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INDONESIA
Faktor Exacta
Published by Universitas Indraprasta PGRI
ISSN : 1979276X     EISSN : 2502339X     DOI : -
Core Subject : Science, Engineering,
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering
Faktor Exacta is a peer review journal in the field of informatics. This journal was published in March (March, June, September, December) by Institute for Research and Community Service, University of Indraprasta PGRI, Indonesia. All newspapers will be read blind. Accepted papers will be available online (free access) and print version.
Arjuna Subject : -
Articles 10 Documents
 1 
Search results for , issue "Vol 18, No 1 (2025)" : 10 Documents clear
Penerapan Metode Naïve Bayes Pada Pengaruh Penggunaan Gadget Terhadap Nilai Siswa Sekolah Dasar Nurhalimah, Nurhalimah; Nurhasanah, Nurhasanah
Faktor Exacta Vol 18, No 1 (2025)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v18i1.27183

Abstract

Saat ini, penggunaan gadget telah menjadi bagian dari kehidupan sehari-hari, termasuk bagi siswa sekolah dasar. Gadget sering digunakan untuk menunjang proses pembelajaran, namun penggunaan yang berlebihan dan tidak terkontrol dapat berdampak negatif terhadap prestasi akademik siswa. Penelitian ini bertujuan untuk menganalisis pengaruh penggunaan gadget terhadap nilai akademik siswa sekolah dasar dengan menerapkan metode Naïve Bayes sebagai teknik klasifikasi. Metode Naïve Bayes digunakan untuk mengklasifikasikan data berdasarkan beberapa variabel, yaitu durasi penggunaan gadget, jenis aktivitas dengan gadget, dan pola belajar siswa. Hasil penelitian menunjukkan bahwa siswa yang menggunakan gadget dengan durasi yang terkontrol dan untuk ak-tivitas edukatif cenderung memiliki nilai akademik lebih tinggi dibandingkan dengan mereka yang menggunakan gadget secara berlebihan untuk hiburan. Selain itu, pola belajar yang lebih ter-struktur, seperti belajar secara mandiri atau dengan bimbingan, ber-kontribusi positif terhadap prestasi akademik siswa. Penelitian ini memberikan wawasan mengenai pentingnya pengawasan dan pengelolaan penggunaan gadget bagi siswa sekolah dasar. Dengan adanya hasil ini, diharapkan orang tua dan pendidik dapat lebih bijak dalam mengarahkan penggunaan gadget agar lebih optimal dalam mendukung proses pembelajaran.
Comparison of PID and Fuzzy Logic Controller Performance on Linear and Nonlinear Dynamics of a Quadrotor Zuhri, Muhammad Rizki
Faktor Exacta Vol 18, No 1 (2025)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v18i1.26091

Abstract

Implementasi Sistem E-Commece Berbasis Website Pada Usaha Micro Kecil Dan Menengah (UMKM) Jajanan Mak Ate Menggunakan Model Pengembangan Extreme Programming Muiz, Adam; Fauzi, M Yahya Ibnu
Faktor Exacta Vol 18, No 1 (2025)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v18i1.27191

Abstract

Penelitian ini bertujuan untuk merancang dan mengembangkan sistem E-Commerce yang sesuai dengan kebutuhan dengan berfokus pada penerapan sistem E-Commerce pada pelaku Usaha Mikro Kecil dan Menengah (UMKM) yaitu Jajanan Mak Ate dengan menggunakan model pengembangan Extreme Programming (XP). Di era digital saat ini, UMKM seperti Jajanan Mak Ate menghadapi tantangan dalam memperluas pasar dan mengoptimalkan penjualan produk secara efisien. Untuk mengatasi tantangan tersebut, dirancang dan dikembangkanlah sebuah sistem E-Commerce yang sesuai dengan kebutuhan UMKM ini. Model pengembangan Extreme Programming dipilih karena sifatnya yang fleksibel dan kemampuannya untuk beradaptasi dengan perubahan kebutuhan selama proses pengembangan. Dengan pendekatan ini, penelitian bertujuan untuk menghasilkan sistem E-Commerce yang fungsional, mencakup fitur-fitur penting seperti katalog produk, keranjang belanja, pemrosesan pesanan, dan sistem pembayaran. Hasil dari implementasi ini menunjukkan bahwa sistem E-Commerce yang dikembangkan mampu meningkatkan efisiensi operasional dan memperluas jangkauan pasar UMKM Jajanan Mak Ate, sehingga berdampak positif terhadap peningkatan penjualan produk
Optimasi Lingkungan Tenang dengan Sistem Monitoring Kebisingan Menggunakan Logika Fuzzy Sutia, Diar Dwi; Setyowati, Endah; Hadi Putri, Dewi Indriati
Faktor Exacta Vol 18, No 1 (2025)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v18i1.24869

Abstract

Identification of Stock Breakouts Using Support Vector Machine with Integrated Fundamental Data and Random Forest Prediction Utama, Gusti Bagus Cahya; Chusyairi, Ahmad; Sahara, Riad
Faktor Exacta Vol 18, No 1 (2025)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v18i1.27805

Abstract

Implementasi Sistem Rekomendasi Menggunakan Metode Collaborative Filtering Pada Aplikasi Pemesanan Menu Restoran Berbasis Android Soleh, Muhamad; Ristianto, Bagas Eka
Faktor Exacta Vol 18, No 1 (2025)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v18i1.25376

Abstract

During the outbreak of the Corona virus disease (Covid-19), many changes have been experienced by society in various fields, including social, economic, political, and education. This has resulted in changes in people's daily activities, with many restrictions imposed to reduce the spread of the Covid-19 virus. These changes have also affected the food and beverage industry, which now uses mobile or web applications to serve customers. With the changes experienced by businesses that already use mobile or web applications, application or web development can be used to improve business by promoting the available menu at a food and beverage business by recommending the menu to customers through the application or web. The recommendation system is very influential for customers in making the decision to order other menus. The development of an application for menu recommendations using User-Based Collaborative Filtering with cosine similarity as the calculation of similarity value and prediction value calculation. The result of this research is an Android-based mobile application for ordering menu to be eaten in a restaurant, by providing a menu recommendation based on the prediction results conducted using the user-based collaborative filtering method.
Pemodelan Klasifikasi Siswa Berprestasi dengan Random Forest: Studi Kasus pada Bimbingan Belajar Apandi, Sopiyan
Faktor Exacta Vol 18, No 1 (2025)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v18i1.27163

Abstract

Academic achievement is a goal desired by every student, leading many to attend additional lessons at tutoring institutions to improve their learning outcomes. This study aims to classify student achievements at a tutoring institution based on periodic evaluation results using the Random Forest algorithm. The dataset used includes 112 students from the 2017 to 2018 academic year, with 67 student records for training and 45 for testing. Evaluation results indicate that students classified as underachieving dominate (98 students), while only 14 students meet the criteria for high achievement. The analysis shows the highest average scores in English (85.38) and Mathematics (83.66), while the lowest averages are in Social Studies (70.47) and Science (78.96). Applying the Random Forest algorithm to the test data resulted in four students with a maximum confidence score of 0.933, demonstrating that the model has high accuracy and can be utilized by the institution to monitor and motivate students to achieve high-performance categories. This research contributes to the development of data-driven systems to support decision-making processes in tutoring institutions.
Analisis Pengukuran Kinerja Supply Chain Management Pendistribusian Barang Pada PT Alfaria Trijaya Dengan Metode Supply Chain Operation Reference (SCOR) dan Analitycal Hierarchy Process (AHP) Suhendar, Endang; Nurfida, Arifia; Borman, Mohammad Riski; Nursahim, Khabib
Faktor Exacta Vol 18, No 1 (2025)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v18i1.25971

Abstract

Competition in the industrial world is a major challenge for companies in carrying out the production activities. PT Alfaria Trijaya is a company that produces frozen chicken processing. The SCM (Supply Chain Management) concept has been implemented to regulate the flow of products from suppliers to the hands of end consumers. However, the company's supply chain experienced problems due to poor delivery processes such as production planning inconsistencies, demand fluctuations and late deliveries. The company felt the need to measure the performance of the company's supply chain. The objective to be achieved in this study is to find out how effective the supply chain implementation is at PT Alfaria Trijaya. The method used is the Supply Chain Operation Reference (SCOR) which is divided into five processes, namely Plan, Source, Make, Deliver and Return, and the Analytical Hierarchy Process (AHP) method. The final score is 89.72. Thus, the performance calculation in the case study into the good attribute performance position has a major influence, namely on the Make and Return processes and each return with a final value of 20.90 and 22.83 for the attribute needs to be maintained. However, there are three attributes with low final values, namely the Plan, Source, and Deliver processes, it is necessary to propose a strategy to be able to increase their value.
QnA-based Learning Platform Using Instant Messaging and Deep Learning Suprayitno, Hadi; Tjong, Wan Sen
Faktor Exacta Vol 18, No 1 (2025)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v18i1.28040

Abstract

The explosion of instant messaging apps has created a new paradigm for learning and knowledge sharing. In this paper, we introduce an innovative Q&A-based learning platform that leverages the power of instant messaging and deep learning to provide inexpensive personalized learning experiences for students. This helps those who may not have access to teachers or need more support outside of regular class hours. Our platform utilizes deep learning technology and/or natural language processing to analyze and respond to students' queries in almost real-time and nonstop 24/7. By integrating instant messaging with deep learning, this platform enables students to engage in interactive and conversational learning experiences. Personal or private messages enable learning systems that are tailored to individual needs and learning styles. We used the Rapid Application Development method with an object-oriented approach to create this platform. We demonstrate the proof of concept of this platform through a series of experiments and evaluations. Based on the results of the trial, the designed platform can attract the attention of many students when learning. The contributions of this paper are threefold. First, we propose a novel Q&A-based learning platform that integrates instant messaging and deep learning to provide personalized learning experiences. Second, we demonstrate the effectiveness of our platform through a series of experiments and evaluations. Finally, we provide a framework for future research and development in the area of intelligent Q&A platforms for personalized learning.
Implementation of Linear Regression Method in Light Strength Measurement Using GY1750BH Sensor Kartika, Kartika; Jannah, Misbahul; Aulia, Rizki; Misriana, Misriana
Faktor Exacta Vol 18, No 1 (2025)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v18i1.26062

Abstract

Developments in light sensor technology have made it possible to achieve better measurement accuracy. The GY1750BH sensor, for example, is known for its ability to detect changes in light with high sensitivity. While this sensor has many advantages, the accuracy of the results depends highly on the calibration method. Without proper calibration, measurement data can suffer from biases detrimental to the applications that rely on it. Linear regression methods can extract the mathematical relationship between the sensor output and light intensity in light sensors. In light sensor calibration, linear regression helps determine the relationship between the sensor-generated signal (e.g., voltage or current) and the measured light intensity. Thus, we can mathematically map the sensor's response to changes in light intensity, which is used for measurement correction to get closer to the actual value. Implementing linear regression in the GY1750BH sensor is expected to contribute significantly to improving the measurement accuracy of this sensor. By modeling the sensor's response to the actual light intensity, the data generated is expected to be more consistent and accurate so that it can be used in applications that require high accuracy. The results of this study are light intensity measurement with the application of linear regression on the GY 1750 BH sensor, which is more stable, and the resulting comparison is close to the measurement results using measuring instruments. The error produced before using linear regression is 1.2%, and when using linear regression on the GY 1750 BH sensor, it becomes 0.54%.

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