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Journal of Big Data Analytic and Artificial Intelligence
Published by Sekolah Tinggi Ilmu Manajemen Informatika dan Komputer Tarakanita Rahmawati
ISSN : 25979604     EISSN : 27223256     DOI : https://doi.org/10.71302
Core Subject : Science,
Computer Science & IT
JBIDAI adalah jurnal nasional berbahasa Indonesia versi online yang dikelola oleh Prodi Sistem Informasi STMIK PPKIA Tarakanita Rahmawati. Jurnal ini memuat hasil-hasil penelitian dengan cakupan fokus penelitian meliputi : Artificial Intelligence, Big Data, Data Mining, Information Retrieval, Knowledge Doscovering in Database dan bidang-bidang lainnya yang termasuk ke dalam rumpun ilmu tersebut.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 5 Documents
 1 
Search results for , issue "Vol 6 No 1 (2023): JBIDAI Juni 2023" : 5 Documents clear
Sistem Pakar Diagnosa Kerusakan Printer Menggunakan Metode Teorema Bayes Ellisa Harini; Indra Tri Saputra; Gusmana, Roman
Journal of Big Data Analytic and Artificial Intelligence Vol 6 No 1 (2023): JBIDAI Juni 2023
Publisher : STMIK PPKIA Tarakanita Rahmawati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71302/jbidai.v6i1.34

Abstract

Trijaya Computer performs computer sales and repair services located on Jl. Panglima Batur, Markoni. Printer repair demands quite a lot. Its massive usage is for printing reports, documents, and other things. Extensive use or even non-use of the printer can damage it. The research applies Bayes' Theorem analysis to an expert system to help admins diagnose printer damage. The discoverer of Theorem by Reverend Thomas Bayes (1701-1761). In general, it is to calculate the probability truth value of evidence. It can also interpret to calculate data uncertainty into definitive data by comparing "yes" or "no" data. The study result was an expert system for diagnosing printer damage as a support system or admins assistant with 80% accuracy. Eight of ten test data were equal to the expert's result.
Perbandingan Metode Klasifikasi Naïve Bayes dan C4.5 untuk Menentukan Potensi Nasabah Pada NSC Finance Marhaeni; Eviana Tjatur Putri; Gusmana, Roman
Journal of Big Data Analytic and Artificial Intelligence Vol 6 No 1 (2023): JBIDAI Juni 2023
Publisher : STMIK PPKIA Tarakanita Rahmawati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71302/jbidai.v6i1.36

Abstract

NSC Finance is a service business that provides loans to the public to meet their needs. However, NSC Finance does not use customer data to obtain necessary information. This research classifies customer data to gain information about promising customers, considered customers, and unpromising customers to loan re-offer. This study compares Naïve Bayes and C4.5 to help customer classification systems be more accurate by measuring accuracy using recall precision. These methods' comparative analyses are to investigate which methods have the highest classification accuracy. Therefore, the company can discover the highest accuracy rate of the classification results of these two methods. Results revealed that the classification patterns of 80 training data and 20 test data make it possible that data still have classification differences from the original data. Methods comparison indicated that the Naïve Bayes classification is better, with 85% accuracy, 94.44% precision, and 89.47% recall.
DESAIN APLIKASI PERAMALAN PENYEWAAN LAPANGAN FUTSAL MENGGUNAKAN METODE DOUBLE EXPONENTIAL SMOOTHING Saputri, Sasya Rahayu; Sinawati, Sinawati; lusi, lusiana
Journal of Big Data Analytic and Artificial Intelligence Vol 6 No 1 (2023): JBIDAI Juni 2023
Publisher : STMIK PPKIA Tarakanita Rahmawati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71302/jbidai.v6i1.40

Abstract

The Futsal Field is a sports venue that is usually rented out by the hour. The problem that occurs is that there is no computerized system that is used to predict the number of rental hours on the futsal field for the next period, so that the owner can know whether in the next period it will increase or decrease. Based on the description above, the author wants to create an application that can predict the amount of rent on one of the futsal fields for the next period. The author will use Brown's Double Exponential Smoothing method to calculate the forecast, then to calculate the accuracy of the forecast calculation using the Mean Absolute Percentage Error method. This research produces an application that can predict the amount of field rent in the next 3 months. The results obtained are, in field 1 for January 2020 it was 136 hours, February 2020 was 136 hours, and March 2020 was 135 hours. Then in field 2, for January 2020 it is 74 hours, February 2020 is 74 hours, and March 2020 is 73 hours. The accuracy rates for fields 1 and 2 are 2.18% and 9.42%, which means very good.
Perbandingan Metode Euclidean Probability dan Teorema Bayes untuk Diagnosa Penyakit Gigi Natalia Cangera; Yusni Amaliah; Gusmana, Roman
Journal of Big Data Analytic and Artificial Intelligence Vol 6 No 1 (2023): JBIDAI Juni 2023
Publisher : STMIK PPKIA Tarakanita Rahmawati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71302/jbidai.v6i1.42

Abstract

Dental disease is a disease that interferes with the normal function of the teeth. Dental disease has almost similar symptoms, so it requires an expert system of dental disease diagnosis for the proper treatment before the disease becomes more serious. The research employs Euclidean probability and Bayes' Theorem. Euclidean probability is a case approach for measuring probability based on causes, while Bayes' Theorem is a mathematical formula for determining conditional probability. Both of these methods determine the disease percentage based on the input symptoms. Their differences reflect in the calculation. Research shows that the Bayesian analysis is better than Euclidean probability, as evidenced by the similarity in the systems diagnostic with experts of 80% accuracy, while Euclidean probability is 40%.
Implementasi Logika Fuzzy Mamdani dalam Menentukan Jumlah Pemesanan Produk pada PT Forisa Nusapersada Area Tarakan: Implementation of Mamdani's Fuzzy Logic in Determining the Number of Product Orders at PT Forisa Nusapersada Tarakan Rita Tri Wulandari; Ummi Syafiqoh; M. Hafid
Journal of Big Data Analytic and Artificial Intelligence Vol 6 No 1 (2023): JBIDAI Juni 2023
Publisher : STMIK PPKIA Tarakanita Rahmawati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71302/jbidai.v6i1.44

Abstract

PT Forisa Nusapersada, Tarakan is an industrial company engaged in the distribution and marketing of products. When ordering products from the head office, since the customer's product demand sometimes increases or decreases every month, it is sometimes necessary to repeat the order within a month, thus affecting the product inventory in the warehouse. This study applied Fuzzy Mamdani to determine the number of orders based on sales data, goods stock and incoming goods from March to August 2021. This method has 5 stages, fuzzy set formation, rule formation, implication function application, rule composition and defuzzification. The input variables were demand and supply, while the output was orders. The results showed that the determination of the value of the fuzzy set domain can affect the final results differently for each product variant. In this study, the value of the fuzzy set domain was from the minimum and maximum values of sales data, goods stock and incoming goods.

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