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All Journal Sistemasi: Jurnal Sistem Informasi Journal of Innovation and Future Technology (IFTECH) SISFOTENIKA ILKOMEDIA: Jurnal Ilmu Komputer dan Multimedia
Putra, Cendra Devayana
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science

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Application of Naïve Bayes Method for Student Performance Classification Prayoga, Riza Akhsani Setyo; Basatha, Rizky; Akbar, Muhammad Sonhaji; Elfaiz, Ersha Aisyah; Putra, Cendra Devayana
SISTEMASI Vol 14, No 2 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i2.4852

Abstract

In every school, students exhibit varying levels of performance, influenced by several factors such as parental support and involvement, participation in extracurricular activities, motivation levels, internet access for learning, teacher quality, peer influence, and learning difficulties. This study aims to classify student performance to identify those who may need additional support for improvement. The classification method employed in this research is the Naïve Bayes algorithm. The results indicate that the trained model successfully classified 25 out of 30 tested data points. The evaluation metrics achieved include a precision of 100%, recall of 80%, specificity of 100%, accuracy of 83%, and an F1-score of 89%.
The Optimisation of Stock Management: Design of an AI-Driven Inventory System Putra, Cendra Devayana; Utami, Ardhini Warih; Dwi, I Kadek; Prayoga, Riza Akhsani Setyo; Basatha, Rizky; Muhammad Sonhaji Akbar
SISFOTENIKA Vol. 15 No. 2 (2025): SISFOTENIKA
Publisher : STMIK PONTIANAK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30700/sisfotenika.v15i2.543

Abstract

The frozen food industry has witnessed remarkable growth in recent years, driven by increasing urbanization and the demand for convenient, ready-to-eat meals. Despite this upward trend, many businesses in the sector struggle with inefficient stock management, particularly in forecasting daily demand due to fluctuating consumer behavior and unpredictable external factors. This study proposes an end-to-end artificial intelligence-based stock forecasting system aimed at optimizing inventory management for frozen food businesses. By adopting the Design Thinking approach, this research places users—both consumers and internal stakeholders—at the center of the problem-solving process to uncover key operational pain points. The study explores recent technological advancements, including augmented reality, RFID, and blockchain, and integrates them into a practical framework tailored to small and medium enterprises (SMEs). Through qualitative analysis and system prototyping, the research identifies essential features for an intelligent stock management system and demonstrates how a user-centric approach can drive innovation and improve business performance. The findings offer valuable insights into the development of adaptive, data-driven solutions in the rapidly evolving frozen food sector.
Penerapan Data Mining untuk Peminjaman Buku dengan Menggunakan Algoritma Apriori PRAYOGA, RIZA AKHSANI; Basatha, Rizky; Akbar, Muhammad Sonhaji; Elfaiz, Ersha Aisyah; Putra, Cendra Devayana
Jurnal Ilmu Komputer dan Multimedia Vol. 1 No. 2 (2024): ILKOMEDIA Edisi Desember 2024
Publisher : Akademi Komunitas Negeri Putra Sang Fajar Blitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46510/ilkomedia.v1i2.18

Abstract

Buku merupakan jendela ilmu yang dimana banyak diminati oleh masyarakat. Setiap perpustakaan memiliki koleksi buku yang cukup banyak namun tidak banyak pemilik buku yang memberikan rekomendasi buku yang sering dipinjam kepada pengunjung perpustakaan. Rekomendasi peminjaman buku ini bisa digunakan untuk membantu pengunjung agar tidak bingung dalam memilih buku sehingga dengan cepat bisa memilih buku sesuai dengan kebutuhan. Selain itu dengan adanya rekomendasi peminjaman buku ini bisa membantu bagi pemilik perpustakaan dalam menyediakan buku yang sering dipinjam sehingga memiliki stok yang cukup. Metode yang digunakan dalam rekomendasi pemilihan buku ini memakai algoritma apriori sehingga nanti hasilnya berupa rekomendasi pemilihan buku beserta aturan asosiasi. Pada perhitungan algoritma ini memerlukan perhitungan support baik satu item maupun dua item dimana support memiliki minimum support 40 %. Perhitungan support ini digunakan untuk menghitung kombinasi item baik satu kombinasi item dan dua kombinasi item . Kemudian dilanjutkan untuk membuat aturan asosiasinya menggunakan perhitungan confidence serta dalam menguji keakuratan aturan asosiasi dengan perhitungan lift. Hasil yang muncul dari rekomendasi peminjaman buku berupa Buku Politik dan Buku Ekonomi dengan nilai confidence 83% dan nilai lift 1,25. Kemudian ada Buku Politik dan Buku Fiksi dengan nilai confidence 67% serta nilai lift 1,18. Lalu ada Buku Ekonomi dan Buku Fiksi dengan nilai confidence 60% dengan nilai lift 1,06.
PENENTUAN DOSIS KOAGULAN PADA PENGOLAHAN AIR MINUM: PENDEKATAN FUZZY BERBASIS DATA DAN PENENTUAN FUZZY SET BERBASIS Z-SCORE Cinthya, Monica; Vinarti, Retno Aulia; Septiyanti, Nisa Dwi; Putra, Cendra Devayana; Rahman, Erik; Abdillah, Rifqi
Journal of Innovation And Future Technology (IFTECH) Vol. 7 No. 2 (2025): Vol 7 No 2 (Agustus 2025): Journal of Innovation and Future Technology (IFTECH)
Publisher : LPPM Unbaja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/0ffxq425

Abstract

direct use of raw water has serious health risks. Therefore, various water treatment processes are needed to make the raw water safe for use in domestic purposes. One important stage in such processing processes is coagulation and flocculation, where chemicals (coagulants) are used to remove colloidal particles and form larger floc that can be easily precipitated through sedimentation and filtration. Determination of the optimal coagulant dosage is essential to achieve the desired water quality. However, jer-test problems, the non-linear nature of water, and the complexity of coagulation theory can make it difficult to determine the optimal dose. Therefore, in this study, a system is proposed that uses a data-based fuzzy approach and fuzzy set determination using z-score to study data patterns and relationships between parameters in the coagulation process. The proposed method utilizes a fuzzy approach to address the non-linear nature of water and the complexity of coagulation theory. The system uses the collected data patterns to develop fuzzy models that can predict optimal coagulant doses based on specific conditions. This approach allows the system to learn from existing data and identify patterns of relationships that may be hidden between relevant parameters. The results showed that the proposed system achieved an RMSE value of 0.7639589866827494, while the MSE value was 0.5836333333333333333. This suggests that the system can provide a fairly accurate prediction of the dose of coagulant required in the coagulation process.
Co-Authors Abdillah, Rifqi Akbar, Muhammad Sonhaji Ardhini Warih Utami, Ardhini Warih Cinthya, Monica Dwi, I Kadek Elfaiz, Ersha Aisyah Muhammad Sonhaji Akbar Nisa Dwi Septiyanti Rahman, Erik Retno Aulia Vinarti Riza Akhsani Setyo Prayoga Rizky Basatha