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Sirojul Hadi
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Jurnal Bumigora Information Technology (BITe)
Published by Universitas Bumigora
ISSN : 26854066     EISSN : 26854066     DOI : https://doi.org/10.30812/bite
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering
Jurnal Bumigora Information Technology (BITe) is one of the journals owned at Bumigora University which is managed by the Department of Computer Science. This journal is intended to provide publications for academics, researchers and practitioners who wish to publish research in the field of information technology and computer science. BITe Journal is published in 2 (two) periods, namely in June and December. The focus and scope of the BITe journal are Fuzzy Logic Control, Internet of Things, Wireless Sensor Network, Artificial Intelligence, Machine Learning and Deep Learning, Business Intelligence, Mobile Computing and Application, Data Mining, Cloud and Grid Computing, Computer Network and Security, Computer Vision, Geographical Information System (GIS), Semantic Web
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 152 Documents
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Integrasi Basis Data Properti Menggunakan Metode Schema Matching Dengan Pendekatan Linguistic dan Constraint Hariri, Muhammad; Triwijoyo, Bambang Krismono; Martono, Gallih Hendro
Jurnal Bumigora Information Technology (BITe) Vol. 7 No. 1 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v7i1.4872

Abstract

Background: The rapid development of technology has driven progress across various sectors, including the property industry in Indonesia. However, property data integration on Lombok Island still faces challenges due to the diversity of attribute naming, which hinders efficient information retrieval.Objective: This study aims to integrate four property databases (Saduthama, Salva, SJP, and Garden View) using a schema matching method based on linguistic and constraint approaches.Methods: The linguistic approach is used to identify similarities between attributes, even when their names differ, using the Bigram technique, which proved effective in identifying attribute similarities with a threshold of 0.7. Meanwhile, the constraint approach evaluates the compatibility of attributes based on additional criteria such as data type, attribute length, null values, and uniqueness, ensuring that the integrated attributes work compatibly. The integration process includes preprocessing, generalization, and attribute matching.Result: The evaluation results show precision (P), recall (R), and F-measure of 90%, with an average accuracy of 84%.Conclusion: This result outperforms previous studies that achieved 100% precision, 60% recall, and 75% F-measure.
Perbandingan Metode Berbasis Decision Tree dalam Deteksi Penyakit Paru-Paru Kurniawati, Lely; Priyanto, Dadang; Ningsih, Neny Sulistia; Syahrir, Moch; Rismayati, Ria
Jurnal Bumigora Information Technology (BITe) Vol. 7 No. 1 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v7i1.4909

Abstract

Background: Lung disease is a leading cause of death globally, with more than 4 million cases each year, including 500,000 new cases in Indonesia, most of which are detected at an advanced stage.Objective: This study aims to compare the performance of three decision tree algorithms, XGBoost, C4.5, and Random Forest, in detecting lung disease and to determine the best method based on evaluation metrics.Methods: A total of 30,000 data samples from Kaggle were processed through a cleaning stage using the IQR method, categorical attribute coding, and data division into 80% for training and 20% for testing. The classification models used include XGBoost, C4.5, and Random Forest. Model performance evaluation used a confusion matrix, accuracy, precision, recall, and F1-score.Result: The results showed that the C4.5 algorithm had the best performance with an accuracy of 94.33% and zero false negatives. XGBoost followed with an accuracy of 93.18%, while Random Forest was the lowest (90.07%).Conclusion: These findings indicate that C4.5 has great potential in an accurate early detection system, helping to reduce the risk of misdiagnosis, especially in false negative cases, and supporting clinical decision making in health facilities. 
Classification of Learning Styles of Junior High School Students Using Random Forest & XGBoost Algorithm Christine Eirene; Dian Syafitri; Neny Sulistianingsih; Khasnur Hidjah; Hairani Hairani
Jurnal Bumigora Information Technology (BITe) Vol. 7 No. 1 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v7i1.4913

Abstract

  Background: Accurately identifying students' learning styles so that educators can adjust their teaching methods accordingly is a challenge in the field of education. However, the application of Machine Learning for learning style classification has not yet been implemented in schools in Mataram City. Objective: This study aims to classify the learning styles of students at Junior high school (SMP) Negeri 2 Mataram using Random Forest and XGBoost algorithms.  Method: Data were collected through questionnaires completed by students in grades 7, 8, and 9. The results of data exploration (EDA) show data imbalance in the collected classes. Result: These results indicate that both algorithms performed well in classifying learning styles, with XGBoost showing slightly better performance. However, the accuracy obtained is not yet optimal, likely due to the limited dataset size. To address data imbalance, the SMOTE technique was applied. Initial evaluation showed that both XGBoost and Random Forest achieved an accuracy of 80%. After Hyperparameter Tuning, the accuracy of XGBoost increased to 84%, while Random Forest reached 82%. Conclusion: This study contributes to the application of Machine Learning in the education sector and highlights the need for further research to enhance model performance.  
Analisis Kerentanan SQL Injection, Cross Site Scripting, Dan Insecure Direct Object Reference Pada Website Perguruan Tinggi Di Nusa Tenggara Barat Menggunakan Metode Pengujian Penetrasi Dhira Wahyu Febrian; Raphael Bianco Huwae; Ahmad Zafrullah Mardiansyah
Jurnal Bumigora Information Technology (BITe) Vol. 7 No. 1 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v7i1.5032

Abstract

Background: In the digital era, cybersecurity is important for universities in protecting academic information and user data. The focus of this research is to identify and analyze the security vulnerabilities of higher education websites in West Nusa Tenggara against three types of attacks, namely SQL Injection, Cross Site Scripting (XSS), and Insecure Direct Object Reference (IDOR), which can compromise the integrity of higher education data and information systems.Objective: This research aims to evaluate the level of vulnerability and severity of the risk of the three types of attacks on the websites of higher education institutions.Methods: This research uses penetration testing methods, and assesses the severity of vulnerabilities based on the Common Vulnerability Scoring System (CVSS) version 3.1.Result: This research results show that 50% of the ten college websites tested are vulnerable to XSS attacks, 30% to SQL Injection, and 20% to IDOR. The highest severity was found in the SQL Injection vulnerability with a CVSS score of 9.0 critical category.Conclusion: The implications of the results of this study indicate that higher education institutions need to immediately strengthen system security with strict input validation, WAF implementation, and adequate authorization mechanisms to prevent future exploitation of similar vulnerabilities.
Revolusi Sistem Transportasi Cerdas: AODV Berbasis Learning Automata untuk Peningkatan Komunikasi V2V di Jalan Bebas Hambatan Bryan Jonathan Hutapea; Ketut Bayu Yogha Bintoro; Helna Wardhana
Jurnal Bumigora Information Technology (BITe) Vol. 7 No. 1 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v7i1.5131

Abstract

Backgroud: Vehicle-to-vehicle communication has become a crucial element in the development of intelligent transportation systems. However, conventional routing protocols face limitations in coping with dense and dynamic traffic conditions. Objective: The objective of this study is to improve communication efficiency between vehicles by modifying an on-demand routing protocol using a learning automata approach. Method: This study employed a simulation method with traffic modeling using traffic modeling software and network simulation tools, based on data from highways in the Soekarno-Hatta International Airport area. Result: The results of this study show that the developed protocol increases the packet delivery ratio to 87.7% and reduces latency by 6.5%. Conclusion: The conclusion of this study is that the application of learning automata in vehicle routing enhances communication reliability and supports the implementation of a more adaptive and efficient transportation system.  
Penerapan Algoritma Naive Bayes untuk Prediksi Kerontokan Rambut Yoraeni, Ani; Rakhmah, Syifa Nur
Jurnal Bumigora Information Technology (BITe) Vol. 7 No. 1 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v7i1.5201

Abstract

 Background: Hair loss is a common problem that can affect a person’s self-confidence. Early prediction of the risk is important to help with more appropriate treatment.Objective: This study aims to apply the Na¨ıve Bayes algorithm to predict hair loss based on personal data and clinical factors such as age, gender, stress levels, hormones, and family history.Methods: The Na¨ıve Bayes method was chosen because it efficiently handles categorical data. The data used in this study were obtained from a public dataset available on the Kaggle platform, which contains individual information about the risk of hair loss.Result: The developed prediction model can classify risks based on various causal factors, but its performance is still low with an accuracy of 55.5%, AUC 0.593, and MCC 0.113.Conclusion: These results indicate that the model is unreliable for practical applications. The implication is that this system can be the basis for further development with more complex algorithms, the addition of clinical features, and stronger validation so that it can be applied effectively in medical contexts and personal consultations. 
Optimalisasi Model Bahasa dan Sistem Ekonomi Berbasis Teks dengan Proximal Policy Optimization: Studi Kasus dalam NLP Modern Darmawan, Irwan; Ramadhani, Nilam; Nazir Arifin, Mohammad; -, Ubaidi; Puspa Dewi, Nindian; Innuddin, Muhammad
Jurnal Bumigora Information Technology (BITe) Vol. 7 No. 1 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v7i1.5222

Abstract

Background: This study investigates the use of the Proximal Policy Optimization (PPO) algorithm in two text-based case studies: alignment of large language models (LLMs) with human preferences and dynamic pricing based on customer reviews. In the LLM case, PPO combined with preference-based learning significantly improves alignment, BLEU, and human-likeness scores.Objective: This research aims to evaluate PPO’s effectiveness in text-based decision-making through these two cases.Methods: The method employed is reinforcement learning experimentation using the PPO approach. For the LLM case, PPO is integrated with preference learning to enhance alignment, BLEU, and human-like output. Meanwhile, in the economic scenario, PPO produces adaptive pricing strategies with high accuracy or low Mean Absolute Error (MAE) and the best cumulative rewards, outperforming the A3C and DDPG algorithms. Cross-validation and ablation studies assessed PPO’s generalization capability and the contribution of reward components, clipping, and exploration strategies.Result: The findings demonstrate that PPO excels across distinct domains and offers a stable and efficient solution for text-based tasks.Conclusion: The findings confirm its flexibility for various NLP applications and intelligent decision-making systems 
Otomasi Manajemen dan Pengawasan Linux Container (LCX) Pada Proxmox VE Menggunakan Ansible Pratama, Muh Akromi Arya; Hariyadi, I Putu
Jurnal Bumigora Information Technology (BITe) Vol. 3 No. 1 (2021)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v3i1.807

Abstract

In the development of internet service technology, it has become a major requirement as a means of communication and exchanging information. Especially in the field of education such as elementary schols, internet facilities are very much needed where the users are administrative staff, teachers, students via the internet can access various knowledge needed quickly, so that it can simplify the learning process. Therefore, the bandwidth sharing system or it can be called bandwidth management must be in accordance with the conditions of the network service to be applied and bandwidth management is indispensable for multi-service networks, because the more and more varied applications that can be served by a network have an effect on link usage. In the network. The method in this research uses library research and the implementation uses the Hierarchical Token Bucket method, which is an application that function to regulate the distribution of bandwidth. The purpose of this analysis is to provide a bandwidth management system to make a fair distribution for users connected to the network. The results showed that the Hierarchicak Token Bucket method can regulate bandwidth usage for each client when downloading, uploading, streaming and browsing
Rancang Bangun Sistem Penyiraman Otomatis Berbasis Internet of Things Pada Tanaman Hias Sirih Gading Wulandari, Putri Ayu; Rahima, Phyta; Hadi, Sirojul
Jurnal Bumigora Information Technology (BITe) Vol. 2 No. 2 (2020)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v2i2.886

Abstract

Kemajuan teknologi dari waktu ke waktu telah berkembang dengan pesat sehingga dapat memberikan banyak kemudahan bagi manusia untuk melakukan pekerjaan sehari-hari seperti melakukan perawatan pada tanaman hias yang berada di dalam rumah. Salah satu contoh tanaman hias yang ada dirumah yaitu tanaman sirih gading. Untuk merawat tanaman diperlukan air untuk melakukan penyiraman. Penyiraman yang teratur merupakan rutinitas penting di lakukan untuk menjaga tanaman terus tumbuh dan berkembang. Pekerjaan yang dilakukan secara rutin dan terjadwal dapat dilakukan dengan memanfaatkan teknologi sensor dan internet of things (IoT) untuk melakukan kontrol dan pemantauan. Teknologi tersebut dapat digunakan untuk membangun sistem yang berfungsi untuk melakukan perawatan dan penyiraman pada tanaman hias sirih gading. IoT merupakan sebuah sistem yang memungkinkan setiap device dapat berkomunikasi, melakukan kontrol dan pemantauan melalui jaringan internet. Hasil yang dicapai setelah penelitian ini dilakukan yaitu dihasilkan sebuah sistem penyiraman otomatis berbasis internet of things dengan menggunakan NodeMCU yang terintegrasi dengan Telegram untuk melakukan perawatan dan penyiraman pada tanaman hias sirih gading. Hasil dari penelitian ini yaitu suhu lingkungan pada tanaman berada pada rentang 24oC–29oC dan rata-rata error pengukuran suhu menggunakan sensor DHT11 yaitu sebesar 2,07%. Pengukuran kelembaban tanah pada tanaman hias sirih gading berada pada rentang 47%-65%.
Indonesia Perancangan Jaringan Komputer untuk Sekolah Dasar Dengan Sistem Manajemen Bandwidth Hierarchical Token Bucket Simbolon, Jesika Marsaulina; Harafani, Hani; Astuti, Rachmawati Darma
Jurnal Bumigora Information Technology (BITe) Vol. 3 No. 1 (2021)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v3i1.966

Abstract

In the development of internet service technology, it has become a major requirement as a means of communication and exchanging information. Especially in the field of education such as elementary schols, internet facilities are very much needed where the users are administrative staff, teachers, students via the internet can access various knowledge needed quickly, so that it can simplify the learning process. Therefore, the bandwidth sharing system or it can be called bandwidth management must be in accordance with the conditions of the network service to be applied and bandwidth management is indispensable for multi-service networks, because the more and more varied applications that can be served by a network have an effect on link usage. In the network. The method in this research uses library research and the implementation uses the Hierarchical Token Bucket method, which is an application that function to regulate the distribution of bandwidth. The purpose of this analysis is to provide a bandwidth management system to make a fair distribution for users connected to the network. The results showed that the Hierarchicak Token Bucket method can regulate bandwidth usage for each client when downloading, uploading, streaming and browsing. Keyword: Bandwidth, HTB, Design, Network, Computer.

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