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All Journal Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Jurnal Teknik Informatika (JUTIF) Solidaritas: Jurnal Pengabdian
Pratiwi, Aniec Anafisah
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Religion Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Social Sciences

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Optimasi Website Sampurna Berkah dengan Framework Scrum Menggunakan Metode Agile untuk Meningkatkan Penjualan Pratiwi, Aniec Anafisah; Tanfitra, Adhim; Waluyo, Bibit; Abid, Umar Abdul; Tarwoto
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 2 (2025): APRIL-JUNE 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i2.3309

Abstract

Waste management has become a complex national issue in Indonesia, driven by population growth, economic expansion, and shifting consumption patterns. The Sampurna Berkah website, owned by Sidapurna Village, Dukuhturi District, Tegal Regency, was created to support an environmentally conscious community focused on recycling non-biodegradable waste. To effectively develop the information system for this website, an agile approach is essential. The Scrum framework is employed to enhance transparency, communication, documentation, and adaptability to change. This study aims to optimize the Sampurna Berkah website, which has existing issues such as a confusing user interface, unsuitable color combinations, and lack of responsiveness. Using the Agile Scrum method, stages like Product Backlog, Sprint Planning, Sprint Backlog, Daily Scrum, and Sprint Review were implemented. The optimization results show significant improvements, including a more user-friendly interface, better website responsiveness, and more visually pleasing color combinations, achieving the main development objectives.
Peningkatan Kapasitas Digital Berkelanjutan pada PAC GP Ansor Kroya Riyanto, Andi Dwi; Wahid, Arif Mu’amar; Pratiwi, Aniec Anafisah
Solidaritas: Jurnal Pengabdian Vol. 4 No. 2 (2024): Solidaritas: Jurnal Pengabdian
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat UIN Prof. K.H. Saifuddin Zuhri

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Abstract

Skill digital merupakan kompetensi dasar yang harus dimiliki oleh organisasi di era digital. GPAnsor Cabang Kroya mengalami permasalahan tidak semua organisasi ranting memiliki mediainformasi dan promosi. Pengelolaan media sosial yang dimiliki masih minimalis dan memerlukan pendampingan. Tujuan dari program ini adalah untuk meningkatkan kapasitas digital danmengatasi kesenjangan penggunaan media sosial di tingkat ranting. Program ini melibatkanserangkaian pelatihan praktis yang fokus pada pembuatan konten, interaksi dengan pengguna,dan strategi penggunaan platform digital untuk memaksimalkan jangkauan dan pengaruh sosial. Metodologi pelaksanaan meliputi diskusi awal, pelatihan interaktif, mentoring, monitoring,dan evaluasi. Output kegiataan adalah dnegan menekankan pada peningkatan jumlah akun aktif,kualitas konten, konsistensi publikasi, dan interaksi dengan pengikut. Evaluasi akhir menunjukkan peningkatan signifikan dalam keaktifan dan kualitas pengelolaan media sosial diantara peserta. Saran untuk perbaikan meliputi penerapan pelatihan virtual yang lebih luas dan pengembangan materi pelatihan yang lebih adaptif untuk mendukung keberlanjutan keterlibatan digitaldi masa depan.
Optimasi Website Sampurna Berkah dengan Framework Scrum Menggunakan Metode Agile untuk Meningkatkan Penjualan Pratiwi, Aniec Anafisah; Tanfitra, Adhim; Waluyo, Bibit; Abid, Umar Abdul; Tarwoto
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 2 (2025): APRIL-JUNE 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i2.3309

Abstract

Waste management has become a complex national issue in Indonesia, driven by population growth, economic expansion, and shifting consumption patterns. The Sampurna Berkah website, owned by Sidapurna Village, Dukuhturi District, Tegal Regency, was created to support an environmentally conscious community focused on recycling non-biodegradable waste. To effectively develop the information system for this website, an agile approach is essential. The Scrum framework is employed to enhance transparency, communication, documentation, and adaptability to change. This study aims to optimize the Sampurna Berkah website, which has existing issues such as a confusing user interface, unsuitable color combinations, and lack of responsiveness. Using the Agile Scrum method, stages like Product Backlog, Sprint Planning, Sprint Backlog, Daily Scrum, and Sprint Review were implemented. The optimization results show significant improvements, including a more user-friendly interface, better website responsiveness, and more visually pleasing color combinations, achieving the main development objectives.
Determining The Loan Feasiblity of Bank Customers Using Naïve Bayes, K-Nearest Neighbors And Linear Regression Algorithms Pratiwi, Aniec Anafisah; Saraswati, Wahyuning Tyas; Ardiansyah, Rizky Firman; Rouf, Erik Halma; Pratama, Adhi
Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Vol. 6 No. 3 (2023): Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI)
Publisher : Utility Project Solution

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Abstract

In the financial industry, lending to customers is one of the core activities in the financial sector which has a significant impact on the economy and business growth. Credit is the provision of money or bills that can be equated with it, based on a loan agreement between banks and other parties that requires the agreement to repay the debt after a certain period of time by providing interest. However, the process within these financial institutions needs to assess the feasibility of granting credit to customers who apply for credit. To facilitate the determination of eligibility for granting credit to customers, an accurate and effective analytical method is needed to help solve problems in determining the eligibility classification for granting credit to customers by applying the Naive Bayes, K-Nearest Neighbors (K-NN) and Linear Regression algorithms. Based on the results of the tests that have been carried out using the three algorithms obtained, the results show an accuracy value on K-NN of 87.837%, calculations using the Naïve Bayes algorithm have an accuracy value of 88.917%, while calculations using the Linear Regression algorithm produce a Mean absolute error value of 6.703. It can be concluded that in bank creditworthiness fraud using the Naïve Bayes algorithm method is more accurate when compared to the K-NN and Linear Regression algorithms
ANALYSIS OF FACTORS DETERMINING STUDENT SATISFACTION USING DECISION TREE, RANDOM FOREST, SVM, AND NEURAL NETWORKS: A COMPARATIVE STUDY Riyanto, Andi Dwi; Wahid, Arif Mu'amar; Pratiwi, Aniec Anafisah
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2188

Abstract

Student satisfaction is crucial in higher education, impacting student loyalty, retention rates, and institutional reputation. This study addresses the gap in applying advanced machine learning techniques to predict and understand key determinants of student satisfaction. The primary objective is to analyze and predict the factors determining student satisfaction using four machine learning models: Decision Tree, Random Forest, SVM, and Neural Networks. The dataset comprises 2527 entries with seven relevant features. Data preprocessing involved normalization and exploratory data analysis (EDA) to ensure accurate analysis. The Neural Network model achieved the highest accuracy with an MSE of 0.001399, RMSE of 0.037397, MAE of 0.030773, and R² of 0.998154, followed closely by the SVM model. These results suggest that advanced machine learning models, particularly Neural Networks and SVM, are effective in predicting student satisfaction and identifying key areas for improvement. This study contributes to understanding the determinants of student satisfaction using machine learning models, providing practical implications for educational administrators to develop targeted strategies to enhance student satisfaction by focusing on critical factors such as academic support and financial aid. The findings highlight the importance of using advanced predictive techniques to gain deeper insights into student satisfaction, thereby enabling institutions to implement more effective interventions. Future research should explore additional variables and more sophisticated model architectures to further improve predictive accuracy and expand the applicability of these models in educational settings.
Co-Authors Abid, Umar Abdul Andi Dwi Riyanto Ardiansyah, Rizky Firman Pratama, Adhi Rouf, Erik Halma Saraswati, Wahyuning Tyas Tanfitra, Adhim Tarwoto Wahid, Arif Mu'amar Wahid, Arif Mu’amar Waluyo, Bibit