JANUARI–JUNI 2025, VOL 6(1)

Dublin Core

Title

JANUARI–JUNI 2025, VOL 6(1)

Contributor

Sri Wahyuni

Collection Items

PENGARUH TIKTOK ADS DAN BLACK CAMPAIGN TERHADAP PERILAKU PEMBELIAN KONSUMEN DI KOTA BATAM
The use of social media platforms such as TikTok as a tool for digital marketing continues to grow along with
the increasing number of users, both for building brand awareness through TikTok Ads and indirectly through
black campaigns. This study…

ANALISIS FAKTOR SOSIAL EKONOMI YANG MEMPENGARUHI RENDAHNYA CAPAIAN PENDIDIKAN DI INDONESIA MENGGUNAKAN KOMBINASI METODE DATA MINING
Educational inequality remains a persistent issue in Indonesia, particularly in regions with challenging
socio-economic conditions. This study aims to analyze how various socio-economic factors influence the
average years of schooling across…

PENGEMBANGAN APLIKASI BERBASIS WEB UNTUK PERAWATAN MOBIL DAN PENGELOLAAN BENGKEL DENGAN METODE PROTOTIPE
This study presents the development of CekMobilmu.com, a web-based application designed to support car
owners and automotive workshop in Jakarta by facilitating the digital recording of vehicle maintenance and
repair activities. In response to…

OPTIMALISASI SISTEM INFORMASI BERBASIS AGILE UNTUK PENGELOLAAN BIAYA VARIABEL DAN EXCHANGE RATE DI INDUSTRI FMCG
In the FastMoving Consumer Goods (FMCG) industry, managing variable costs and exchange rates is a
major challenge that affects operational efficiency and business decision-making. This study aims to
develop an Agile-based information system that…

OPTIMASI ALGORITMA RANDOM FOREST UNTUK MENINGKATKAN AKURASI PREDIKSI INDEKS MASSA TUBUH (BMI)
Accurate Body Mass Index (BMI) prediction is essential for detecting obesity risks and related diseases.
This study optimizes the Random Forest algorithm to enhance BMI prediction accuracy through
hyperparameter tuning and feature selection. The…

PENGELOMPOKAN PENJUALAN PRODUK DENGAN MENGGUNAKAN K-MEANS CLUSTERING : STUDI KASUS ANALISIS PENJUALAN COFFEE SHOP OLEH KAGGLE.COM
The purpose of this study is to categorize coffee shop items sold by analyzing sales records with the KMeans clustering method. The Kaggle dataset consists of three main features: Product_ID, number of items
sold (Transaction_Qty), and price per…
View all 6 items

Collection Tree