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All Journal Jurnal Informatika Upgris Jurnal Nasional Komputasi dan Teknologi Informasi JSAI (Journal Scientific and Applied Informatics) Jurnal Manajemen Informatika dan Sistem Informasi Jurnal Sistem Komputer dan Informatika (JSON) Dikmas: Jurnal Pendidikan Masyarakat dan Pengabdian Jurnal Ilmu Komputer dan Sistem Informasi Journal Of Software Engineering And Communication
Nur Oktavin Idris
Universitas Negeri Gorontalo
Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Library & Information Science Neuroscience Transportation

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Journal : jsai journal scientific and applied informatics

 1 
Sistem Informasi Penjualan dan Promosi Kayu Bangunan dan Rumah Berbasis Web Fitriyanti Suleman; Nur Oktavin Idris; Siti Andini Utiarahman
JSAI (Journal Scientific and Applied Informatics) Vol. 4 No. 3 (2021): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v4i3.2438

Abstract

Kayu merupakan bahan utama yang digunakan untuk kebutuhan tiang penyangga, pembuatan tiang atap, kusen, daun pintu, daun jendela dan lainnya. Salah satu usaha industri kecil yang bergerak di bidang penjualan kayu yaitu Wana Lestari Dua. Pemasaran yang dilakukan oleh Wana Lestari Dua masih secara tatap muka atau hanya dilakukan di tempat usaha dengan lingkup pembeli yang meliputi wilayah kecamatan Kwandang, dan belum menggunakan promosi secara online. Sehingga belum ada akses secara meluas ke pelanggan lain di luar wilayah tersebut. Oleh karena itu diperlukan sistem penjualan dan promosi yang dapat dijangkau pelanggan lainnya. Untuk itu penelitian ini bertujuan merancang sistem informasi penjualan dan promosi kayu bangunan dan rumah berbasis web. Penelitian ini menggunakan metode waterfall, dan bahasa pemrograman menggunakan PHP dan MySQL sebagai basis data. Data yang ada diperoleh dengan melakukan observasi, wawancara dan mengumpulkan referensi sebagai pendukung. Hasil dari penelitian dengan sistem yang dirancang dapat memudahkan pelanggan untuk melakukan pemesanan kayu serta memudahkan perusahaan industri kayu dalam melakukan promosi.
Housing Credit Payment Information System Using the Sliding Rate Method Farid; Nur Oktavin Idris; A. Mulawati Mas Pratama
JSAI (Journal Scientific and Applied Informatics) Vol 6 No 2 (2023): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v6i2.5407

Abstract

Housing is a basic need that is essential for human life. Some members of the community rely on home ownership credit facilities (KPR) to achieve homeownership. Therefore, Bank Paro Dana offers KPR to support the increasing housing needs of the community. However, it is important for customers to understand the calculation mechanism and payment system of KPR that are safe and suitable for their needs, as well as to understand the varying interest rates in KPR and be cautious in facing market interest rate uncertainties. The problems encountered so far are the high-interest rates and installments that must be paid. Therefore, an effective and efficient method is needed in managing KPR installment payments, supported by the development of an information system that can automatically and transparently manage monthly installment calculations and assist customers in making payments. Hence, this research aims to implement the sliding rate method in the housing credit payment information system. The testing results using the white box technique obtained V(G) = 2 and Cyclomatic Complexity (CC) = 2, indicating that the proposed system can be concluded as effective and efficient. With the existence of this system, it is expected that the quality of service to customers can be improved through a better information system and provide a positive contribution to the development of the KPR payment system, thus providing maximum benefits for all parties involved
Analisis Regresi Linear dan Ensemble Learning Berbasis Kontribusi Fitur dalam Prediksi Harga Mobil Listrik Nur Oktavin Idris; Fuad Pontoiyo
JSAI (Journal Scientific and Applied Informatics) Vol 9 No 1 (2026): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v9i1.9891

Abstract

This study aims to analyze the performance of linear regression and ensemble learning methods in predicting electric vehicle prices based on technical specifications, as well as to examine the contribution of key features to the prediction results. The main challenge in electric vehicle price prediction lies in the high price variability driven by nonlinear relationships among technical attributes, which are difficult to capture using simple linear models. Linear regression was employed as a baseline model, while Random Forest and Gradient Boosting were used as ensemble learning approaches. The dataset was obtained from Kaggle and processed through data cleaning, categorical encoding, normalization, and an 80:20 train–test split. Model performance was evaluated using mean squared error (MSE) and the coefficient of determination (R²). The results indicate that the Gradient Boosting model achieved the best performance, with an MSE of 8.63 and an R² of 0.891, outperforming both Random Forest and linear regression models. Feature contribution analysis reveals that vehicle acceleration time is the most influential factor in determining electric vehicle prices. These findings demonstrate that ensemble learning not only improves predictive accuracy but also provides analytical insights into the key technical factors shaping electric vehicle pricing.
Co-Authors Adam, Novita Andi Mulawati Mas Pratama Badaruddin, Muliati Farid Farid Farid Farid, F. Fuad Pontoiyo Maryati Kadir Thalib Nurjana Suleman Rapika Anwar Satriadi D. Ali Sri Oktavia Dai Suleman, Fitriyanti Suleman, Nurjana Utiarahman, Siti Andini Wiwik Handayani Zufrianto K Dunggio