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Precipitation and water discharge for internet of things based flood disaster prediction improvement Efendi, Rissal; Widiasari, Indrastanti R.
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp6773-6785

Floods are a major global problem affect communities and businesses. For these effects to be mitigated and emergency measures to be improved, accurate prediction is essential. Conventional flood prediction models frequently fail because the models ignore important hydrological elements like water discharge and instead solely use rainfall data. This limitation was addressed by the combination of rainfall and water discharge data on internet of things (IoT)-based technologies. It focuses on analyzing historical records from flood-prone areas in Semarang using gated recurrent unit (GRU) models. The findings demonstrate how effectively the GRU model performs when rainfall and water discharge factors are taken into account, resulting in very accurate and dependable predictions of flood events. Precision, Recall, and F1-score are evaluation metrics that demonstrate the accuracy on which the model determines flood emergency statuses. This study advances flood prediction methods and highlights the value of integrating internet of things data to improve preparedness and resilience against flood disasters.

Analisis Quality of Service (QoS) Jaringan Internet Pada Website Flexible-Learning Universitas Kristen Satya Wacana Tasik, Irianto Liling; Efendi, Rissal
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 1 (2024): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i1.757

In the era of increasingly advanced information and network technology, the need for communication and information exchange has become very important. Modern networks transfer data in a variety of applications such as voice, video, and data, which have different requirements in terms of speed, constraints, and service availability. Quality of Service (QoS) is a technology used to ensure that the Internet provides good and stable service quality to users. Wireshark is a network analysis tool used to monitor and analyze Internet network traffic. This research aims to analyze network quality when accessing the Satya Wacana Christian University Flexible-Learning website using Wireshark. QoS parameters such as throughput, delay, jitter, and packet loss are measured to evaluate network performance. The analysis results show that while throughput, delay, and jitter are relatively stable, the high packet loss rate indicates instability in data transmission. Therefore, network infrastructure improvements are needed to improve overall service quality

Integrasi Blockchain dan Keamanan Data untuk Meningkatkan Efisiensi dan Transparansi Sistem Logistik Global Nabila, Cheysha Restu; Efendi, Rissal
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 2 (2025): APRIL-JUNE 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i2.3277

The global logistics system currently faces complex challenges related to efficiency and transparency. To address these issues, integrating blockchain and data security has emerged as a promising solution. Blockchain, the foundational technology behind cryptocurrencies, provides the capability to record, verify, and secure transactions in a decentralized and transparent manner. This study aims to analyze the potential of integrating blockchain and data security to enhance efficiency and transparency in global logistics systems. The research employs a literature review approach, examining relevant studies on blockchain and data security applications within the global logistics context. The findings indicate that blockchain integration in global logistics can facilitate a more efficient supply chain by enabling transparency, real-time validation, and enhanced monitoring of logistics activities. Additionally, encrypted data security can mitigate security risks and reduce fraud, providing better protection against cyberattacks and data manipulation.

Design and Implementation of Load Balancing for Quality of Service Improvement Widiasari, Indrastanti Ratna; Efendi, Rissal
Jurnal Buana Informatika Vol. 15 No. 2 (2024): Jurnal Buana Informatika, Volume 15, Nomor 02, Oktober 2024
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

At the Information Technology Faculty, Satya Wacana Christian University, load balancing systems are implemented where the web server serves 500 users. This is to prevent server overload or downtime during simultaneous access to the web server. Test results indicate significant differences in CPU usage, request time, and bandwidth between load balancing and single servers. The use of load balancing is more effective than relying on a single server, as evidenced by test results. The CPU usage with load balancing is significantly lower, with a difference of up to 45% compared to a single server. The request time with load balancing is also slightly better, with only 21.5ms compared to 42ms for a single server. However, the difference in bandwidth between load balancing and a single server is not very significant. The highest bandwidth recorded on a single server is 182kb/s, while with load balancing it reaches 165kb/s.

Pengaruh Sistem E-Learning Terhadap Hasil Belajar Siswa Di Jurusan Teknik Jaringan Komputer Dan Telekomunikasi (TJKT) Soterio, Stephan; Efendi, Rissal
Wahana Pendidikan Vol 12, No 1 (2025): Januari
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/jwp.v12i1.14967

Penelitian ini dilaksanakan di SMK Telekomunikasi Tunas Harapan Kabupaten Semarang, bertujuan untuk mendeskripsikan pengaruh sistem e-learning terhadap kompetensi afektif siswa. Penelitian ini menggunakan metode penelitian kuantitatif dengan desain penelitian pra-eksperimental, dilaksanakan dengan memanfaatkan platform e-learning yang telah di implemetasikan disekolah. Subjek pada penelitian uji eksperimen penggunaan e-learning ini yaitu siswa kelas XE SMK Telekomunikasi Tunas Harapan Kabupaten Semarang. Objek dalam penelitian ini adalah hasil belajar siswa kelas XE TJKT. Jenis e-learning yang digunakan ialah e-moodle atau “Modulator Object Oriented Dynamic Learning”. Penelitian ini menggunakan uji paired sample t-test dengan teknik analisis data Uji Normalitas dan Uji Homogenitas, dan analisis deskriptif guna untuk memaparkan dan menggambarkan data penelitian mencakup jumlah data penelitian, nilai maksimal-minimal serta nilai rata-rata. Penelitian di uji dari data yang diambil dengan total sampling 34 siswa partisipan. Untuk menguji apakah penelitian ini valid atau tidak setelah penerapan e-learning peneliti menguji penelitian ini dengan uji normalitas yang telah dilakukan dengan hasil uji statistik data Asymp.Sig pretest dan posttest berdistribusi normal dengan (2-tailed = 0,25 dan 0,27) ≥ ½ α (sigma) (0,05) maka data berdistribusi normal dan uji homogenitas diperoleh p-value (sig) = > 0,05, disimpulkan bahwa varians data hasil belajar siswa adalah homogen.

Integrasi Blockchain dan Keamanan Data untuk Meningkatkan Efisiensi dan Transparansi Sistem Logistik Global Nabila, Cheysha Restu; Efendi, Rissal
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 2 (2025): APRIL-JUNE 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i2.3277

The global logistics system currently faces complex challenges related to efficiency and transparency. To address these issues, integrating blockchain and data security has emerged as a promising solution. Blockchain, the foundational technology behind cryptocurrencies, provides the capability to record, verify, and secure transactions in a decentralized and transparent manner. This study aims to analyze the potential of integrating blockchain and data security to enhance efficiency and transparency in global logistics systems. The research employs a literature review approach, examining relevant studies on blockchain and data security applications within the global logistics context. The findings indicate that blockchain integration in global logistics can facilitate a more efficient supply chain by enabling transparency, real-time validation, and enhanced monitoring of logistics activities. Additionally, encrypted data security can mitigate security risks and reduce fraud, providing better protection against cyberattacks and data manipulation.

Efektivitas Penggunaan E-Modul Pelajaran TIK Terhadap Peningkatan Motivasi Belajar Siswa Kelas X SMA Negeri 15 Kabupaten Kepulauan Tanimbar Ferdy Kowarin, Hansen; Efendi, Rissal
Petik: Jurnal Pendidikan Teknologi Informasi Dan Komunikasi Vol. 11 No. 1 (2025): Volume 11 No 1 Maret 2025
Publisher : Pendidikan Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31980/petik.v11i1.1657

Abstrak Peneliti menemukan bahwa di SMA Negeri 15 Kabupaten Kepulauan Tanimbar (KKT) memiliki masalah dalam pembelajaran yaitu yang pertama, kurangnya motivasi belajar siswa dalam memahami pembelajaran Teknologi Informasi dan Komunikasi TIK, ke dua daya tarik dari media pembelajaran yang digunakan guru masih kurang. Penelitian ini bertujuan untuk menganalisis keefektivitasan penggunaan e-modul pelajaran Teknologi Informasi dan Komunikasi (TIK) pada peningkatan motivasi belajar siswa kelas X SMA Negeri 15 Kabupaten Kepulauan Tanimbar (KKT). Pendekatan yang digunakan dalam penelitian ini yaitu deskriptif kuantitatif dan rancangan penelitiannya adalah Pretest-Posttest Non-Equivalent Control Group, teknik analisis data yang digunakan adalah uji normalitas, uji homogenitas, uji independent sampel T-test atau uji banding, uji rata-rata (mean) motivasi belajar siswa dan uji N-Gain. Populasi dalam penelitian ini adalah seluruh siswa kelas X SMA Negeri 15 KKT yang berjumlah 34 Orang, yang dibagi kedalam kelompok kelas X2 sebagai kelas perlakuan dan kelas X kelas kontrol, siswa dengan masing-masing kelas berjumlah 17 siswa. Hasilnya kelas perlakuan pada diagram batang yaitu untuk indikator perhatian 85.00, indikator relevansi 80.00, indikator keyakinan 90.00, dan indikator kepuasan 95.00 dan juga di perjelas melalui hasil uji independent T-test yaitu 0.001 < 0.05 dan hasil uji nilai rata-rata post-test pada kelas perlakuan (X2) 89.41, kelas kontrol (X1) 67.65. Sedangkan untuk rata-rata N-Gain pada kelas perlakuan (X2) sebesar 72.08 dan kelas kontrol (X1) sebesar 20.43. Berdasarkan hal tersebut, maka dapat disimpulkan bahwa media pembelajaran e-modul pelajaran TIK efektif dalam meningkatkan motivasi belajar terhadap siswa Kelas X SMA Negeri 15 KKT. Kata Kunci: Efektivitas, E-Modul, Motivasi Belajar Siswa Abstract Researchers found that at SMA Negeri 15 Tanimbar Islands Regency (KKT) has problems in learning, namely first, lack of student motivation to learn in understanding ICT and Information Technology learning, second, the attractiveness of the learning media used by teachers is still lacking. This study aims to analyze the effectiveness of the use of e-modules in Information and Communication Technology (ICT) lessons in increasing the learning motivation of students in grade X of SMA Negeri 15 Tanimbar Islands Regency (KKT). The approach used in this study is quantitative descriptive and the research design is Pretest-Posttest Non-Equivalent Control Group, the data analysis techniques used are normality test, homogeneity test, independent test of T-test sample or comparative test, mean test of student learning motivation and N-Gain test. The population in this study is all students of class X of SMA Negeri 15 KKT which is 34 people, which is divided into class X2 group as a treatment class and class X as a control class, students with a total of 17 students in each class. The results of the treatment class on the bar chart are for the attention indicator 85.00, the relevance indicator 80.00, the confidence indicator 90.00, and the satisfaction indicator 95.00 and also clarified through the results of the independent T-test which are 0.001 < 0.05 and the results of the post-test average score test in the treatment class (X2) 89.41, the control class (X1) 67.65. Meanwhile, the average N-Gain in the treatment class (X2) was 72.08 and the control class (X1) was 20.43. Based on this, it can be concluded that the ICT lesson e-module learning media is effective in increasing learning motivation for students of CLASS X SMA Negeri 15 KKT. Keyword: Effectiveness, E-Modules, Student Learning Motivation

Pengembangan Sistem Deteksi Kualitas Udara Berbasis Sensor IoT Menggunakan Fitur Notifikasi Telegram di Terminal Tingkir, Salatiga Pariama, Alberth; Efendi, Rissal
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 2 (2025): Mei
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v6i2.1384

Climate change and air pollution are two of the world’s most pressing issues that have a major impact on ecosystems and human health. The aim of this study is to create an internet of things-based air quality monitoring system that can identify pollutants such as CO2, NO2, and PM2.5 in real-time. The system that notifies users via a mobile application such as Telegram once the air quality exceeds a certain threshold is built with MQ-135 and DHT11 sensors. The study was conducted through an experiment with a development approach. Literature review, system design, prototyping, and performance evaluation are all part of this methodology. The results of the study show that the system can help monitor air quality and increase public awareness about the environment. Therefore, this study enhances efforts to reduce air quality pollution, especially in Indonesian cities.

PREDIKSI RISIKO DROP OUT MAHASISWA MENGGUNAKAN MODEL MACHINE LEARNING BERBASIS DATA AKADEMIK (Studi Kasus : Universitas XYZ) Tumbilung, Chresto Friedrich; Efendi, Rissal
JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI Vol. 16 No. 2 (2025): September
Publisher : UNIVERSITAS STEKOM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtikp.v16i2.1257

Higher education is crucial for developing competitive human resources, yet the issue of student dropout (DO) remains a significant challenge for institutions. This study aims to develop a predictive model for identifying students at risk of dropout using machine learning techniques. By analyzing academic data, including Grade Point Averages (GPA), course loads, attendance rates, and failure rates, the research employs three machine learning algorithms: Decision Tree, Naive Bayes, and K-Nearest Neighbor (KNN). The results indicate that the Decision Tree model outperforms the others, achieving a perfect accuracy of 100% in classifying students as either "Graduated" or "Dropout." Naive Bayes also shows strong performance with 95% accuracy, particularly excelling in identifying actual dropout cases. Conversely, KNN exhibits the lowest effectiveness. The findings suggest that implementing the Decision Tree model can significantly enhance early detection and intervention strategies for at-risk students, ultimately improving academic management and student retention rates.

A Hybrid SMOTE-PSO-LSTM-GRU Model for Enhanced Android Malware Detection Efendi, Rissal; R. Widiasari, Indrastanti
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 11 No. 3 (2025): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v11i3.30774

As the use of Android devices increases, malware threats are becoming increasingly critical and often undetected by conventional methods due to data imbalance and dynamic behavior in network traffic and application activities. This study aims to answer the question of whether a hybrid deep learning model equipped with optimization and data balancing techniques can significantly improve the performance of malware detection. We propose a novel architecture that integrates SMOTE to balance the class distribution by oversampling minority malware samples, an LSTM-GRU network to learn sequential behavioral patterns, and Particle Swarm Optimization (PSO) to optimize model hyperparameters. The model is trained using a real-world dataset that includes labeled network and application activity logs. Compared with baseline models such as standard LSTM and GRU, our approach shows significant performance improvements, with an F1 score of 98.3%, an accuracy of 98.8%, a precision of 98.1%, and a recall of 98.5%. These results indicate that the proposed model not only addresses the major challenges in Android malware detection but also has strong potential for application in real-world mobile security systems.

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