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All Journal snimed Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Proceedings of KNASTIK Semantik Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik JSI: Jurnal Sistem Informasi (E-Journal) Jurnal SOLMA Jurnal Ilmiah Matrik JuSiTik : Jurnal Sistem dan Teknologi Informasi Komunikasi Progresif: Jurnal Ilmiah Komputer Zonasi: Jurnal Sistem Informasi Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Sistem Informasi dan Sains Teknologi MEANS (Media Informasi Analisa dan Sistem) Jurnal Teknimedia: Teknologi Informasi dan Multimedia CITIZEN: Jurnal Ilmiah Mulitidisiplin Indonesia Jurnal Abdimas Musi Charitas Jurnal Sistem Informasi JSITP JSITIK: Jurnal Sistem Informasi dan Teknologi Informasi Komputer Jurnal Ilmiah Sistem Informasi MDP Student Conference Jurnal Sistem Informasi Journal Of Informatics And Busisnes Jurnal TEFSIN ( Jurnal Teknik Informatika dan Sistem Informasi) Scientica: Jurnal Ilmiah Sains dan Teknologi 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 Jurnal Riset Sistem Informasi Jurnal Sistem Informasi, Manajemen dan Teknologi Informasi Jurnal Sains dan Teknologi Jurnal Ilmu Komputer dan Informatika Jurnal Riset Multidisiplin Edukasi Sinergi : Jurnal Ilmiah Multidisiplin INTECH - Informatika Dan Teknologi
Andri Wijaya
Universitas Katolik Musi Charitas
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Perancangan Data Warehouse Untuk Analisis Peminjaman Dan Pengembalian Buku Di Perpustakaan Silaban, Bintang Jelita Nasrani; Zalukhu, Indri Feni Asih; 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.v3i3.3837

Abstract

The current library environment is experiencing rapid data collection, particulary from the daily activity of borrowing and returning books. This vast amount of data could potentially be utilized for analysis, but in practice, library information systems are often used solely for operational purposes. Consequently, opportunities to extract valuable insights from this data are limited. Given the situation, this study attempts to design and implement a data warehouse focused on analyzing book borrowing and returning patterns, utilizing PostgreSQL as the primary platform. The research process involved several stages, starting with data collection, needs analysis, data warehouse model design using the star schema, and implementation into PostgreSQL. Afterward, an ETL (Extraction, Transformation, and Loading) process was performed to able to combine library transaction data into a more structured and ready for analysis. From this data, the system was able to generate various insights, such as patterns of books that were borrowed most, medim, and least.
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jibs.v3i4.3948

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 Mining Dalam Mengkategorikan Produk Terlaris dan Kurang Laris Pada Toko Retail OPQ Menggunakan Metode Naive Bayes Oktarina, Theresia; Wiikananda, Ketut Agus; Wijaya, Andri
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 | DOI: 10.47233/jibs.v3i4.3964

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
The Role Of Law In Providing Decent Work For Citizens To Support The National Long-Term Development Plan 2025-2045 Wijaya, Andri
Citizen : Jurnal Ilmiah Multidisiplin Indonesia Vol. 5 No. 5 (2025): CITIZEN: Jurnal Ilmiah Multidisiplin Indonesia
Publisher : DAS Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53866/jimi.v5i5.1015

Abstract

This study discusses the role of law in fulfilling decent work for citizens to support the National Long-Term Development Plan (RPJPN) 2025-2045. The government always strives to provide and create decent jobs for its citizens, but unfortunately, the number of jobs is insufficient to meet the large number of prospective Indonesian workers. One reality on the ground is the widespread layoffs by companies for various reasons. As a developing country, layoffs have had various negative impacts on ongoing development. The high unemployment resulting from layoffs certainly has a systemic impact on the economy and development in Indonesia. The RPJPN 2025–2045 serves as the legal basis and primary guideline for all development actors—both government and non-government—in realizing Indonesia's grand vision by 2045, known as the "Vision of Golden Indonesia 2045." In the Vision of Golden Indonesia 2045, the phrase "sustainable" is written, which means that Indonesia has a dream of implementing continuous development without stopping with the support of various sectors. The labor sector plays an important role in realizing this sustainable development, but this sustainable development will experience obstacles if there is a lot of unemployment due to layoffs. This study employs a normative legal research method. The results of the study indicate that The Golden Indonesia 2045 Vision and the 2025–2045 RPJPN directly address the issue of layoffs through inclusive and sustainable economic development, improving human resource quality, digital and industrial transformation, and adaptive employment policies.
Klasifikasi resiko Diabetes Mengunakan Algoritma Decision Tree Stefanus Charles Selvianto, Stefanus Charles Selvianto; Novaldi, Alexander; Wijaya, Andri
Jurnal Sistem Informasi dan Teknologi Peradaban Vol. 6 No. 2 (2025): jurnal Sistem Informasi dan Teknologi Peradaban
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Peradaban

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58436/jsitp.v6i2.2485

Abstract

Abstrak Peningkatan kasus Diabetes Mellitus menuntut adanya metode deteksi dini yang efektif untuk mencegah komplikasi serius pada penderita. Penelitian ini bertujuan mengklasifikasikan risiko diabetes menggunakan algoritma Decision Tree yang mampu menghasilkan aturan keputusan yang mudah diinterpretasikan oleh tenaga medis. Penelitian memanfaatkan dataset Pima Indians Diabetes dari repositori UCI Machine Learning yang diolah menggunakan perangkat lunak RapidMiner. Melalui tahapan preprocessing dan pembagian data latih serta uji dengan rasio 80:20, model dievaluasi menggunakan Confusion Matrix dan kurva ROC. Hasil pengujian menunjukkan model mencapai akurasi 70.13%, presisi 70.00%, recall 25.93%, dan nilai AUC sebesar 0.736 (fair performance). Meskipun nilai recall rendah mengindikasikan keterbatasan sensitivitas, tingginya nilai presisi menunjukkan model sangat andal dalam meminimalkan kesalahan diagnosis positif palsu. Secara spesifik, model menemukan aturan klinis bahwa kadar glukosa di atas 127.5 mg/dL merupakan indikator risiko tinggi, diikuti oleh Body Mass Index (BMI) dan usia sebagai faktor determinan sekunder pada pasien dengan gula darah normal. Penelitian ini menyimpulkan bahwa metode Decision Tree efektif digunakan sebagai sistem pendukung keputusan medis berbasis aturan (rule-based decision support) untuk identifikasi profil risiko pasien.
Deteksi Risiko Scam Airdrop Kripto Pada Platform Telegram Menggunakan Metode Lexicon-Based Filikano, Thomas; Wijaya, Andri
JSI: Jurnal Sistem Informasi (E-Journal) Vol 17 No 2 (2025): JSI: Jurnal Sistem Informasi (E-Journal)
Publisher : Jurusan Sistem Informasi Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/jsi.v17i2.268

Abstract

Perkembangan pesat teknologi blockchain dan kripto telah menghadirkan berbagai inovasi, salah satunya airdrop kripto sebagai strategi pemasaran untuk menarik pengguna. Telegram menjadi platform utama penyelenggaraan airdrop melalui Telegram Mini Apps, namun juga rentan terhadap praktik scam yang merugikan pengguna. Penelitian ini mengimplementasikan metode lexicon-based untuk mendeteksi risiko scam airdrop kripto di Telegram. Data dikumpulkan dari grup Telegram Mini Apps menggunakan pustaka Telethon, lalu dianalisis dengan pendekatan lexicon-based yang menggabungkan VADER dan custom lexicon istilah scam. Analisis dilakukan terhadap unigram dan bigram guna menangkap konteks kata yang relevan. Hasil menunjukkan mayoritas pesan netral (252.164), diikuti positif (101.455) dan negatif (66.791). Frasa seperti “list date” dan “scam project” menjadi indikator risiko utama. Metode ini efektif mendeteksi risiko scam meski kebanyakan pesan bersifat informatif. Penelitian ini diharapkan dapat meningkatkan kewaspadaan pengguna dan berkontribusi pada ekosistem blockchain yang lebih aman. Untuk penelitian selanjutnya, disarankan pengembangan dashboard real-time dengan pembaruan lexicon berkala mengikuti dinamika komunitas kripto dan integrasi dengan machine learning.
Edukasi Pencegahan Stunting melalui Teknologi Artificial Intelligence (AI) Pada PKK Sukarami Theresia Anita; Andri Wijaya; Agnes Felicia Lubis; Jonathan Supriadi; Stefanus Agung Sagita
Jurnal SOLMA Vol. 15 No. 1 (2026)
Publisher : Universitas Muhammadiyah Prof. DR. Hamka (UHAMKA Press)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/solma.v15i1.21807

Abstract

Background: Stunting masih menjadi masalah kesehatan masyarakat yang berdampak serius pada tumbuh kembang anak dan kualitas sumber daya manusia di masa depan. Kecamatan Sukarami menghadapi tantangan dalam meningkatkan kesadaran masyarakat terkait pencegahan stunting, khususnya melalui peran kader PKK. Studi ini bertujuan untuk meningkatkan pengetahuan, keterampilan, dan peran kader PKK dalam upaya pencegahan stunting dengan memanfaatkan teknologi Kecerdasan Buatan (AI). Metode: pemberian pretest, pemaparan materi, pemeriksaan kesehatan balita, dan pendampingan penggunaan aplikasi AI Prediksi Stunting. Hasil: Rata-rata skor pre-test 55% meningkat menjadi 85% pada post-test), tersedianya media edukasi berupa flipchart Isi Piringku, dan keterampilan kader dalam mengoperasikan aplikasi AI untuk mendeteksi risiko stunting. Kesimpulan: Penerapan teknologi AI telah terbukti memperkuat peran PKK dalam edukasi gizi, deteksi dini, dan pencegahan stunting. Ke depannya, program ini berpotensi untuk memperluas cakupan dan mengembangkan aplikasinya agar lebih terintegrasi dengan layanan kesehatan daerah.
Forecasting Model using Single Exponential Smoothing Method on PT. Rakha Medika Christy, Hanna; Wijaya, Andri
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 8 No. 1 (2026): Maret
Publisher : Universitas Wahid Hasyim

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

Abstract

PT. Rakha Medika is a healthcare company with a network of clinics spread across various branches in the city of Palembang. In stock management, the company faces significant challenges related to both overstocking and stock shortages, which impact operational efficiency. These issues arise because inventory orders are made without proper planning. This study aims to optimize stock management by applying the Single Exponential Smoothing forecasting method to analyze usage patterns. The data used includes inventory records spanning a one-year period (April 2023 to April 2024), comprising a total of 4,033 entries. The forecasting results indicate that an alpha value of 0.99 is the most optimal, achieving a forecasting accuracy of MAPE at 14%, MAD at 4, and MSE at 97. These results suggest that the forecasting method performs reasonably well, as the MAPE score does not exceed 20%. However, a comparison between the forecasting results and the actual values reveals a deviation of 38.24% from the total inventory. This deviation is influenced by the characteristics of the data and unavoidable external factors.
Co-Authors Aditya, Putra Adtiya, Setenilaus Afifah Azzahra Agnes Felicia Lubis Agustin, Evelyn Agustio Dwitama Aguswan, Michael Junius Alessandro, Andreas Alfonso Sitompul Andreas Alessandro Andreas Alessandro Fernando Putra Andronikus G Anggoro, Deo Ardi Riyadi Ardika, Petra Putri Arif Aliyanto Arif Aliyanto Arif Aliyanto Arif Aliyanto Arif Aliyanto Arron Mosses Jhon Hadi Ayu Elisya Natama Sianturi Azzahra, Afifah Azzahra, Violina Bima Aprianto S Br Hombing, Nova Magdalena Branchris Buchori Asyik Chintia Cantika Christy, Hanna Crecia Crecia Crecia Crecia Crecia, Crecia Daely, Septia Angelika Gettin Damayanti, Lily Daniawan, Benny Deo anggoro Dwitama, Agustio Effendy, Ellena Enjeli, Margareta Erwin Erwin Erwin erwin Filikano, Thomas Gunawan, Andronikus Hans Rafael Gabriel Turnip Imanuel, Michael Iskandar Syah Jacqueline Henny P Johan Abisay Tambunan Jonathan Supriadi Julian Masidin, Nevin Juni Lapita Hasugian Kevin Alexander Yech Kevin kevin Kusneti, Leni Latius Hermawan Leni Kusneti Maharani, Wianti Marcello, Daniel Maria Bellaniar Ismiati Martinus Ponco Pamungkas Masidin, Nevin Julian Mayer Dani Sitompul Meilinda Meilinda Meilinda Michael Junius Aguswan Michael Junius Aguswan Muhamad Raka Nur Habibi Muhammad Basri Muhammad Raka Nur Habibi Mutia Maharani Nababan, Clara Nova Magdalena Br Hombing Novaldi, Alexander Oktarina, Theresia P. Arindra Pratama Pamungkas, Martinus Ponco Pratama, Paskalis Arindra Putra, Steven Adi Ratu, Anggitta Riski Surya Saputra Rosana Rosana Sanjaya, Aloisius Egi Seli Septi Putri Septi Putri Azzahra Septia Angelika Gettin daely, Septia Angelika Gettin daely Setenilaus Aditya Setiawan, Ferdy Shevchenko, Angelus Galang Silaban, Bintang Jelita Nasrani Simanjuntak, Welmi Simbolon, Defrianti Simbolon, Defrianti Sri Andayani Sri Andayani Stefanus Agung Sagita Stefanus Charles Selvianto, Stefanus Charles Selvianto Stenilaus A Sugiarti, Sabar Sumual, Imanuel Marcell Supriadi, Jonathan Sutikno, Samuel Dimas Theresia Anita Thomas Filikano Thomas Filikano Turnip, Hans Rafael Gabriel VF Anindya W Wayan Pondra Lesmana Welmi Simanjuntak Wiikananda, Ketut Agus Wikananda, Ketut Agus Yakub, Handoyo Yohanes Agung Apriyanto Zalukhu, Indri Feni Asih