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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal Riset Informatika bit-Tech International Journal Engineering and Applied Technology (IJEAT)
Gina Purnama Insany
Nusa Putra University
Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Electrical & Electronics Engineering Engineering Mechanical Engineering

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Research topic modeling in informatics engineering study program at Nusa Putra University using LDA method Kamdan; Ivana Lucia Kharisma; Gina Purnama Insany; Paikun
INTERNATIONAL JOURNAL ENGINEERING AND APPLIED TECHNOLOGY (IJEAT) Vol. 5 No. 2 (2022): November 2022
Publisher : Nusa Putra University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/ijeat.v5i2.76

Abstract

Writing research reports at the undergraduate level is one of the obligations that must be fulfilled by students as a fulfillment of graduation requirements at a university. One of the independent learning programs implemented at Nusa Putra University is through the research method, where students are required to conduct research as a graduation requirement in the Study Completion Program course. The growing development of information and communication technology provides opportunities for students to determine research themes. However, sometimes students take research themes that are not in accordance with the concentration in the study program. This research was conducted with the aim of identifying how the LDA topic modeling method can analyze research topic trends by modeling topics on research titles that have been taken by students at the Informatics Engineering Study Program, University of Nusa Putra. Latent Dirichlet Allocation (LDA) is one of the most popular topic modeling methods today. This research uses a dataset in the form of 159 titles of study completion program research reports and tittles of final assignment reports for students of the Informatics Engineering study program, University of Nusa Putra. This research is expected to be a reference in conducting research by students based on the topics that have been modeled
Perancangan Sistem Otomatisasi Pemberi Pakan Ikan Lele Berdasarkan Suhu Air Menggunakan Logika Fuzzy Sugeno Somantri Somantri; Gina Purnama Insany; Siti Olis; Kamdan Kamdan
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 9, No 2 (2023): Volume 9 No 2
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v9i2.65823

Abstract

Ikan merupakan kelas vertebrata yang dikategorikan sebagai hewan ektotermik, artinya suhu tubuhnya berubah-ubah tergantung suhu lingkungan, hal tersebut berpengaruh terhadap tingkah laku makan ikan, saat ini sudah banyak sistem otomatisasi pakan ikan, namun sistem yang ada belum memperhatikan kondisi lingkungan, faktor yang sangat signifikan berpengaruh terhadap tingkah laku makan ikan adalah suhu air, dari permasalahan tersebut, peneliti membuat sistem otomatisasi pemberi pakan ikan lele berdasarkan suhu air menggunakan logika fuzzy sugeno. Sistem yang dibuat menggunakan metode pengembangan sistem prototype dan logika fuzzy sugeno, logika fuzzy sugeno digunakan untuk membuat aturan banyaknya pakan yang keluar berdasarkan parameter suhu air. variabel input suhu air memiliki rentang antara 0-36 oC dan variabel output jumlah pakan memiliki rentang 0-100%, hasil pengujian pada aplikasi matlab menunjukan akurasi yang tinggi, dari pengujian motor servo, didapat keluaran pakan 20 gram setiap satu kali putaran dalam waktu satu detik, pada pengujian sensor suhu air didapat selisih rata-rata 0.45 oC dengan rata-rata error 1,8%. Pada pengujian penjadwalan didapat selisih pada waktu pagi, siang dan sore hari yaitu 5 detik. Pengujian lapangan dilakukan pada kolam berukuran 4x3 meter dengan bobot ikan 600 kg, dari hasil perhitungan, kebutuhan pakan dalam satu hari yaitu 18 kg, maka sistem harus melakukan 900 kali putaran dengan waktu 15 menit untuk memenuhi kebutuhan pakan ikan dalam kolam tersebut.
Comparison of K-means and DBSCAN Web- Based Food in Clustering Based on Nutritional Content Gina Purnama Insany; Anggun Fergina; Muhammad Ilham Juardi
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.2813

Abstract

Food is the main energy source for the human body; however, poor dietary habits can lead to health risks such as obesity and cardiovascular diseases. Understanding the nutritional composition of food is essential to support healthier dietary decisions. Clustering food based on nutritional content can support personalized diet planning and assist healthcare professionals in recommending healthier food choices. This study applies clustering techniques to group foods based on their nutritional content specifically carbohydrate, calorie, protein, and fat levels using K-Means and DBSCAN algorithms. These unsupervised learning methods are suitable for analyzing numerical data without predefined categories. A key challenge in clustering is determining the optimal number of clusters; thus, evaluation methods such as the Elbow Method, Davies-Bouldin Index (DBI), and Silhouette Score were utilized. The K-Means algorithm achieved a Silhouette Score of 0.578 and a DBI of 0.661, indicating reasonably good clustering, though cluster separation was not optimal. In contrast, DBSCAN outperformed K-Means with a Silhouette Score of 0.626 and a DBI of 0.328, suggesting more compact and well-defined clusters. This indicates that DBSCAN formed more distinct and separated clusters, which is essential for effective grouping of foods based on nutritional similarity. The clustering results were deployed via an interactive web application using Streamlit an open-source Python framework enabling rapid development of lightweight web interfaces. This platform allows users to interactively explore clustering patterns through visualizations and tables, providing an intuitive tool to understand food groupings based on nutritional profiles
Prediction of Nile Tilapia Fingerling Production Using Multiple Linear Regression Alfiansyah Hidayat; Gina Purnama Insany; Zaenal Alamsyah; Evi Amriawati; Muhammad Nurdin
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.2829

Abstract

The production of Nile tilapia fingerlings plays a crucial role in ensuring the sustainability of freshwater aquaculture systems, particularly in Indonesia, where tilapia is a major source of protein and livelihood. Accurate prediction of fingerling output can significantly enhance resource efficiency, reduce operational costs, and support economic sustainability in hatchery operations. This study aims to predict fingerling production based on environmental factors and feed quantity, using data from the Center for Freshwater Aquaculture Development (BBPBAT) in Sukabumi, Indonesia. Multiple Linear Regression (MLR) was chosen for its interpretability and suitability for modeling linear relationships in moderate-sized datasets. MLR was applied to model the relationship between water temperature, pH, dissolved oxygen (DO), ammonia concentration, and feed quantity with fingerling production. The dataset consisted of 147 historical records, and model performance was evaluated using R² = 0.836, Mean Absolute Error (MAE) = 35,664, Mean Squared Error (MSE) = 2,014,982,858, and Root Mean Squared Error (RMSE) = 44,852. These results indicate a strong predictive capability. Compared to baseline mean-based predictions, the model significantly reduces forecast error and captures the production variability more effectively. Furthermore, the model was deployed via an interactive web-based tool using the Streamlit framework. This application allows hatchery staff to input current environmental conditions and feed data to generate real-time production forecasts, facilitating proactive management and better resource planning. Overall, this study demonstrates that MLR is a practical and effective tool for supporting decision-making in aquaculture production systems.
Implementation of IOT-based Motorcycle Security System with Cut Off Engine and Mobile Application Gina Purnama Insany; Sindi Aulia Alawiyah; Somantri; Deni Ramdan Septian; Iyusmani
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2841

Abstract

The increasing rate of motorcycle theft highlights the limitations of conventional security systems such as mechanical alarms and double locks, which often fail to provide proactive protection. This research proposes an Internet of Things (IoT)-based motorcycle security system integrating an engine cut-off feature, GPS tracking, vibration detection, and real-time notifications via a custom mobile application. Unlike previous solutions that commonly rely on SMS gateways or third-party services, this system leverages the Wemos D1 Mini microcontroller and Firebase Realtime Database to enable high-speed, two-way communication between the vehicle and the user. The system allows real-time vehicle location monitoring, remote engine control, and immediate detection of suspicious activities through the SW-420 vibration sensor connected to an audible buzzer alarm. The Android application, developed independently using the Kodular platform, not only provides digital vehicle location mapping but also enables quick engine deactivation and emergency alerts within seconds. Laboratory and field tests confirm a response time of less than one second for the engine cut-off function and accurate GPS tracking with an average deviation of under 10 meters. The primary innovation of this study lies in the full integration of IoT components, mobile interfaces, and cloud databases into a single platform without external dependencies, thereby enhancing efficiency, reliability, and system flexibility. The results demonstrate the system’s potential to deliver adaptive and modular vehicle security solutions, with opportunities for future enhancements such as geofencing, biometric authentication, and hybrid connectivity for improved resilience.
Optimization Of Food Product Sales System and Customer Service Through Customer Relationship Management Approach Anggun Fergina; Yulva Cintakandida; Gina Purnama Insany
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.2943

Abstract

ABC Kitchen, a micro, small, and medium enterprise (MSME) in the culinary sector, faced operational inefficiencies due to manual data management and a lack of integration between ordering and payment processes. This study developed a web-based Customer Relationship Management (CRM) system using the IDIC (Identify, Differentiate, Interact, Customize) model to address these issues. Functional validation was conducted using black-box testing, which evaluates system performance against predetermined requirements without examining the internal code structure. Test results on four captured pages demonstrated a 100% success rate across 13 functional scenarios. The system enables automatic customer identification from transaction history, personalized promotions through preference-based differentiation, real-time interactions through an intuitive user interface, and service customization such as vouchers, various payment options, and VIP membership features. Furthermore, an analytics dashboard provides administrators with actionable insights to monitor customer behavior and sales trends, supporting data-driven decision-making. This study contributes to the MSME digital transformation literature by demonstrating how CRM integration can enhance customer engagement, improve operational efficiency, and provide a competitive advantage in a dynamic market environment. The novelty of this study lies in tailoring CRM to the specific operational and marketing needs of micro-scale culinary businesses, enabling sales growth and customer loyalty through an easily accessible sales system. This study demonstrates how context-specific digital CRM solutions can accelerate MSMEs' digital transformation, increase competitiveness, and create a sustainable foundation for growth in a dynamic market. 
Integration of OCR Technology with ETL Processes for Automating Data Pipeline of Financial Disbursement Documents at BPS Sukabumi Regency Muhammad Raihan Izharul Haq; Gina Purnama Insany; Somantri
Jurnal Riset Informatika Vol. 7 No. 4 (2025): September 2025
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1600.245 KB) | DOI: 10.34288/jri.v7i4.395

Abstract

In the digital era, managing archival data poses challenges for many institutions, including Badan Pusat Statistik (BPS) of Sukabumi Regency, especially when dealing with unstructured PDF documents. This study develops a data pipeline by effectively integrating Optical Character Recognition (OCR) technology with Extract, Transform, Load (ETL) processes. Unstructured data from financial disbursement documents, such as SPM and SP2D, were automatically extracted with high accuracy, achieving an average of 98.52% for SPM using a combination of OCR and PDFPlumber, and 100% for SP2D extracted using PDFPlumber. Extraction results were stored in a data warehouse, then transformed using Apache Spark and loaded into data marts. ETL process was automated using Apache Airflow, which operated reliably according to dependencies. The processed data were presented through an interactive Looker Studio dashboard in real-time, supporting efficient archive management and more informed decision-making. This study not only provides a solution to existing archival management problems but also opens opportunities for further development in the application of big data technologies and business process automation in public sector.
Co-Authors adang badru jaman,anggun fergina, adang badru jaman,anggun fergina Alfiansyah Hidayat Deni Ramdan Septian Evi Amriawati IVANA LUCIA KHARISMA Iyusmani Kamdan Muhammad Ilham Juardi Muhammad Nurdin Muhammad Raihan Izharul Haq Paikun Sindi Aulia Alawiyah Siti Olis Somantri Somantri Yulva Cintakandida Zaenal Alamsyah