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Devi Sartika
Universitas Dehasen
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IMPLEMENTASI DATA MINING UNTUK PENGELOMPOKKAN WILAYAH PELANGGARAN LALU LINTAS MENGGUNAKAN METODE K-MEANS PADA POLRES BENGKULU Devi Sartika; Juju Jumadi
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 6, No 2 (2023): June 2023
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v6i2.1341

Abstract

Numbers of congestion and especially traffic violations occur everywhere in the city of Bengkulu, especially at city junctions. The large number of road users who do not comply with traffic regulations properly, every day can increase the rate of accidents and violations of traffic rules in driving in the Bengkulu City area. Due to the large piles of data on traffic violations in the jurisdiction of the Bengkulu City Police, each year only this data is processed into Microsoft Excel, making the data irregular. The process of extracting useful information in order to obtain violation data can be carried out using data mining methods, one of which is k-means clustering The implementation of the system uses the Visual Basic 2010 programming language. From the results of the tests conducted, it can be concluded that the areas with the most violations are the Tanah Patah and Betungan areas, for areas with violations in the moderate group there are Sawah Lebar, Pintu Batu, Padang Harapan, Kebun Tebeng and Simpang Nakau and for areas with low violations are the Swamp Makmur and Sungai Hitam areas
SISTEM PENDUKUNG KEPUTUSAN PENEPATAN PEGAWAI YANG AKAN DIPROMOSIKAN MENGGUNAKAN METODE MULTIFACTOR EVALUATION PROCESS PADA KANTOR BKPSDM KABIPATEN LEBONG Lia Veranica; Sapri Sapri; Devi Sartika
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 6, No 2 (2023): June 2023
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v6i2.1320

Abstract

Determination of employees who are promoted to positions aims to provide motivation and positive influence on other employees to further improve the work ethic in the Lebong District Regent's office. Determining who will be famous for mutation/promotion has of course gone through various stages of the process from within the Committee Team as well as passing the evaluation stages from the Committee based on certain criteria that have been set. These criteria include class (I, II, III and IV), tenure (long, long and recent), last education (Diploma, S1 and S2), training (1-3, 3-5, > 5) achievement (low, medium, high, and very high) and time period (short, medium and long). Lebong Regency Government Offices who meet the highest criteria will be selected to get a promotion for their dedication. However, the problem is how to make the right and competent choice as an employee who has high dedication if in the assessment alone there are employees who have almost the same rating score, close to the same, or even the exact same. It will be difficult for the Committee to make a decision to determine which employees are promoted to positions. Therefore, a Decision Support System with the application of the MFEP (Multifactor Evaluation Process) method can assist in making decisions on complex issues by simplifying the process. This system can assist decision makers in determining promotions quickly and precisely.
IMPLEMENTASI METODE CERTAINTY FACTOR UNTUK MENDETEKSI KERUSAKAN SEPEDA MOTOR PADA SENTRAL YAMAHA BENGKULU Avenzio Alif Rahman; Asnawati Asnawati; Devi Sartika
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 7, No 1 (2024): February 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i1.1681

Abstract

Abstract: Motorbikes are a means of transportation that is widely used by society in general, however, most people can only use them without knowing the symptoms and damage that occurs to their motorbikes. Due to the lack of knowledge and ignorance of motorbike users about the damage that occurs, motorbike users usually assume it is normal without knowing the actual damage and usually the user just takes it to a repair shop. Therefore, to help the public, especially automatic motorbike users, in providing knowledge and consultation on the diagnosis of damage that is often experienced, this is by designing and building an expert system application by applying the Certainty Factor method. Certainty Factor The Certainty Factor method has the advantage that it can measure whether something is certain or not certain, for example in diagnosing damage to an automatic motorbike. The final result of this research is an expert system that is able to diagnose automatic motorbike damage along with the confidence value of the damage selected or experienced by automatic motorbike users, which shows the system's level of confidence in the damage. Keywords: expert systems, automatic motorcycles, certainty factor Abstrak: Kendaraan sepeda motor merupakan salah satu alat transportasi yang banyak digunakan masyarakat pada umumnya, akan tetapi kebanyakan masyarakat hanya dapat menggunakannya saja tanpa mengetahui gejala serta kerusakan-kerusakan yang terjadi pada motornya. Karena minimnya pengetahuan serta ketidaktahuan pengguna sepeda motor dengan kerusakan yang terjadi, biasanya pengguna sepeda motor menganggap hal yang biasa tanpa mengetahui kerusakan yang sebenarnya dan biasanya pengguna hanya membawa ke bengkel. Maka dari itu untuk membantu masyarakat khususnya pengguna motor matic dalam memberikan pengetahun, dan konsultasi diagnosa kerusakan yang sering dialamai tersebut adalah dengan merancang dan membangun aplikasi sistem pakar dengan menerapkan metode Certainty Factor. Certainty Factor metode Certainty Factor memiliki keuntungan yaitu dapat mengukur sesuatu apakah yakin atau tidak yakin misalkan dalam mendiagosa kerusakan motor matic. Hasil akhir dari penelitian ini adalah sebuah sistem pakar yang mampu untuk melakukan diagnosa kerusakan motor matic beserta nilai keyakinan dari kerusakan yang dipilih atau dialami pengguna motor matic, yang menunjukkan tingkat keyakinan sistem terhadap kerusakan tersebut. Kata kunci: sistem pakar, motor matic, certainty factor
PENERAPAN METODE K - MEANS CLUSTERING DALAM MEMPREDIKSI TINGKAT PEMINAT EKSTRAKURIKULER PADA SISWA SMA MUHAMMADIYAH 4 BENGKULU Elsi Apri Yanti; Dewi Suranti; Devi Sartika
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 7, No 3 (2024): August 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i3.2173

Abstract

Abstract: Extracurricular activities are additional activities carried out outside of class hours which are carried out either at school or outside school with the aim of gaining additional knowledge, skills and insights and helping to shape the character of students according to their respective interests and talents. The extracurricular activities at SMA Muhammadiyah 4 Bengkulu include 4 extracurricular activities, namely soccer, volleyball, futsal, and scouts. K-Means is one of the data mining methods that is without direction, meaning that this method is applied without training and without a teacher and does not require an output target. The system development method used is Waterfall, K-Means Clustering. The application of the implementation of the K-Means Clustering method in predicting the level of interest in extracurricular activities at SMA Muhammadiyah 4 Bengkulu students was built using the Visual Basic.Net 2010 programming language with the Ms.Access database. From the results of the implementation and testing of the application, it shows that the application can provide recommendations for clustering students' interests and talents for extracurricular activities at SMA 4 Muhammadiyah 4 of Bengkulu City which are input into the application properly. Keywords: data mining, k-means, clustering, extracurricular activities Abstrak: Kegiatan ekstrakurikuler atau ekskul adalah kegiatan tambahan yang dilakukan di luar jam pelajaran yang dilakukan baik di sekolah atau di luar sekolah dengan tujuan untuk mendapatkan tambahan pengetahuan, keterampilan dan wawasan serta membantu membentuk karakter peserta didik sesuai dengan minat dan bakat masing. Adapun Kegiatan ekstrakurikuler di sekolah SMA Muhammadiyah 4 Bengkulu meliputi 4 ekstrakurikuler yaitu Sepak bola, Bola Voli, Futsal, dan Pramuka. K-Means merupakan salah satu metode data mining yang bersifat tanpa arahan, maksudnya metode ini diterapkan tanpa adanya latihan dan tanpa ada guru serta tidak memerlukan target output.  Metode pengembangan sistem yang digunakan adalah Waterfall, K-Means Clustering . Aplikasi implementasi metode K-Means Clustering Dalam Memprediksi Tingkat Peminat Kegiatan Ekstrakurikuler Pada Siswa SMA Muhammadiyah 4 Bengkulu dibangun dengan menggunakan bahasa pemrograman Visual Basic.Net 2010 dengan database Ms.Access. Dari hasil implementasi dan pengujian dari aplikasi menunjukkan bahwa aplikasi dapat memberikan rekomendasi clustering minat dan bakat siswa terhadap kegiatan ekstrakurikuler di SMA 4 Muhammadiyah 4 Kota Bengkulu yang di – input ke dalam aplikasi dengan baiki. Kata kunci: data mining, k-means, clustering, ekstrakurikuler 
Co-Authors Asnawati Asnawati Avenzio Alif Rahman Dewi Suranti Elsi Apri Yanti Juju Jumadi Lia Veranica Sapri Sapri