Klaim Artikel Anda
Verifikasi kepemilikan artikel akademik
Apakah artikel-artikel ini milik Anda?
Daftarkan diri Anda sebagai author untuk mengklaim artikel dan dapatkan profil akademik terverifikasi dengan fitur lengkap.
Badge Verifikasi
Profil terverifikasi resmi
Statistik Lengkap
H-index, sitasi, dan metrik
Visibilitas Tinggi
Tampil di direktori author
Kelola Publikasi
Dashboard artikel terpadu
Langkah-langkah Klaim Artikel:
- 1. Daftar akun author dengan email akademik Anda
- 2. Verifikasi email dan lengkapi profil
- 3. Login dan buka menu "Klaim Artikel"
- 4. Cari dan klaim artikel Anda
- 5. Tunggu verifikasi dari admin (1-3 hari kerja)
Menampilkan 1–10 dari 57 artikel
Analisis Klasifikasi Keputusan Belanja Konsumen Pada Toko Online XX Menggunakan Algoritma Decision Tree
Putri Maria Theresia Kehi
; I Wayan Sudiarsa
; Maria Oktaviani Suryati
; Yosefina Dehadi
; Maria Karlinda
Saturnus: Jurnal Teknologi dan Sistem Informasi
Vol 4
, No 1
(2026)
This study aims to analyze consumer purchasing behavior on e-commerce platforms using the Decision Tree algorithm as an easily interpretable classification method. The dataset used consists of 12,330 transaction records with 18 attributes representing visitor characteristics and user activities during interactions with the e-commerce platform. The research stages include data exploration to identify initial patterns, data preprocessing to handle missing values and class imbalance, splitting the...
Sumber Asli
Google Scholar
DOI
Implementasi Pipeline ETL dan Pemodelan Prediktif ARIMA dalam Memetakan Pola Pembelian Konsumen pada Dataset Marketplace
I Wayan Manik Mas Sri Dantya
; I Wayan Sudiarsa
; I Putu Kabinawa Raesa Putra
; Brian Adi Sapurta
; I Komang Hari Sastrawan
Repeater : Publikasi Teknik Informatika dan Jaringan
Vol 4
, No 1
(2026)
In the rapidly evolving digital economy, the ability to anticipate transaction surges is a strategic asset for marketplace platforms to maintain operational efficiency. This research aims to build an accurate daily transaction volume forecasting system thru the implementation of an Extract, Transform, and Load (ETL) pipeline and Autoregressive Integrated Moving Average (ARIMA) predictive modeling. The dataset used is sourced from dataset_olshop.csv, which includes transaction history for the ent...
Sumber Asli
Google Scholar
DOI
Optimasi Prediksi Harga Saham BBNI melalui Integrasi Proses ETL dan Algoritma Long Short-Term Memory
I Gusti Ngurah Rangga Mahesa
; I Wayan Sudiarsa
; I Putu Dicky Dharma Suryasa
; Putu Agus Aditya Putra
; Yulianus Kevin Dharmawa Sagur
Repeater : Publikasi Teknik Informatika dan Jaringan
Vol 4
, No 1
(2026)
Stock price prediction remains a complex challenge due to the dynamic and non-linear nature of financial markets, especially for banking stocks like PT Bank Negara Indonesia (Persero) Tbk (BBNI). This study aims to optimize BBNI stock price forecasting by integrating an automated Extract, Transform, Load (ETL) pipeline with the Long Short-Term Memory (LSTM) algorithm within a data engineering framework. Historical data from 2019 to 2025 were processed through a structured ETL sequence—including...
Sumber Asli
Google Scholar
DOI
Analisis Tren Gaji Profesi AI di Pasar Kerja Global Tahun 2025 Berdasarkan Data Lowongan Pekerjaan
Saturnus: Jurnal Teknologi dan Sistem Informasi
Vol 4
, No 1
(2026)
Rapid developments in the Artificial Intelligence (AI) industry have triggered an increased need for workers with specialized competencies, which has implications for significant variations in salary levels. This research aims to analyze the factors that influence salaries in the AI sector using the multiple linear regression method. The dataset used includes 15,000 AI job vacancies with variables including job and company characteristics. The data was engineered via the one-hot encoding method...
Sumber Asli
Google Scholar
DOI
Analisis Prediksi Penjualan Bisnis Retail Menggunakan Metode Decision Tree dan Random Forest
Agung Narayana Adhi Putra
; I Wayan Sudiarsa
; I Kadek Adi Gunawan
; Kadek Bagus Karunia Dwi Dharmayasa
; I Wayan Eka Saputra
Saturnus: Jurnal Teknologi dan Sistem Informasi
Vol 4
, No 1
(2026)
The retail industry generates an extremely large and continuously growing volume of transactional data along with the advancement of digital technology, thereby requiring sophisticated and systematic data analysis approaches to support effective and evidence-based business decision-making. This study aims to analyze retail sales data by utilizing the Retail Sales Dataset obtained from the Kaggle platform, which consists of 100,000 transaction records and broadly represents the characteristics of...
Sumber Asli
Google Scholar
DOI
BERBAGI PENGETAHUAN DAN KEPEMIMPINAN DIGITAL TERHADAP KINERJA PEGAWAI MELALUI KOMITMEN ORGANISASI(Studi pada Dinas Penanaman Modal dan Pelayanan Terpadu Satu Pintu Kabupaten Pemalang)
Innovation, Theory & Practice Management Journal
Vol 5
, No 1
(2026)
digital baik secara langsung maupun tidak langsung melalui komitmen organisasi pada pegawai Dinas Penanaman Modal dan Pelayanan Terpadu Satu Pintu Kabupaten Pemalang. Populasi yang digunakan pada penelitian ini adalah pegawai yang bekerja di Dinas Penanaman Modal dan Pelayanan Terpadu Satu Pintu Kabupaten Pemalang dengan jumlah 64 orang pegawai, dengan teknik pengambilan sampel menggunakan sample jenuh. Sumber data yang digunakan data primer, dengan metode pengumpulan data kuesioner. Teknik anal...
Sumber Asli
Google Scholar
DOI
Implementasi Algoritma Random Forest untuk Klasifikasi Rentang Harga Ponsel Berdasarkan Spesifikasi Teknis
Yustinus Liguori
; I Wayan Sudiarsa
; I Made Jagat Dita
; I Gusti Ngurah Galih Jimbar Baskara
; Pande Wisnu Wijaya Putra
Router : Jurnal Teknik Informatika dan Terapan
Vol 3
, No 4
(2025)
The rapid development of smartphone technology today creates challenges for consumers and manufacturers in determining an objective price range based on highly varied technical specifications. This study aims to implement the Random Forest algorithm in classifying smartphone price ranges into four main categories, namely low, mid-range, high, and flagship. The research method was carried out systematically through the stages of loading a dataset of 2,000 entries, exploratory data analysis (EDA)...
Sumber Asli
Google Scholar
DOI
Analisis Machine Learning pada Data Netflix Shows untuk Mengklasifikasikan Tren Genre dan Karakteristik Film
Mars: Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer
Vol 3
, No 6
(2025)
The rapid development of digital streaming platforms such as Netflix has generated a large volume of content data with diverse characteristics, thereby requiring effective analytical methods to understand emerging patterns and trends. This study aims to classify Netflix content into two main categories, namely movies and television shows, and to analyze genre trends and content characteristics using a data mining approach with the Naive Bayes algorithm. The dataset used in this study is the Netf...
Sumber Asli
Google Scholar
DOI
Sistem Pendukung Keputusan Untuk Klasifikasi Dan Pemeringkatan Pelanggan Dalam Mendukung Strategi Pemasaran Dengan Metode AHP Dan WSM
Jurnal Elektronika dan Komputer
Vol 18
, No 2
(2025)
Penelitian ini bertujuan untuk mengembangkan sistem pendukung keputusan yang dapat membantu tim Marketing Officer (MO) PT. Alvarel Technology Innovation dalam menentukan status pelanggan secara objektif dan terstruktur. Sistem ini dirancang menggunakan kombinasi metode Analytical Hierarchy Process (AHP) dan Weighted Sum Model (WSM). Metode AHP digunakan untuk menentukan bobot kriteria yang meliputi Potensial Pasar, Urgensi, Finansial, serta Hubungan dan Reputasi, dengan memastikan konsistensi ma...
Sumber Asli
Google Scholar
DOI
Strategic Air Transportation Management in Military Operations Other Than War (MOOTW) : Enhancing Archipelagic Resilience
International Journal of Management Science and Entrepreneurship
Vol 2
, No 4
(2025)
The purpose of this study is to investigate the strategic role of air transportation management in Military Operations Other Than War (MOOTW), particularly in archipelagic contexts such as Indonesia, where rapid humanitarian response, territorial surveillance, and civil–military cooperation are essential for resilience. By applying a Systematic Literature Review (SLR), this article synthesizes findings on humanitarian logistics, technological transformation, and policy frameworks for strengtheni...
Sumber Asli
Google Scholar
DOI