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All Journal Jurnal Informatika dan Komputasi STMIK Indonesia Jakarta Format : Jurnal Imiah Teknik Informatika Community Services and Social Work Bulletin
Firdiansyah Firdaus Basri
Program Studi Sistem Informasi, STMIK Indonesia
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Languange, Linguistic, Communication & Media Social Sciences

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PERANCANGAN STRATEGI E-BISNIS BERBASIS BALANCED SCORECARD DAN COBIT PADA TOKO MENYK ANREZ Khasanah, Khasanah; Basri, Firdiansyah Firdaus
Jurnal Informatika dan Komputasi STMIK Indonesia Jakarta Vol 7, No 1 (2013): Jurnal Informatika dan Komputasi STMIK Indonesia Jakarta
Publisher : Jurnal Informatika dan Komputasi STMIK Indonesia Jakarta

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Abstract

Seiring pesatnya perkembangan Teknologi Informasi yang terjadi sekarang ini khususnya di negara kita Indonesia Teknologi tidak lagi menjadi barang yang aneh, bahkan sangat diperlukan untuk mendukung kinerja dari suatu organisasi. Untuk saat ini tanpa dukungan teknologi informasi sebuah perusahaan mungkin sangat mustahil untuk dapat berkembang. Dalam konteks ini, informasi dapat dikatakan menjadi kunci untuk mendukung dan meningkatkan manajemen perusahaan agar dapat memenangkan persaingan yang semakin lama akan semakin meningkat. Dalam hal ini bertujuan untuk membuat sebuah rekomendasi perencanaan strategi yang sesuai dengan visi dan misi Toko Menyk Anrez berdasarkan kesenjangan antara bisnis goals dengan IT goals. Nantinya diharapkan rekomendasi perecanaan strategi ini dapat dijadikan sebagai pertimbangan pihak manajemen, bagaimana sebaiknya strategi yang digunakan untuk mendukung kinerja layanan penjualan yang dilakukan oleh pihak Toko Menyk Anrez terutama dalam pelayanan.
SOSIALISASI PENTINGNYA DIGITAL MARKETING UNTUK PEMASARAN PRODUK UMKM MASYARAKAT DESA KARANG SARI KOTA TANGERANG Husain, Syepry Maulana; Aksani, Muhammad Lutfhi; Basri, Firdiansyah Firdaus; Saputra, Muhammad Rizka
Community Services and Social Work Bulletin Vol 3, No 1 (2023): Community Services and Social Work Bulletin Volume 3 No. 1 2023
Publisher : Universitas Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/cswb.v3i1.10374

Abstract

Digital marketing has become a very important aspect of modern marketing. This has changed the way businesses interact with customers and reach their target audience. Advances in technology, especially the internet and mobile devices, have changed the way people interact with information and brands. Easy access to the internet and mobile devices has opened the door to digital marketing. Today's consumers are more likely to search for products and services online, read reviews, and conduct research before making a purchasing decision. This creates opportunities for businesses to leverage digital platforms to reach and influence consumers. Digital marketing allows businesses to use user data to target advertising more precisely. This means advertising can be tailored to individual interests and preferences, making it more effective. One of the advantages of digital marketing is the ability to better measure and analyze campaign results. This allows businesses to understand what is working and what is not, so they can improve their marketing strategies. Many businesses compete for customer attention in the digital world. This drives innovation and continuous improvement in digital marketing practices. Digital marketing is more accessible to small and medium businesses, due to the lower cost of entry compared to traditional advertising. This provides an opportunity for small businesses to compete with big players. Although digital marketing offers many benefits, privacy issues also arise as data collection increases. This has resulted in changes in data privacy regulations, such as the European Union's GDPR. Digital marketing is becoming an important tool for businesses and organizations to grow their online presence, reach a wider audience, and influence consumers in a more measurable way. With a good understanding of trends and developments in digital marketing, people can use it to their advantage in promoting their business or understanding how information is presented to them online.
Klasifikasi Kepribadian Berdasarkan Dimensi Ekstraversi Berbasis Data Mining Menggunakan Extremely Randomized Trees Yanuardi, Yanuardi; Basri, Firdiansyah Firdaus; Aksani, Muhammad Luthfi
FORMAT Vol 14, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2025.v14.i2.008

Abstract

Personality is one of the fundamental aspects that distinguishes individual behavior, thought patterns, and interaction styles. The extraversion dimension, which is part of the Big Five Personality Traits framework, reflects an individual’s tendency to engage in social interactions with two main poles, namely introvert and extrovert. Identifying personality based on this dimension has various applications, ranging from education to employee recruitment. This study aims to develop a personality classification model based on the extraversion dimension using the Extremely Randomized Trees (ERT) algorithm and to compare its performance with other algorithms, namely Decision Tree, K-Nearest Neighbor (KNN), and Support Vector Machine (SVM). The dataset used in this study was obtained from the Kaggle platform, consisting of 2,900 entries and including social behavior indicators represented by five numerical variables and two categorical variables. The research methodology involves data preprocessing, exploratory data analysis, model construction, and evaluation using confusion matrix, precision, recall, F1-score, accuracy, and ROC-AUC. The results indicate that ERT achieves the best performance compared to the other algorithms. The ERT model obtained an accuracy of 92.69%, an F1-score of 0.9269, and a ROC-AUC of 0.9429, outperforming SVM (F1 0.9173; AUC 0.9300), KNN (F1 0.9086; AUC 0.9146), and Decision Tree (F1 0.8879; AUC 0.8876). The superiority of ERT is supported by its tree-based ensemble mechanism with high randomization, which enhances generalization, reduces variance, and captures complex non-linear interactions among behavioral variables. Therefore, ERT is proven to be effective in consistently distinguishing introvert and extrovert tendencies.
Co-Authors A.A. Ketut Agung Cahyawan W Aksani, Muhammad Lutfhi Aksani, Muhammad Luthfi Husain, Syepry Maulana Saputra, Muhammad Rizka Yanuardi Yanuardi