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Bulletin of Information Technology (BIT)
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 27220524     DOI : 10.47065/bit.v2i3.106
Core Subject : Science,
Computer Science & IT
Jurnal Bulletin of Information Technology (BIT) memuat tentang artikel hasil penelitian dan kajian konseptual bidang teknik informatika, ilmu komputer dan sistem informasi. Topik utama yang diterbitkan mencakup:berisi kajian ilmiah informatika tentang : Sistem Pendukung Keputusan Sistem Pakar Sistem Informasi, Kriptografi Pemodelan dan Simulasi Jaringan Komputer Komputasi Pengolahan Citra Dan lain-lain (topik lainnya yang berhubungan dengan teknologi informasi)
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 256 Documents
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Pengembangan dan Implementasi Sistem Deteksi Serangan DDoS Berbasis Algoritma Random Forest Kiswanto, Dedy; Ramadhani, Fanny; Maulida Surbakti, Nurul; Afiati Nasution, Nadrah
Bulletin of Information Technology (BIT) Vol 6 No 3: September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i3.2203

Abstract

Serangan Distributed Denial of Service (DDoS) merupakan ancaman serius bagi keamanan jaringan, sementara metode deteksi tradisional seperti threshold-based detection dan signature-based detection memiliki keterbatasan dalam mengenali pola serangan baru maupun anomali lalu lintas yang kompleks. Penelitian ini bertujuan merancang dan mengimplementasikan model prediksi serangan DDoS berbasis algoritma Random Forest yang mampu membedakan trafik normal dan berindikasi serangan secara akurat. Pendekatan Research and Development (R&D) digunakan, meliputi studi literatur, perancangan model, implementasi, serta evaluasi performa menggunakan metrik akurasi, precision, recall, F1-score, confusion matrix, dan learning curve. Berdasarkan hasil evaluasi, model Random Forest menunjukkan kinerja sangat baik dengan akurasi 0,99942 (99,942%). Precision untuk kelas 0 dan 1 masing-masing sebesar 0,99979 dan 0,99884, sedangkan recall mencapai 0,99928 untuk kelas 0 dan 0,99966 untuk kelas 1. Nilai F1-score tinggi, yaitu 0,99953 untuk kelas 0 dan 0,99925 untuk kelas 1, dengan macro average F1-score sebesar 0,99939 dan weighted average sebesar 0,99942, menunjukkan keseimbangan performa pada kedua kelas. Confusion Matrix menunjukkan kesalahan klasifikasi rendah (44 false positive dan 13 false negative dari 99.066 sampel). Analisis learning curve mengungkapkan akurasi pelatihan stabil di atas 0,998, sedangkan akurasi validasi meningkat dari 0,986 pada 10.000 data hingga di atas 0,998 pada 80.000 data, dengan jarak antarkurva semakin kecil. Pola ini menandakan model mampu memanfaatkan data tambahan untuk meningkatkan generalisasi tanpa gejala overfitting atau underfitting. Temuan ini membuktikan bahwa model Random Forest yang dirancang dapat menjadi solusi deteksi dini serangan DDoS yang andal, adaptif, dan berpotensi diintegrasikan dalam sistem keamanan jaringan secara real-time.
Sistem Pemantauan Tanaman Dalam Pot Indoor Dengan Internet of Things Iqbal Setiawan, Muhammad; Efendi, Bachtiar; Karim Syahputra, Abdul
Bulletin of Information Technology (BIT) Vol 6 No 3: September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i3.2204

Abstract

This study discusses the design and implementation of an Internet of Things (IoT)-based indoor potted plant monitoring system, which aims to help users care for plants in a more effective and efficient manner. The system uses an ESP32 microcontroller connected to a DHT22 sensor to measure air temperature and humidity, soil moisture, an LDR to measure light intensity, and a TDS sensor to monitor nutrient levels in the water. Data collected from the sensors is transmitted directly via a WiFi connection to an MQTT broker, displayed on a Node-RED dashboard, and stored in Firebase for historical documentation purposes. This system has two operational modes, manual and automatic, allowing users to control the water pump and grow light directly or let the system operate based on pre-set parameters. Test results show that all sensors function accurately and respond to changes in environmental conditions, thereby improving efficiency in watering and lighting. The advantage of this system lies in the integration of four monitoring parameters into a single platform that is easy to use, flexible, and widely accessible. This research is expected to provide practical solutions for urban agriculture and the development of smart farming at the household level, although further testing on various plant types and environmental conditions is still needed for further refinement
Metode Maut dan Waspas Menentukan Mahasiswa Berprestasi di Universitas Bhayangkara Jakarta Raya dengan Pembobotan ROC Gunawan Sudarsono, Bernadus; Galih Whendasmoro, Raditya
Bulletin of Information Technology (BIT) Vol 6 No 3: September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i3.2205

Abstract

Becoming an outstanding student in higher education is a positive and proud achievement, reflecting the national education goal of developing students' potential to become educated, creative, and democratic and responsible citizens. Determining outstanding students faces obstacles when prospective candidates excel in some criteria but do not meet the standards in other criteria. To help the evaluation team, an effective decision support system is needed. The Multi-Attribute Utility Theory (MAUT) method with ROC weighting was used to convert various interests into numerical values ​​on a scale of 0-1, with the results showing that student Erwin Sulistiono (A4) had the highest utility value, namely 0.8975. For comparison, the Weighted Aggregated Sum Product Assessment (WASPAS) method was also applied, combining the Weighted Sum Model (WSM) and the Weighted Product Model (WPM), which gave consistent results with MAUT, showing that both methods provide an objective approach in determining outstanding students, although WASPAS with ROC weighting offers higher accuracy by combining the advantages of two scoring approaches.
Sistem Pakar Berbasis AI dengan Artificial Neural Networks untuk Identifikasi Hama & Penyakit Jamur Tiram Husain, Nursuci Putri; Mirnawaty Sultan, Dian
Bulletin of Information Technology (BIT) Vol 6 No 3: September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i3.2208

Abstract

Oyster mushroom cultivation is an agricultural sector with high economic potential, but its productivity is often disrupted by pests and diseases. Inappropriate management due to farmers' limited knowledge can cause significant losses. This study aims to develop an expert system for oyster mushroom pest and disease diagnosis based on Artificial Neural Networks (ANN), to assist in early identification of emerging disorders. The dataset consists of 150 samples covering a combination of symptoms and disease labels, collected from two different cultivation locations. There are several stages in this study, namely the preprocessing process that includes label encoding, feature normalization using Z-score, and data division in a ratio of 80% for training and 20% for testing. The ANN model was designed using a Multi-Layer Perceptron (MLP) with two hidden layers containing 10 neurons each, a ReLU activation function, an Adam solver, and a maximum iteration of 1000. The test results showed the model has an accuracy rate of 97%, with perfect precision and recall values ​​for most disease classes. This study shows that the ANN approach is able to effectively recognize oyster mushroom disease symptom patterns. This system can be an efficient and adaptive diagnostic tool, and has the potential to be further developed as a smart agricultural technology solution
Sentiment Analysis of User Reviews of Kitalulus Job Search App on Google Play Store Using Machine Learning Hendri Hariadi, Astrid Ayuzi Putri; Intan, Bunga; Armanto
Bulletin of Information Technology (BIT) Vol 6 No 3: September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i3.2220

Abstract

This study seeks to assess the sentiment of user reviews for the "KitaLulus" job search app found on the Google Play Store, utilizing Machine Learning techniques. Given the intensifying competition within the job market, this application serves as a crucial resource for job seekers in Indonesia. The study employs a sentiment analysis method to categorize user reviews into three groups: positive, negative, and neutral. The dataset comprises 20,000 reviews in Indonesian gathered from the Google Play Store. The methodologies used in this study include K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Artificial Neural Network (ANN), Logistic Regression, and Naïve Bayes. The findings indicate that various algorithms demonstrate different levels of accuracy in sentiment classification. It is anticipated that the outcomes of this analysis will offer valuable insights to developers about the quality and effectiveness of the "KitaLulus" application, while also assisting users in making informed decisions prior to utilizing the app. Additionally, this research contributes to the domain of sentiment analysis, particularly concerning job search applications in Indonesia.
Komparasi Model LSTM dan CNN-LSTM untuk Peramalan Curah Hujan di Kota Tangerang Selatan Uliyatunisa; Supriatna, Dahlan
Bulletin of Information Technology (BIT) Vol 6 No 3: September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i3.2235

Abstract

This study compares the performance of Long Short-Term Memory (LSTM) and Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) models for daily rainfall forecasting in South Tangerang City using meteorological data from January 2005 to July 2025. Data from official meteorological stations was processed with mean imputation for missing values and MinMaxScaler normalization. Models were evaluated based on Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Squared Error (MSE), and coefficient of determination R². Results show CNN-LSTM outperforms with RMSE 0.79, MAE 0.63, MSE 0.62, and R² 0.61, compared to LSTM (RMSE 0.83, MAE 0.60, MSE 0.68, R² 0.58). Prediction visualizations confirm CNN-LSTM's accuracy in capturing extreme patterns, with statistically significant differences via t-test. The novelty lies in using a long-term (20-year) dataset for tropical Indonesia, demonstrating the hybrid model's efficacy for complex spatio-temporal predictions. Findings support flood early warning systems and water resource management, recommending additional climate variable integration for further development.
Penerapan Algoritma Bellman-Ford Untuk Optimisasi Pengendara Dalam Menentukan Rute Terpendek UMKM Di Kabupaten Padang Lawas Julia Hasibuan, Putri Indah; Ikhwan, Ali
Bulletin of Information Technology (BIT) Vol 6 No 3: September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i3.2243

Abstract

This study designs a web-based Geographic Information System (GIS) using the Bellman-Ford algorithm to determine the shortest route for Micro, Small, and Medium Enterprises (MSMEs) in Padang Lawas Regency. The main problem faced by MSMEs is the limited and insufficient use of information technology. This condition makes it difficult for the public to find strategic MSME locations and the fastest routes to business sites, leading to low competitiveness and marketing inefficiency. To address this issue, the system was developed using the waterfall model and integrated with Leaflet JS technology, enabling broad accessibility through the web without additional installation. The Bellman-Ford algorithm was chosen for its ability to calculate the shortest path even when negative weights are present in the graph. Test results show that the optimal route obtained is 1.795 km, more efficient compared to an alternative route of 2.563 km, providing a distance saving of about 30%. The system has proven capable of delivering fast and accurate route recommendations while simultaneously presenting MSME location information interactively. The novelty of this research lies in the integration of Bellman-Ford with interactive web-based digital maps specifically for MSME promotion, which has rarely been applied in regional contexts. The purpose of this study is to improve marketing efficiency, expand accessibility, and strengthen the competitiveness of MSMEs in Padang Lawas. Furthermore, this research is expected to make a real contribution to the community in finding MSMEs more quickly and accurately..
Sistem Informasi Geografis Pemetaan Daerah Rawan Pangan Pada Dinas Ketahanan Pangan di Kabupaten Labuhanbatu Utara Dengan Algoritma Dijkstra Berbasis Web Almanda, Rico; Ikhwan, Ali
Bulletin of Information Technology (BIT) Vol 6 No 3: September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i3.2248

Abstract

Food security is a strategic aspect that determines community welfare and regional stability. In North Labuhanbatu Regency, 24 out of 82 villages and 8 sub-districts are still categorized as food-insecure. The main challenges include manual mapping processes and difficulties in determining the nearest food distribution routes, which make government interventions less efficient. This study aims to develop a web-based Geographic Information System (GIS) to map food-insecure areas and calculate the fastest distribution routes using Dijkstra’s algorithm. The system was developed using the waterfall model through observation, interviews, and literature studies. The test results show that the system can interactively visualize 24 food-insecure villages and recommend distribution routes with an average distance of 37.04 km and an average travel time of 37.35 minutes. These results are more efficient than manual methods, which tend to generate longer routes and higher travel times. The main contribution of this research is the application of Dijkstra’s algorithm in a web-based GIS for mapping food-insecure villages, which has not been implemented previously in North Labuhanbatu Regency. This finding is expected to support local governments in making strategic decisions regarding the acceleration of food distribution, thereby improving public services and strengthening community food security.
Aplikasi Belajar Matematika di Sekolah Dasar Negeri 2 Lape Berbasis Android Untuk Meningkatkan Pemahaman Siswa Hilmy Adrizul Rifqi Hidayat; Esabella, Shinta; Afriliansyah, Jonathan
Bulletin of Information Technology (BIT) Vol 6 No 3: September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i3.2200

Abstract

This study aims to develop an Android-based Mathematics Learning Application as an interactive and engaging learning medium to enhance elementary school students' understanding, particularly at Lape 2 Public Elementary School. The research employs the Waterfall software development model, which consists of five stages: requirements analysis, design, implementation, testing, and maintenance. Data collection was carried out through the distribution of questionnaires as well as the administration of pre-tests and post-tests to fifth-grade students. The application was developed with core features including learning materials, practice questions, automatic scoring, and learning outcome reports. Testing was conducted using the black box testing method to evaluate the application's functionality, and the improvement in students’ understanding was analyzed using the N-Gain method. The results indicate an improvement in students’ understanding, categorized as moderate to high, after using the application. This application is expected to serve as an effective, enjoyable, and relevant alternative learning medium that meets the needs of elementary school students.
Portal Belajar Tarian Sumbawa Berbasis Augmented Reality Untuk Pelestarian Seni Budaya Kepada Generasi Muda Nora Dery Sofya; Esabella, Shinta; Putra, Ardiansyah; Sari, Nikmata; Hasanuddin; Fithriati
Bulletin of Information Technology (BIT) Vol 6 No 3: September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i3.2179

Abstract

Abstrak- Tujuan dari penelitian ini untuk merancang, membuat dan mengembangkan tari Sumbawa kedalam portal belajar berbasis augmented reality sebagai upaya pelestarian kepada generasi muda dengan menggunakan metode Mutimedia Development Life Cycle (MDLC) menggunakan basis web dan android dengan objek penelitian diakukan di Kabupaten Sumbawa, Nusa Tenggara Barat. Proses perancangan, pembuatan dan pengembangan portal belajar berbasis augmented reality dilakukan dengan enam tahap yang dimulai dari tahap konsep untuk menentukan tujuan pengguna, tahap desain untuk membuat spesifik arsitektur program, tahap material collecting untuk pengumpulan bahan aplikasi, tahap assembly untuk pengkodean aplikasi, tahap testing untuk pengujian aplikasi dan tahap distribution untuk penyajian aplikasi pada halaman web dan android. Portal belajar berbasis augmented reality berhasil dibuat dengan php framework laravel dan database MySQL. Sementara untuk desain menggunakn 3D designer blender dan aplikasi augmented reality menggunakan unity serta marvelous designer. Portal belajar berbasis augmented reality berhasil diuji coba menggunakan model back box testing yang dilakukan oleh ahli informatika, budayawan dan generasi muda. Ragam fitur yang dihasilkan menampilkan tarian sumbawa dalam bentuk augmented reality dengan tiga tarian yang dilengkapi dengan pakai adat dari masing-asing tari serta instrumen pendukung. Pada laman web menampikan sejarah, musik pengiring, makna dari setiap gerakan dasar, informasi tarian, dan makna dari kostum tradisional yang digunakan. Dengan adanya aplikasi berbasis augmented reality diharapkan generasi muda dapat mempelajari dan mempraktikkan tarian Sumbawa dengan teknologi dan visual yang lebih menarik serta melestarikan tarian Sumbawa yang merupakan warisan kebudayaan.

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