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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) Sinkron : Jurnal dan Penelitian Teknik Informatika Creative Information Technology Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING JUTEI (Jurnal Terapan Teknologi Informasi) JUTIM (Jurnal Teknik Informatika Musirawas) Jurnal Telematika JIEMS (Journal of Industrial Engineering and Management Systems) JOISIE (Journal Of Information Systems And Informatics Engineering) Zonasi: Jurnal Sistem Informasi JISA (Jurnal Informatika dan Sains) Jurnal Algoritma, Logika dan Komputasi
Thenata, Angelina P.
Universitas Bunda Mulia
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Other

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PERANCANGAN DAN ANALISIS DATA WAREHOUSE MENGGUNAKAN NINE STEP DESIGN PADA PERUSAHAAN SKY Thenata, Angelina Pramana; Agus, Agus; Sinata, Frans
Jurnal Algoritma, Logika dan Komputasi Vol 8, No 1 (2025): Jurnal ALU, Maret 2025
Publisher : Universitas Bunda Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30813/j-alu.v8i1.8250

Abstract

Perkembangan dunia teknologi informasi yang sudah semakin pesat memberikan dampak yang besar pada perusahaan, terutama dalam dunia bisnis yang semakin sulit untuk bersaing. Perusahaan Sky merupakan perusahaan yang bergerak di bidang penjualan aksesoris variasi kendaraan roda dua. Perusahaan ini masih menggunakan cara yang konvensional dalam proses mencatat transaksi penjualan, sehingga membutuhkan waktu yang lama dalam mengolah data tersebut. Sebuah data warehouse berfungsi untuk mengkonsolidasikan dan meringkas data perusahaan yang berbeda sehingga dapat membantu para pemimpin/manajer menganalisis data yang ada untuk membuat keputusan strategis dengan cepat dan akurat. Berdasarkan permasalahan tersebut penelitian ini bertujuan untuk merancang dan mengimplementasikan data warehouse menggunakan metode Nine Step Design serta menyajikan hasil analisisnya melalui visualisasi guna mendukung pengambilan keputusan strategis di perusahaan Sky. Adapun perancangan data warehouse ini menggunakan pemodelan data skema bintang dan proses migrasi database ke dalam data warehouse (ETL) dengan menggunakan aplikasi Pentaho Data Integration. Kemudian dalam pengolahan dan analisis data menggunakan OLAP (On-Line Analytical Processing) dengan menggunakan aplikasi Tableau. Hasil penelitian ini berupa 3 tabel dimensi dan 1 tabel fakta, yaitu dimensi waktu, dimensi produk, dimensi admin, dan fakta transaksi. Perancangan data warehouse pada perusahaan Sky ini membantu perusahaan dalam menunjukkan perkembangan transaksi bulanan, dan tahunan. Hasil tersebut dapat meningkatkan mutu pelayanan perusahaan, serta dapat menjadi landasan dalam pengambilan keputusan untuk menentukan strategi penjualan dan perencanaan stok bulanan atau tahunan.
Analysis of Public Sentiment Towards President Prabowo's Work Program Using The CNN Thenata, Angelina Pramana; Saputra, Dimas Sakti Reka
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9394

Abstract

Digital media has now become the primary means for Indonesians to receive and respond to information, including the work programs presented by Prabowo Subianto. One of the programs that is widely discussed by the public is related to efforts to improve the national economy. Public responses to this issue are widespread on social media, reflecting diverse sentiments. Therefore, this study aims to analyze the sentiment of comments from social media users X regarding President Prabowo's work programs in the economic sector, using a deep learning approach based on the Convolutional Neural Network (CNN) architecture. The methods employed include data collection, text preprocessing, and training a CNN model. The dataset used consisted of 2,467 data points, with 1,086 labeled as positive and 1,381 labeled as negative. The test results showed that the model achieved an accuracy of 87.45% and an Area Under the Curve (AUC) score of 0.9373, indicating excellent classification performance in distinguishing between positive and negative sentiments. This study proves that the combination of CNN and FastText is a practical approach to understanding text-based public opinion from social media.
Klasifikasi Terawasi Anomali Suara Kipas Industri Menggunakan Jaringan Saraf Tiruan dan Fitur Akustik Rekayasa Thenata, Angelina Pramana; ., Ranny; Hakim, Bhustomy; Kaunang, Fergie Joanda
Jurnal Telematika Vol. 20 No. 1 (2025)
Publisher : Yayasan Petra Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61769/telematika.v20i1.772

Abstract

Penelitian ini menggunakan pendekatan supervised learning berbasis jaringan saraf untuk deteksi anomali pada sistem kipas industry. Dengan subset data FAN dari MIMII (malfunctioning industrial machine investigation and inspection) dataset dengan 530 rekaman berlabel (383 normal dan 147 abnormal), penelitian ini mengekstraksi fitur akustik yang meliputi mel-frequency cepstral coefficients (MFCC), spectral descriptor (centroid, roll off), serta temporal measures (zero-crossing rate, autocorrelation). Uji statistik univariat menunjukkan sejumlah koefisien MFCC dan fitur domain waktu berbeda signifikan antar kelas (p < 0,05). Model jaringan saraf feed-forward dengan dua lapisan tersembunyi berukuran 64 unit (aktivasi ReLU) dan regularisasi dropout dilatih menggunakan stratified cross validation dengan 5-fold sehingga menghasilkan nilai F1 rata-rata sebesar 89,9%. Penggunaan beberapa nilai ambang (τ ∈ {0,3–0,7}) menegaskan kekokohan model yang terlihat pada hasil data uji dengan nilai ambang terpilih adalah τ = 0,5 yang mencapai precision sebesar 100%, recall = 93,10%, F1 = 96,43%, dan akurasi = 98,11% (hasil identik diperoleh pada τ = 0,6–0,7; sementara τ = 0,3 memberikan recall lebih tinggi). Model juga menghasilkan nilai AUC-ROC sebesar 0,9978 yang mendekati ideal dan menunjukkan daya diskriminasi lintas-ambang yang sangat baik. Temuan ini memperlihatkan bahwa penggabungan fitur akustik yang dapat diinterpretasikan dengan pengklasifikasi saraf yang ringkas memungkinkan deteksi anomali non-invasif yang akurat untuk penerapan Industri 4.0 dengan kebutuhan perangkat keras minimal.
Data Pipeline Architecture with Near Real-Time Streaming Multiple Source Indonesian Online News Data Lake Thenata, Angelina Pramana
JISA(Jurnal Informatika dan Sains) Vol 3, No 1 (2020): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v3i1.657

Abstract

The rapid development of information has made online news increasingly needed. Online news attracts readers' attention by providing convenience and speed in presenting news from various fields. However, the large amount (volume) of online news that spreads in a short time (velocity) and the public's need to consume news in various references (variety) can affect people's lives. Therefore, the government as the regulator and news agencies need to monitor online news circulating. Based on these problems, the researcher proposes a data lake architectural design that is suitable for online news and can run in real-time. Data lakes can solve the main problems of Big Data (volume, velocity, variety). In proposing this data lake architecture, the researcher conducted a literature study and analyzed the flow of the data lake architecture according to online news. Furthermore, the researcher will use this architecture to combine and uniform the online news data structure from several online news channels and then stream it in real-time to fill the data lake. The results of using the data lake architecture for online news will be stored on MongoDB which functions as a database to store all data for both the short and long term. Finally, this data lake will be a means to accommodate, dive into, and analyze the circulating online news data. Keywords – Data Lake, Online News, Real-Time
Classification of Facial Acne Types Based on Self-Supervised Learning using DINOv2 Chardaputeri, Gantari; Thenata, Angelina Pramana
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11856

Abstract

Acne is a common inflammatory skin condition that can affect an individual’s psychological well-being and overall quality of life. The inability to independently recognize specific types of acne often leads to the use of inappropriate skincare products. This situation highlights the need for an image-based classification system that can provide accurate visual identification. The self-supervised learning method Distillation with NO Labels, version 2 (DINOv2), is employed as a feature extractor to classify four types of acne—Acne fulminans, Acne nodules, Papules, and Pustules—using the “skin-90” dataset. The fine-tuning process is conducted through a Parameter-Efficient Fine-Tuning (PEFT) approach using Low-Rank Adaptation (LoRA) to adjust the model’s visual representations to the acne domain without updating all parameters in full, followed by integration with a classification head. The results show that the model achieves an accuracy of 90.70%, with precision, recall, and F1-score values of 90.64%, 90.68%, and 90.57%, respectively. The findings suggest that the proposed architectural design and training configuration are suitable for capturing relevant visual patterns of acne, while further validation is required to assess robustness across more diverse data distributions.
Co-Authors ., Ranny Agus, Agus Andhika Galuh Prabawati Arron, Rivaltino Asvian Sulaeman Bhustomy Hakim Chardaputeri, Gantari Kaunang, Fergie Joanda Lim Yong Teck Matheus Alvian Wikanargo Muh Rizky Ramadhan Muhammad Syukri Mustafa Novian Adi Prasetyo Ranny, Ranny Saputra, Dimas Sakti Reka Sinata, Frans Wikanargo, Matheus Alvian