Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal Jurnal SOLMA Infotech: Journal of Technology Information
Gozali, Carisha Puspa
Unknown Affiliation
Computer Science & IT Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Implementasi Aplikasi Web Corporate profile dan Sistem Pre-order untuk UMKM Wiji Lauro, Manatap Dolok; Gozali, Carisha Puspa; Puteri, Carissa
Jurnal SOLMA Vol. 14 No. 2 (2025)
Publisher : Universitas Muhammadiyah Prof. DR. Hamka (UHAMKA Press)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/solma.v14i2.18834

Abstract

Background: UMKM memegang peranan krusial dalam perekonomian Indonesia dengan berkontribusi signifikan terhadap PDB dan penyerapan tenaga kerja. Namun, banyak UMKM masih menghadapi tantangan dalam adaptasi teknologi. UMKM Wiji, sebuah usaha mikro di bidang makanan dan minuman, saat ini mengandalkan media sosial dan proses pre-order manual melalui WhatsApp. Ketiadaan website corporate profile dan sistem pre-order terintegrasi membatasi jangkauan pasar dan efisiensi operasional. Metode: Proyek pengembangan aplikasi website untuk UMKM Wiji menggunakan metodologi Agile Scrum. Tahap Requirement gathering dilakukan menggunakan pendekatan Design Thinking. Pendekatan ini berpusat pada pemahaman kebutuhan pengguna dan bisnis untuk menghasilkan solusi yang relevan dan inovatif. Implementasi proyek dilaksanakan selama Maret hingga April 2025. Hasil: Proyek ini menghasilkan aplikasi website corporate profile dan sistem pre-order yang dapat diakses di https://rumahwiji.com. Website ini mencakup berbagai halaman dan fitur sesuai dengan hasil tahapan Design Thinking, seperti informasi produk, promo, tautan media sosial, serta fitur pre-order. Keseluruhan kebutuhan yang teridentifikasi pada tahap Requirement berhasil diimplementasikan. Kesimpulan: Implementasi aplikasi website corporate profile dengan sistem pre-order untuk UMKM Wiji telah berhasil dilaksanakan sesuai dengan kebutuhan yang didefinisikan. Website ini berfungsi untuk meningkatkan visibilitas UMKM serta memfasilitasi dan mengefisienkan proses pre-order bagi calon pembeli.
ANALISIS HUBUNGAN MATA KULIAH KOMPUTASI DASAR DENGAN IPK MAHASISWA TEKNIK INFORMATIKA MENGGUNAKAN SUPPORT VECTOR REGRESSION Perdana, Novario Jaya; Ferdinand, Kelvin; Gozali, Carisha Puspa; Herwindiati, Dyah Erny
Infotech: Journal of Technology Information Vol 11, No 1 (2025): JUNI
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i1.383

Abstract

Student academic performance serves as a key indicator in higher education assessment. For students in Informatics Engineering, foundational computing skills are critical to their academic progression, and these are primarily acquired through first-semester courses. This study proposes a predictive model for Cumulative Grade Point Average (GPA) using the Support Vector Regression (SVR) method with a Radial Basis Function (RBF) kernel. The courses "Introduction to Algorithms," "Computation I," "Computation II," and "Data Structures" were selected as independent variables, as they provide essential computing foundations for subsequent coursework. The dataset comprised 270 records, each containing grades from the aforementioned courses and the corresponding GPA achieved by students in their fourth semester. To ensure data quality, outlier detection was performed using the Z-score method, resulting in a refined dataset of 200 entries. This dataset was then split into 75% for training and 25% for testing. A grid search optimization identified the best hyperparameter combination: C = 100, γ = 0.05, and ε = 0.05. Model evaluation yielded promising results, with a Mean Absolute Error (MAE) of 0.0742, a Mean Absolute Percentage Error (MAPE) of 2.19%, a Mean Squared Error (MSE) of 0.012, and an R² score of 0.8695—indicating strong predictive accuracy. Furthermore, the F-test produced a value of 74.9440, which exceeds the critical F-value of 2.5787, confirming the statistical significance of the independent variables in predicting GPA. This model has the potential to support academic monitoring and enhancement efforts by delivering actionable predictions and insights for the Informatics Engineering program.
Co-Authors Dyah Erny Herwindiati Ferdinand, Kelvin Manatap Dolok Lauro, Manatap Dolok Novario Jaya Perdana Puteri, Carissa