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All Journal Proceeding International Conference on Information Technology and Business Jurnal Publika Pengabdian Masyarakat Journal of Computer Science and Informatics (JOCSI)
Suci Mutiara
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Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media

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Naïve Bayes Classifier Algorithm for Predicting Non-Participation of Elections in Lampung Province Fitria -; Rifad Sobah; Chairani Fauzi; Septilia Arfida; Suci Mutiara; Siti Nurlaila
Prosiding International conference on Information Technology and Business (ICITB) 2022: INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND BUSINESS (ICITB) 8
Publisher : Proceeding International Conference on Information Technology and Business

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Abstract

Several problems related to the DPT (Permanent Voter List) including the KPU (General Election Commission) it is difficult to get the NIK (Population Identification Number) of people who are in correctional institutions or prisoners, beginner voters who do not have an ID card (Kartu Tanda Sipil) who are currently in prison. study in student dormitories, Islamic boarding schools, and others who are outside the city, the number of which is 3-5% of invalid NIK, voters who do not have a resident identity, voters with KTP (Kartu Identity Card)/old Family Card and NIK (Population Identification Number) ) invalid around 7-19% and voters are difficult to find around 5-8% so that the KPU must-visit houses as regulated in the legislation. This could allow not all DPT (Permanent Voters List) to be registered.Naïve Bayes Classifier is one of the classification methods used in Data Mining which is based on the Bayes theorem. Bayes is a simple probability-based prediction technique based on the application of Bayes' theorem (or Bayes' rule) with strong (naive) independent (independence) assumptions. Naive Bayes is only a method for analyzing, it takes other media to display information that is easy to understand the results of the Naïve Bayes Classifier calculations. Pentaho data integration is a tool that integrates large amounts of data, calls from Excel, MySQL, and provides instructions for existing data. Tableau is an application that will improve, tableau can call data that has been integrated and display the data in the form of diagrams, text, spatial data, and points from locations.Keywords: Naïve Bayes Classifier, Algorithm, Election Commission
STRATEGI PEMASARAN SECARA ONLINE PADA UMKM BUDIDAYA LELE BERBASIS TEKNOLOGI DI DESA HURUN KECAMATAN TELUK PANDAN KABUPATEN PESAWARAN Anggalia Wibasuri; A.K Yohanson; Suci Mutiara; Anggawidia Wibaselppa; Fidha Citra Ardila
Jurnal Publika Pengabdian Masyarakat Vol 5, No 2 (2023): Jurnal Publika Pengabdian Masyarakat
Publisher : Institut Informatika dan Bisnis Darmajaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30873/jppm.v5i2.3948

Abstract

Pemasaran online telah menjadi strategi pemasaran suatu usaha saat ini yang sedang berkembang, tidak terkecuali usaha kecil dan menengah Desa Hurun memiliki masyarakat yang bermata pencaharian penduduk ialah petani, peternak, pedagang. Tetapi sebagian besar mata pencaharian penduduk Desa Hurun ialah pertanian dan perternakan. Budidaya ikan lelepun menjadi salah satu budidaya yang banyak dijumpai pada Desa tersebut. Desa Hurun sudah memiliki beberapa usaha micro kecil menengah (UMKM). Sehingga kami hanya membantu UMKM tersebut dalam melakukan penerapan strategi pemasaran online pada produk yang berbasis teknologi. Kegiatan pengabdian masyarakat yang telah dilakukan melakukan inovasi budidaya, pembuatan media pemasaran, pembinaan membuat anggaran sederhana, editing video. Target peserta dalam kegiatan tersebut UMKM dan masyarakat serta pemangku Desa Harun Teluk Pandan. Hasil kegiatan yang telah dicapai, sebagai berikut: 1) Cara mengembangkan UMKM Budidaya Lele di Desa Hurun yaitu menciptakan Inovasi kreatif dalam pemberian label, merk, dan kemasan sehingga mambantu UMKM dan masyarakat dalam mengenal produk, dan  sebagai usaha penghasilan tambahan ekonomi Masyarakat. 2) Pembuatan Laporan keuangan UMKM Budidaya Lele berbasis teknologi sehingga dapat mempermudah penggunanya. 3) Memberikan pelatihan Teknologi Informasi bagi Perangkat Desa guna mempercepat dalam menyelesaikan pekerjaan administrasi pemerintahan Hurun.
IMPLEMENTASI ALGORITMA K-MEANS CLUSTERING BERBASIS ANDROID UNTUK MENENTUKAN NILAI KELULUSAN PADA SMK NEGERI 3 METRO Amalyanda Azhari; Angger Sasmito; Mei Ratnasari; Suci Mutiara
Journal of Computer Science and Informatics (JOCSI) Vol 4 No 1 (2026): Agustus
Publisher : EDU PARTNER INDONESIA

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Abstract

Clustering nilai kelulusan merupakan sistem berbasis teknologi informasi yang menerapkan konsep data mining untuk mengelompokkan data nilai kelulusan secara terstruktur dan sistematis. Sistem ini digunakan untuk mengelola serta menyebarluaskan informasi persentase kelulusan dalam bentuk digital. SMK Negeri 3 Metro sebagai sekolah menengah kejuruan terus berupaya meningkatkan mutu layanan pendidikan melalui pemanfaatan teknologi informasi dan komunikasi (TIK). Penerapan clustering pada sistem nilai kelulusan memungkinkan pengelompokan nilai nilai kelulusan siswa sehingga memudahkan siswa, guru, dan pihak sekolah dalam mengakses serta menganalisis informasi akademik. Pengembangan sistem clustering nilai kelulusan memerlukan pemahaman yang mendalam terhadap kebutuhan dan karakteristik pengguna agar sistem dapat berjalan secara optimal. Penelitian ini bertujuan untuk mengkaji efektivitas sistem data mining clustering nilai kelulusan dalam meningkatkan manajemen dan akses informasi nilai kelulusan di SMK Negeri 3 Metro. Sistem dikembangkan menggunakan bahasa pemrograman PHP, HTML, dan CSS dengan metode pengembangan waterfall. Hasil penelitian menunjukkan bahwa sistem mampu memberikan kemudahan akses informasi nilai nilai kelulusan dan kelulusan bagi siswa, guru, serta orang tua kapan saja dan di mana saja tanpa harus datang langsung ke sekolah. Clustering of passing scores is an information technology-based system that applies data mining concepts to group diploma grade data in a structured and systematic manner. This system is used to manage and disseminate graduation percentage information in digital form. SMK Negeri 3 Metro, as a vocational high school, continues to strive to improve the quality of educational services through the use of information and communication technology (ICT). The application of clustering to the diploma system allows for grouping of student diploma grades, making it easier for students, teachers, and the school to access and analyze academic information. The development of a diploma clustering system requires a deep understanding of user needs and characteristics so that the system can run optimally. This study aims to assess the effectiveness of the diploma clustering data mining system in improving the management and access of diploma grade information at SMK Negeri 3 Metro. The system was developed using the PHP, HTML, and CSS programming languages ​​​​with the waterfall development method. The results show that the system is able to provide easy access to diploma and graduation grade information for students, teachers, and parents anytime and anywhere without having to come directly to school.
Co-Authors A.K Yohanson Amalyanda Azhari Anggalia Wibasuri Anggawidia Wibaselppa Angger Sasmito Chairani Fauzi Fidha Citra Ardila Fitria - Mei Ratnasari Rifad Sobah septilia arfida Siti Nurlaila