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All Journal snimed Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Semantik JSI: Jurnal Sistem Informasi (E-Journal) Jurnal Kreativitas PKM JuSiTik : Jurnal Sistem dan Teknologi Informasi Komunikasi Zonasi: Jurnal Sistem Informasi Jurnal Informatika dan Rekayasa Perangkat Lunak Prosiding Seminar Nasional Multidisiplin Ilmu Jurnal Sistem Informasi dan Sains Teknologi MEANS (Media Informasi Analisa dan Sistem) Jurnal Pengkajian Dhamma Algor PROFICIO: Jurnal Pengabdian Masyarakat CITIZEN: Jurnal Ilmiah Mulitidisiplin Indonesia JURNAL PENDIDIKAN INDONESIA: Teori, Penelitian, dan Inovasi INTECH (Informatika dan Teknologi) Abdi-Dharma Jurnal Abdimas Musi Charitas Jurnal Sistem Informasi JSITP JSITIK: Jurnal Sistem Informasi dan Teknologi Informasi Komputer Jurnal Ilmiah Sistem Informasi MDP Student Conference Journal Of Informatics And Busisnes Jurnal Ilmiah Computer Science Masterpiece: Journal of Islamic Studies and Social Sciences Journal of Technology and System Information Jurnal Riset Teknik Komputer Jurnal Sains Sistem Informasi Inovasi Gagasan Abdimas & Kuliah Kerja Nyata Jurnal Dunia Peternakan Jurnal Riset Sistem Informasi Jurnal Sistem Informasi, Manajemen dan Teknologi Informasi Jurnal Sains dan Teknologi Jurnal Ilmu Komputer dan Informatika Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK) Jurnal Riset Multidisiplin Edukasi INTECH (Informatika dan Teknologi) Sinergi : Jurnal Ilmiah Multidisiplin Ar-Rasyid: Jurnal Publikasi Penelitian Ilmiah
Andri Wijaya
Sistem Informasi, Sekolah Tinggi Teknik Musi, Palembang 30133
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Journal : Journal Of Informatics And Busisnes

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Perancangan Data Warehouse Untuk Mendukung Keputusan Strategi Pemasaran Dalam Penjualan Br Hombing, Nova Magdalena; Simanjuntak, Welmi; Wijaya, Andri
Journal Of Informatics And Busisnes Vol. 3 No. 3 (2025): Oktober - Desember
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jibs.v3i3.3855

Abstract

Operational sales data is often fragmented, impeding management from developing data driven marketing strategies. This research aims to conceptually design a data warehouse to support sales marketing strategy decision making. The method utilizes a descriptive-conceptual approach employing the Kimball’s Nine-Step methodology on the Superstore Sales Data (2025) dataset from Kaggle. The resulting design is a Star Schema, which integrates historical data (customer, product, region, and time). Via the ETL (Extract, Transform, Load). The derived multidimensional analysis yields critical insights: Furniture products are the primary profit drivers, the Home Office segment demonstrates superior profitability, and the Q4 seasonal pattern (October-December) is the consistent sales speak. This data warehouse model proves effective in providing structured, actionable insights for marketing profit optimization.
Penerapan Data Mining Untuk Klasterisasi Buku Di Perpustakaan Menggunakan Algoritma K-Means Zalukhu, Indri Feni Asih; Silaban, Bintang Jelita Nasrani; Wijaya, Andri
Journal Of Informatics And Busisnes Vol. 3 No. 3 (2025): Oktober - Desember
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jibs.v3i3.3904

Abstract

Libraries expand their book collections every year, making managing and organizing shelves increasingly challenging. This makes finding and grouping relevant books quite time – consuming, especially when the data is already quite large. Therfore, this study attemps to utilize data mining methods, specifically the K-Means algorithm, to help group books based on certain similarities, such as category and borrowing. Before the grouping process is carried out, the book data first goes through preprocessing and normalization stages to make data look neat and ready to be processed. Furthermore, the K-Means algorithm is used to generate several groups of books with similar characteristics. From the data processing results, K-Means has been proven to be able to form several fairly clear clusters, this sifnificantly assisting libraries in organizing books, providing reading recommendations, and improving the quality of service for students and lecturers. Overall, the implementations of the K-Means algorithm in this library can accelerate collection management work and support a more data – driven decision – making process.
Implementasi Metode Kimball dan Pendekatan Star Schema dalam Membangun Data Warehouse Analisis E-Commerce Oktarina, Theresia; Sanjaya, Aloisius Egi; Wijaya, Andri
Journal Of Informatics And Busisnes Vol. 3 No. 4 (2026): Januari - Maret
Publisher : CV. ITTC INDONESIA

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Abstract

Perkembangan platform e-commerce mendorong peningkatan volume data transaksi yang sangat besar dan kompleks. Namun, data tersebut umumnya masih tersimpan dalam sistem operasional yang belum optimal untuk kebutuhan analisis jangka panjang dan pengambilan keputusan strategis. Penelitian ini bertujuan untuk merancang dan mengimplementasikan data warehouse pada platform e-commerce VWX, khususnya pada kategori Pet Supplies, guna mendukung analisis bisnis secara multidimensi. Metode yang digunakan adalah pendekatan Kimball dengan model star schema, yang terdiri dari satu tabel fakta dan dua tabel dimensi. Data diperoleh dari hasil web scraping dan diproses melalui tahapan ETL (Extract, Transform, Load) menggunakan RapidMiner untuk memastikan kualitas, konsistensi, dan kesiapan data. Selanjutnya, data dianalisis menggunakan teknik OLAP seperti roll-up, drill-down, slice, dan dice untuk menggali informasi terkait performa produk, kategori, dan kualitas rating pelanggan. Hasil penelitian menunjukkan bahwa penerapan data warehouse dengan model star schema mampu menyajikan data secara terstruktur dan mempermudah proses analisis, sehingga menghasilkan informasi yang relevan dan dapat dimanfaatkan sebagai dasar pengambilan keputusan yang lebih efektif pada platform e-commerce VWX.
Implementasi Data Warehouse Skema Snowflake untuk Analisis Determinan Kompetensi Siswa Samuel Dimas Sutikno; Michael Imanuel; Andri Wijaya
Journal Of Informatics And Busisnes Vol. 3 No. 4 (2026): Januari - Maret
Publisher : CV. ITTC INDONESIA

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Abstract

The implementation of the National Assessment (AN) produces complex educational data volumes, covering the results of the Minimum Competency Assessment (AKM), Character Surveys, and Learning Environment Surveys. The management of transactional and scattered data often hinders the comprehensive education quality evaluation process. This study aims to design and implement a Data Warehouse using the Snowflake Schema method to analyze the influence of socio-economic status and school profiles on student literacy and numeracy achievements. Kimball's Nine-Step Methodology approach is used in data architecture design. Test results show that the Snowflake scheme is effective in handling regional and school dimension hierarchies by reducing storage redundancy. OLAP (Online Analytical Processing) analysis reveals significant gaps in literacy and numeracy scores based on school accreditation levels and student economic backgrounds, where school quality is proven to be a moderating variable in improving student achievements from low economic groups.
Implementasi Data Mining Dalam Mengkategorikan Produk Terlaris dan Kurang Laris Pada Toko Retail OPQ Menggunakan Metode Naive Bayes Oktarina, Theresia; Ketut Agus Wiikananda; Wijaya, Andri
Journal Of Informatics And Busisnes Vol. 3 No. 4 (2026): Januari - Maret
Publisher : CV. ITTC INDONESIA

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Abstract

Pesatnya volume data transaksi menuntut efisiensi dalam pengelolaan stok dan rencana pemasaran di industri ritel. Riset ini mengevaluasi penggunaan algoritma Naive Bayes untuk memisahkan produk di Toko OPQ menjadi kategori "Unggulan" dan "Reguler". Dengan bantuan RapidMiner Studio, dataset diproses melalui fase pembersihan, standarisasi Z-score, serta pengujian dengan rasio data 70:30. Temuan eksperimen menunjukkan akurasi model mencapai 99%. Meski demikian, ditemukan kendala pada nilai presisi kelas "Unggulan" yang hanya sebesar 16,67% akibat adanya ketimpangan distribusi jumlah sampel. Studi ini menyimpulkan bahwa metode ini efektif untuk memetakan tren, namun memerlukan optimasi pada keseimbangan dataset
Analisis Sentimen Berita terhadap Harga Saham BBCA Menggunakan Naive Bayes Michael Imanuel; Samuel Dimas Sutikno; Andri Wijaya
Journal Of Informatics And Busisnes Vol. 3 No. 4 (2026): Januari - Maret
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The dynamics of the Indonesian capital market are increasingly influenced by information flow in the digital era. PT Bank Central Asia Tbk (BBCA), as a key market proxy, experienced price volatility in 2024–2025 despite solid fundamentals, indicating the influence of market psychology. This study aims to analyze the effect of stock market news sentiment on BBCA stock prices and test the effectiveness of the Multinomial Naive Bayes algorithm. Using a text mining approach, 5,000 economic news articles (2020–2025) were processed using TF-IDF and classified into positive, negative, and neutral sentiments. The results show the model achieved 92.4% accuracy with 89% precision for negative sentiment detection. Pearson correlation analysis revealed a strong positive relationship (r = 0.78) between daily sentiment scores and the following day's closing prices. The study concludes that news sentiment is a valid leading indicator for stock movements. The Naive Bayes algorithm proved efficient for financial text analysis, offering a viable tool for investor risk mitigation.
Co-Authors Adi Sucipto, Adi Aditiya Hermawan Aditya, Putra Adtiya, Setenilaus Afifah Azzahra Agustin, Evelyn Agustio Dwitama Aguswan, Michael Junius Alessandro, Andreas Alexander Chandra Alexius Hendra Gunawan Amat Basri Andreas Alessandro Andreas Alessandro Fernando Putra Andri Wijaya Andronikus G Anggoro, Deo Ardi Riyadi Ardika, Petra Putri Arif Aliyanto Arif Aliyanto Arif Aliyanto Arron Mosses Jhon Hadi Arvin Lawistra Asek, Ambo Ayu Elisya Natama Sianturi Azahra, Khalida Zia Fitrah Azzahra, Afifah Azzahra, Violina Baiturrahman, Ridwan Benny Daniawan Bima Aprianto S Br Hombing, Nova Magdalena Branchris Buchori Asyik Chintia Cantika cia, crecia Crecia Crecia Crecia, Crecia Daely, Septia Angelika Gettin Damayanti, Lily Daniawan, Benny Deo anggoro Desty Ervira Puspaningtyas Dwitama, Agustio Effendy, Ellena Endri Yuliati Enjeli, Margareta Erwin Erwin Filikano, Thomas Gunawan, Andronikus Halim, Ardie Hambali, M Syahbani Hans Rafael Gabriel Turnip IFAH KHADIJAH, IFAH Iskandar Mirza Iskandar Syah Jacqueline Henny P Jessen Laorenza Suwandi Johan Abisay Tambunan Julian Masidin, Nevin JUNAEDI Juni Lapita Hasugian Ketut Agus Wiikananda Kevin Alexander Yech Kevin kevin Kurniawan Maranto, Ardiane Rossi Kusneti, Leni Latius Hermawan Leni Kusneti Lily Damayanti Lusia Komala Widiastuti Maharani, Wianti Marcello, Daniel Maria Bellaniar Ismiati Masidin, Nevin Julian Mayer Dani Sitompul Meilinda Meilinda Meilinda Michael Imanuel Michael Junius Aguswan Muhamad Raka Nur Habibi Muhammad Basri Muhammad Firdaus Muhammad Raka Nur Habibi Mujiyanto Mujiyanto Mutia Maharani Nababan, Clara Nova Magdalena Br Hombing Novaldi, Alexander Nurhadi, M Wiran Jaya Oktarina, Theresia Pamungkas, Martinus Ponco Pratama, Paskalis Arindra Puspita Mardika Sari Putra, Steven Adi Raditya Rimbawan Raditya Rimbawan O Ratu, Anggitta Rika Solihah, Rika Riski Surya Saputra Rosana Rosana Samuel Dimas Sutikno Sanjaya, Aloisius Egi Seli Septi Putri Septi Putri Azzahra Septia Angelika Gettin daely Setiawan, Ferdy Shevchenko, Angelus Galang Silaban, Bintang Jelita Nasrani Simanjuntak, Welmi Simbolon, Defrianti Sri Andayani Sri Andayani Stefanus Charles Selvianto Stenilaus A Styaningrum, Silvia Dewi Sugiarti, Sabar Sumual, Imanuel Marcell Supriadi, Jonathan Suwitno Suwitno, Suwitno Thomas Filikano Turnip, Hans Rafael Gabriel Verri Kuswanto Welmi Simanjuntak Wikananda, Ketut Agus Wiyono Yakub, Handoyo Yo Ceng Giap Yoel, Yoel Marcelino Pribadi Yohanes Agung Apriyanto Yusuf Kurnia Zalukhu, Indri Feni Asih