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All Journal Elkom: Jurnal Elektronika dan Komputer Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Indonesian Journal on Software Engineering (IJSE) Bina Insani ICT Journal Jurnal Pilar Nusa Mandiri Jusikom : Jurnal Sistem Komputer Musirawas Jurnal Teknologi Informasi MURA Jurnal Teknologi Informasi dan Multimedia INFOKUM Jurnal Sistem Informasi Jurnal AbdiMas Nusa Mandiri JUSTIAN - Jurnal Sistem Informasi Akuntansi Ilmu Komputer untuk Masyarakat Jurnal Insan Journal of Accounting Information System Jurnal Teknologi Informasi Mura Journal of Computer Science Contributions (Jucosco) MUARA EKONOMI : Jurnal Ilmiah Ilmu Ekonomi, Manajemen & Bisnis Bianglala Informatika
Eni Pudjiarti
Universitas Bina Sarana Informatika
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Mathematics Physics Social Sciences Other

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Pemodelan dan Prediksi Harga Emas Menggunakan Metode ARIMA pada Data Time Series Yesni Malau; Eni Pudjiarti; Fintri Indriyani; Riswandi Ishak; Asep Sayfulloh; Wahyutama Fitri Hidayat
Bianglala Informatika Vol. 14 No. 1 (2026): Maret 2026
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/bianglala.v14i1.12455

Abstract

This study aims to analyze and predict gold price movements using a time series approach with the Autoregressive Integrated Moving Average (ARIMA) model. The data used in this research are historical daily gold closing prices from 2020 to 2026 obtained from Investing.com, consisting of 1,568 data. The research stages include data collection, preprocessing, stationarity testing using the Augmented Dickey-Fuller (ADF) test, parameter identification through Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) analysis, parameter estimation, diagnostic checking, and model accuracy evaluation. The results indicate that the data are stationary with a p-value < 0.05. Based on the identification and model selection process, the ARIMA (3,0,3) model was identified as the best model with an Akaike Information Criterion (AIC) value of 15449.326. Model evaluation results show an RMSE of 120.86, MAE of 95.02, and MAPE of 5.48%. The MAPE value below 10% indicates that the model has good accuracy in predicting gold prices. Therefore, the ARIMA model can be used as an effective approach to predict gold price movements based on historical data.
Analisa Sentimen Ulasan Skintific Peptide Brightening Lip Serum Di Tokopedia Menggunakan Algoritma Support Vector Machine (SVM) Sri Hardani; Leliyanah Leliyanah; Eni Pudjiarti; Siti Faizah
MUARA EKONOMI : Jurnal Ilmiah Ilmu Ekonomi, Manajemen & Bisnis Vol. 2 No. 3 (2026): JULI : Jurnal Ilmiah Ilmu Ekonomi, Manajemen & Bisnis
Publisher : CV Muara Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64365/muanomi.v2i3.375

Abstract

Dunia kecantikan mengalami perkembangan yang sangat pesat. Tidak hanya berfokus pada make up, tetapi sudah berkembang pada produk untuk perawatan kulit wajah dan perawatan bibir. Bibir merupakan fitur utama wajah bagian bawah yang sangat mudah dipengaruhi oleh kondisi lingkungan yang dapat menyebabkan bibir kering dan pecah-pecah. Untuk menjaga kesehatan bibir, diperlukan pelembab bibir. Skintific, salah satu merk produk perawatan kulit yang terkenal dengan tagline Repair Your Skin Barrier, baru saja mengeluarkan produk perawatan bibir yang diberi nama Skintific Peptide Nourishing Lip Serum. Sebagai produk baru, tentunya Skintific sebagai pemilik merk, membutuhkan ulasan dari pelanggan guna mengetahui respon pelanggan terhadap produknya. Salah satu metode untuk menganalisa ulasan pelanggan adalah dengan Analisa sentimen. Salah satu algoritma yang sering digunakan dalam Analisa sentimen adalah Support Vector Machine (SVM). Terbukti penerapan Support Vector Machine (SVM) dalam penelitian ini berhasil mendapatkan akurasi sebesar 98%, precision 97%, recall 98%, dan F1 score 97%. Selain itu, terdapat sentimen negatif terhadap Skintific Peptide Nourishing Lip Serum yang dapat menjadi masukan bagi  Skintific untuk memperbaiki layanan dan kualitas produknya.
Rancang Bangun Perangkat Lunak Lelang Vendor Barang dan Jasa Berbasis Website Yesni Malau; Eni Pudjiarti; Ahmad Setiadi; Wahyutama Fitri Hidayat
Jurnal Sistem Informasi Akuntansi Vol 6 No 2 (2025): Periode September 2025
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/justian.v6i2.10727

Abstract

Conventional vendor selection in a project often faces various problems, such as granting exclusive rights to certain vendors, wasting time and costs, and a lack of transparency that can lead to potential corruption. This study aims to develop a website-based vendor selection system using the Codeigniter framework to improve order and transparency in the vendor selection process. The methods used include collecting user requirements data, designing the system using the PHP programming language and the Codeigniter framework, and comprehensive system testing through a Black Box Testing approach. The test results show that all features of the website-based procurement system function as expected with 100% valid results. This software aims to reduce unethical practices and increase user satisfaction and productivity by providing a faster and more transparent procurement process. This study provides a real solution to improve the vendor selection tender process and is expected to be widely implemented to support order and transparency in procurement across various sectors. In addition, this system is also expected to improve data accuracy and accelerate the decision-making process in procurement.
Co-Authors - STMIK Nusa Mandiri, Adelia Alvi Yana Ahmad Setiadi Andi Saryoko Aprillia Ananda Septyawati Asep Sayfulloh Dini Nurlaela Eka Puspita Sari Eka Puspitasari Faizah, Siti Fandi Ahmad Fintri Indriyani Hani Harafani, Hani Hardani, Sri Helma Susanti Herlambang Brawijaya Kresna Ramanda Leliyanah Leliyanah Leliyanah Leliyanah, Leliyanah Muhamad Tabrani Muhammad Hilman Fakhriza Muhammad Tabrani Nunung Hidayatun Riswandi Ishak Rudianto, Biktra Siti Faizah Siti Faizah Siti Faizah Siti Faizah Siti Faizah Siti Faizah Siti Faizah Sri Hardani Verra Sofica Verry Riyanto Wahyutama Fitri Hidayat Wina Sulistyani Yesni Malau