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All Journal BERNAS: Jurnal Pengabdian Kepada Masyarakat CSRID
Dahriani Hakim Tanjung, Dahriani Hakim
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Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Dentistry Education Environmental Science Languange, Linguistic, Communication & Media Mathematics Neuroscience Nursing Public Health Social Sciences Veterinary Other

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Landing Page (LPg) Sebagai Media Digital Marketing Dalam Memulai Usaha Di SMK Swasta Gajah Mada Sembiring, Hilda Elsera Br; Fujiati, Fujiati; Dewi, Rofiqoh; Tanjung, Dahriani Hakim; Verina, Wiwi; Sanjaya, Andi
BERNAS: Jurnal Pengabdian Kepada Masyarakat Vol. 6 No. 1 (2025)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/jb.v6i1.10293

Abstract

Kehadiran digital marekting saat ini memudahkan segala kalangan dalam memulai bisnis dengan tepat dan sesuai dengan target yang dituju. Belanja di internet juga bukanlah sebuah hal baru yang dilakukan calon pembeli ketika mencari informasi produk yang akan dibeli [1]. Salah satu teknologi tersebut Landing Page yang dapat digunakan sebagai media pemasaran online yang dapat menjangkau calon pembeli, penggunaannya bisa dilakukan dan di kontrol dimana saja tanpa menguras waktu dan tenaga serta hanya membutuhkan modal berupa smartphone ataupun laptop (sejenisnya) [2]. Salah satu peran Landing page adalah dapat mengubah pengunjung menjadi pelanggan sebagi wujud prospek potensial dan gerbang konversi dalam pemasaran digital [3]. Untuk itu dibutuhkan sebuah pelatihan Landing page kepada siswa/i Sekolah Menengah Kejuruan (SMK) sebagai dasar awal praktek memulai bisnis ketika selesai sekolah karena salah tujuan siswa/i SMK ketika tamat sekolah yaitu siap kerja dan berwirausaha [4]. Oleh karena itu siswa/i SMK selalu di latih dan diajarkan secara langsung mengenai praktek dalam memulai bisnis dan berkarir. Hal tersebut menjadi salah satu tujuan dari pelatihan ini yaitu untuk membekali siswa/i dalam berwirausaha digital dengan memanfaatkan platform Landing page agar mendapatkan calon pembeli yang prospek sesuai dengan bisnis yang dipasarkan.
Analisis Perbandingan Algoritma Klasifikasi Terhadap Data Problem Mesin ATM Dengan Rapidminer Tanjung, Dahriani Hakim; Dewi, Rofiqoh; Fujiati, Fujiati; Salim, Rinrin Meilani
CSRID (Computer Science Research and Its Development Journal) Vol. 16 No. 2 (2024): June 2024
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid.16.2.2024.188-200

Abstract

The aim of the proposed research is to compare and test the accuracy of data mining classification algorithms. Comparing algorithms that depend on different parameters of a given data set. There are learning and classification algorithms that are used to analyze, study and classify the available data. However, the problem is finding the best algorithm and the desired results with the highest level of accuracy in predicting future values ​​or events from a data set. Where the classification models used are the C4.5 and Naïve Bayes algorithms. Testing and validation using k-fold Cross Validation as well as evaluating the performance of the prediction model using the ROC-AUC graph with graphic visualization. The data used as samples were taken from ATM machine problem data with a total of approximately 250 samples. Testing was carried out with the help of the Rapidminer tool with operators and parameters used in creating models of the algorithms being compared. The tests that have been carried out prove that the C4.5 algorithm has the best performance with an average accuracy value of 96.00%, a recall value of 97.78% and a precision value of 92.14%, while the naïve Bayes algorithm produces an accuracy value of 83. 00%, the recall value is 76.40% and the precision value is 84.82%. Apart from that, evaluation and validation in this test is also seen based on the ROC curve called AUC (Area Under the ROC Curve) where for the C4.5 algorithm the value is 0.931 while naïve Bayes is 0.894 so the C4.5 algorithm is categorized as Very Good Classification because it has a value between 0.90-1.00. These results show that the C4.5 algorithm is proven to be a potentially effective and efficient classification algorithm.
Co-Authors Andi Sanjaya Fujiati ., Fujiati Rofiqoh Dewi Salim, Rinrin Meilani Sembiring, Hilda Elsera Br Wiwi Verina, Wiwi