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All Journal Jurnal Media Infotama International Journal of Artificial Intelligence Research ILKOM Jurnal Ilmiah KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Indonesia Raya Jurnal PADAMU NEGERI (Pengabdian pada Masyarakat Bidang Eksakta) Jurnal Dehasen Untuk Negeri Jurnal Media Computer Science Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Jurnal Komputer Indonesia Jurnal Komputer, Informasi dan Teknologi
Ila Yati Beti
Universitas Dehasen Bengkulu
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Journal : jurnal media computer science

 1 
Implementation Of Data Mining Using Algorithms A Priori in Determining The Pattern Of Product Purchases Perfume Sold Case Study On (Rafflesia Aromatic Professional Perfume) Kadek Dwi Andi Sasrawan; Dewi Suranti; Ila Yati Beti
Jurnal Media Computer Science Vol 1 No 2 (2022): Juli
Publisher : Fakultas Ilmu Komputer Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (724.976 KB) | DOI: 10.37676/jmcs.v1i2.2694

Abstract

At the rafflesia aromatic professional perfume store, we have not used a special application in determining the purchase pattern of perfume products sold and still use manual data processing such as writing in books, and do not utilize existing sales data and sales data only as an archive. So tejadi accumulation of data that is not in the know the benefits. Basically, the data set has useful information to make a decision about the pattern of perfume sales that are sold. One method that can solve the above problems is the Apriori algorithm method. Because the apriori algorithm is a suitable algorithm used to determine the search for Frequent itemsets using the Assciation rule technique with transaction data that is used for 1 month (January 1, 2022 – January 30, 2022).With the amount of 25 data from 15 transactions, support items can be displayed minimum support Value = 10% as many as 10 perfumes consisting of Celebrity, Citra Edition , Alasca , Topaza , Rock Star ,Be Delicitions , La Verne , B Agua Marine, Jasmin Note , and garuda. For a combination of 2 itemset is to use support 15% which consists of, Celebrity-Citra Edition, Celebrity-Alasca, Topaza-Rock Star, Rock Star-be Delicitionse, La Verne-B aqua Marine, B aqua Marine- Jasmine Note, then look for the rules of association that can meet the minimum requirement for confidence is to calculate the confidence associative rules based on a ❸ ( ❸ ) B with a minimum value of support taken is 20%, then that meets that there is a perfume most purchased by consumers is Citra edication, celebrity, alasca ,celebrity topaza, rock star the minimum value of support taken is 20%, then that there is a perfume most purchased by consumers is Citra edication, celebrity, alasca ,celebrity topaza, rock star.
Implementasi Data Mining Algoritma K-Nearest Neighbor Pada Penentuan Pemberian Sanksi Disiplin Di Rumah Sakit Umum Daerah Dr. M. Yunus Bengkulu Fiqi Aprianto; Jusuf Wahyudi; Ila Yati Beti
Jurnal Media Computer Science Vol 5 No 3 (2026): Juli
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v5i3.12078

Abstract

Regional General Hospital (RSUD) Dr. M. Yunus Bengkulu is a government-owned health care facility with a strategic role in providing health services to the public, making employee discipline an important factor to maintain. The determination of disciplinary sanctions for employees at RSUD Dr. M. Yunus Bengkulu is still carried out manually based on recorded violation data, which requires a relatively long time and has the potential to create subjectivity in decision making. This study aims to apply the data mining method using the K-Nearest Neighbor (K-NN) algorithm to classify employee disciplinary sanctions based on five assessment attributes, namely years of service, number of tardiness incidents, number of unexplained absences, SOP violations, and service ethics violations. The system was developed using the Waterfall development method and implemented as a web-based application using the PHP programming language and MySQL database. Testing was conducted on 20 training data and 20 testing data using a K value of 5, calculated from the square root of the number of training data. The test results show that the K-Nearest Neighbor algorithm is able to classify employee disciplinary violation data into four sanction categories, namely no sanction, verbal warning, written warning, and disciplinary sanction, with an accuracy rate of 90%. Black box testing results also show that all system functions run according to requirements. This research is expected to help the management of RSUD Dr. M. Yunus Bengkulu make decisions on employee disciplinary sanctions in a more objective, consistent, and measurable manner.
Expert System For Early Detection Of Attention Deficit Hyperactive Disorder (ADHD) At Soeprapto Psychiatric Hospital Using The Certainty Factor Method Aprilia Dwi Gumay; Herlina Latipa Sari; Ila Yati Beti
Jurnal Media Computer Science Vol 5 No 1 (2026): Januari
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v5i1.9110

Abstract

ADHD (Attention Deficit Hyperactive Disorder) is a mental disorder that causes children to have difficulty concentrating, as well as impulsive and hyperactive behavior. ADHD generally appears in children under 12 years of age, but ADHD that occurs in children can be carried into adulthood. This condition can impact a child's achievement if not treated early. Soeprapto Mental Hospital is one of the specialized hospitals that provides facilities and infrastructure in mental health and drug services for the community in Bengkulu Province. Based on the results of observations conducted at Soeprapto Mental Hospital Bengkulu, an average of 2-5 children per month are found to experience ADHD. One way to diagnose this disorder is to consult with an expert. The Expert System for Early Detection of Attention Deficit Hyperactive Disorder (ADHD) at Soeprapto Mental Hospital Using the Certainty Factor Method was created using the PHP programming language and MySQL database, and can be accessed online through the link https://adhdrsjksoepraptobkl.online/. This expert system for early detection of Attention Deficit Hyperactive Disorder (ADHD) can help the public, especially in Bengkulu Province, to consult by entering the patient's symptoms to obtain information on early detection of Attention Deficit Hyperactive Disorder. Based on testing conducted using the black box method both offline and online, it was found that the application's functionality ran well in terms of input, output, and the applied CF method. From the results of alpha testing conducted at Soeprapto Mental Hospital, it can be concluded that this expert system application can be a solution in the process of early identification of ADHD symptoms so that it can be used as a further consideration and faster intervention.
Co-Authors Abdussalam Al Akbar Adib Candora Ahmad Revaldo Aprilia Dwi Gumay Arius Satoni Kurniawansyah Desi Mahdalena Devi Sartika Devina Ninosari Dewi Suranti Edy Hermansyah Fiqi Aprianto Hendra Hendra Hengki Juliansa Herlina Latipa Sari Hoki Dewangga Jumadi, Juju Jusuf Wahyudi Kadek Dwi Andi Sasrawan Kanedi, Indra Kanedi Kanita Febianda Khairil Khairil Lena Elfianty Lianda, Deri Maryaningsih Maryaningsih Miki Andika Muhammad Wahyu Rizky Mutiara Octa Sari Nara Puspita Niken Disriani Oktian Dwi Pradana Putra Okto Farhan Maulana Panca Nugraha Rahman Ahmad Sapri , Sapri Siswanto Siswanto Tutut Dwinka Utari Venny Novita Sari Wika Apriza yupianti yupianti Yupianti, Yupianti