi Andini]]>
<![CDATA[ Bulletin of Artificial Intelligence Vol 2 No 1 (2023): April 2023 ]]>
Publisher : <![CDATA[Graha Mitra Edukasi ]]>
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<![CDATA[Technological advances have helped solve problems in various fields, especially in the health sector, one of which is in disease classification which makes it easier to control disease management to see what type of disease the disease belongs to. The classification process using a computer can be applied using various classification methods, one of which is the Artificial Neural Network method with the Backpropagation Algorithm. An artificial neural network is an information processing system that is designed to imitate the workings of the human brain by carrying out the learning process through changes in the weight of its synapses. One of the problems that can apply the Backpropagation algorithm in the case of classification is the classification of Fever Disease (Dengue and Typhoid) because of the similarity of the symptoms of the two diseases. The application of the Backpropagation algorithm in the Classification of Fever (Dengue and Typhoid Dengue Fever) begins with the training stages on 135 training data, and the best variation of learning rate and hidden layer neurons is obtained by trial and error. The test was carried out on test data as many as 15 data, the test results were in the form of a classification of fever diseases which were compared with the actual target.]]>
<![CDATA[Sistem Pendukung Keputusan Pemilihan Pengrajin Ulos Ragi Hotang Terbaik Di Desa Meat Menerapkan Metode Maut ]]>
<![CDATA[Irvan Siahaan]]>
<![CDATA[ Bulletin of Artificial Intelligence Vol 2 No 2 (2023): October 2023 ]]>
Publisher : <![CDATA[Graha Mitra Edukasi ]]>
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<![CDATA[Meat Village is a center for making hotang yeast ulos which is carried out by women. The Meat Village Office selects the best yeast hotang ulos craftsmen every year to improve the community's economy and provide enthusiasm for hotang yeast ulos craftsmen who aim to improve the quality of hotang yeast ulos which has criteria for neatness, motifs, and color combinations. The problem faced by the Meat Village office is still using the manual method, especially in determining the best hotang yeast ulos craftsmen in Meat Village. On this occasion the author proposes the selection of hotang yeast ulos craftsmen using a decision support system using the MAUT Method, programming in Microsoft Visual Studio 2010 with Visual Basic language and MySQL as a database. From the results of my research I want to help the Meat Village office in determining the best hotang yeast ulos craftsmen in Meat Village by using a Decision Support System using the multi attribute utility theory (MAUT) method. Those who got the best score in selecting hotang yeast ulos craftsmen were A8 on behalf of Ester Simanjuntak with a score of 0.427 as the first rank, A9 with the name Oni Siahaan the value of 0.363 in the second rank and A4 with the name Herbeslina Maharaja the value of 0.344 in the third rank.]]>
<![CDATA[Implementasi Algoritma Yamamoto’s Recursive Code Dalam Mengkompresi File Gambar ]]>
<![CDATA[Lulu Nurhidayanti Nasution]]>
<![CDATA[ Bulletin of Artificial Intelligence Vol 2 No 2 (2023): October 2023 ]]>
Publisher : <![CDATA[Graha Mitra Edukasi ]]>
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<![CDATA[The size of the data stored whether it is stored on a computer or in cloud storage is one of the problems in the computer world. One of the best solutions to overcome this problem is to use compression techniques. In this study, the author uses Yamamoto's Recursive Code Algorithm to compress image files. Image files with bitmap (bmp) extension have a smaller size than those in jpeg format, this causes problems if the recipient's download speed is slow or the internet connection is unstable, information, information cannot be processed immediately because the data transfer time is too long. For that we need a technique to change the size of the data to be smaller . This technique is known as data compression. Data compression is a process of converting a set of data into a form of code to save the need for data storage. On this basis, the application of Yamamoto's Recursive Code Algorithm in Compressing Image Files is made in order to help computer users compress image files that are initially large into their smallest size.]]>
<![CDATA[Multiple Attribute Decision Making Menggunakan Metode TOPSIS Dalam Penentuan Staff Marketing Terbaik ]]>
<![CDATA[Setiawansyah Setiawansyah]]>;
<![CDATA[Very Hendra Saputra]]>;
<![CDATA[Sanriomi Sintaro]]>;
<![CDATA[Ahmad Ari Aldino]]>
<![CDATA[ Bulletin of Artificial Intelligence Vol 2 No 2 (2023): October 2023 ]]>
Publisher : <![CDATA[Graha Mitra Edukasi ]]>
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<![CDATA[Multiple Attribute Decision Making (MADM) is an approach used in decision making to select the best alternative from a number of given criteria or attributes. This research aims to apply the TOPSIS method in selecting the best marketing staff so that it can become a reference and benchmark for companies in selecting the best marketing staff using a decision support system model. The results of the ranking of the selection of the best marketing staff who got rank 1 with a value of 0.644, namely Ahmad, rank 2 with a value of 0.539, namely Hermawan, rank 3 with a value of 0.529, namely Santoso, rank 4 with a value of 0.443, namely Jayanti, rank 5 with a value of 0.399, namely Heru.]]>
<![CDATA[Sistem Pakar Identifikasi Penyakit Tanam Ubi Kayu Dengan Metode Certainty Factor ]]>
<![CDATA[Jambak, Rinaldi]]>
<![CDATA[ Bulletin of Artificial Intelligence Vol 2 No 2 (2023): October 2023 ]]>
Publisher : <![CDATA[Graha Mitra Edukasi ]]>
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DOI: 10.62866/buai.v2i2.102
<![CDATA[Ubi Kayu merupakan salah satu sayuran yang banyak ditemukan di Indonesia. Ubi Kayu adalah salah satu tanaman yang rentan terkena penyakit. Hampir semua Ubi Kayu yang ada saat ini belum ada yang memiliki daya tahan kuat bila sudah terserang. Untuk menanggulangi penyakit tanaman Ubi Kayu, maka dibangunlah aplikasi sistem pakar dengan menggunakan metode Certainty Factor. Sistem pakar merupakan salah satu pemecahan yang potensial untuk mengatasi masalah diagnosis penyakit pada tanaman ubi kayu. Dengan system pakar dapat mempermudah kerja atau bahkan mengganti tenaga ahli, menggabungkan ilmu dan pengalaman dari beberapa tenaga ahli, dan menyediakan keahlian yang diperlukan suatu proyek yang tidak memiliki tenaga ahli dengan media konsultasi. Hasil uji konsultasi dengan sistem ini menunjukkan bahwa sistem mampu menentukan penyakit beserta pengobatan dan penanganan awal yang harus dilakukan, berdasarkan gejala-gejala yang sebelumnya dipilih oleh pengguna.]]>
