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All Journal ComEngApp : Computer Engineering and Applications Journal Transmisi: Jurnal Ilmiah Teknik Elektro PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal technoscientia Prosiding SNATIF Teknika: Jurnal Sains dan Teknologi Prosiding Semnastek Scientific Journal of Informatics Proceeding SENDI_U SMATIKA Jurnal Ampere JURNAL NASIONAL TEKNIK ELEKTRO PROtek : Jurnal Ilmiah Teknik Elektro Sistemasi: Jurnal Sistem Informasi JETT (Jurnal Elektro dan Telekomunikasi Terapan) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JURNAL MEDIA INFORMATIKA BUDIDARMA VOLT : Jurnal Ilmiah Pendidikan Teknik Elektro Indonesian Journal of Artificial Intelligence and Data Mining INOVTEK Polbeng - Seri Informatika Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal RESISTOR (Rekayasa Sistem Komputer) Patria Artha Technological Journal EDUMATIC: Jurnal Pendidikan Informatika Jurnal Qua Teknika Jurnal Fokus Elektroda : Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali Building of Informatics, Technology and Science Jurnal Informatika dan Rekayasa Elektronik Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) JURNAL TEKNOLOGI TECHNOSCIENTIA Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) Fokus Elektroda: Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali) Jurnal Pendidikan dan Teknologi Indonesia Aptekmas : Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmiah Teknik Elektro Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) Emitor: Jurnal Teknik Elektro INOVTEK Polbeng - Seri Informatika Smatika Jurnal : STIKI Informatika Jurnal ITEJ (Information Technology Engineering Journals)
Sopian Soim, Sopian
Politeknik Negeri Sriwijaya
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A Comparative Study of Machine Learning Classifiers with SMOTE for Predicting Purchase Intention Khairunnisa, Khairunnisa; Soim, Sopian; Lindawati, Lindawati
Building of Informatics, Technology and Science (BITS) Vol 7 No 2 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i2.7615

Abstract

The rapid growth of e-commerce has made it increasingly important for online platforms to understand user behavior, particularly in predicting purchasing intention. This study examines the implementation of three machine learning models: Logistic Regression, Random Forest, and Gradient Boosting, to classify purchase intention using real transaction session data. One of the primary obstacles confronted in this investigation is the matter of class imbalance found in the dataset, where 10422 records indicate no purchase while only 1908 indicate a completed purchase. This disparity may result in a biased model performance that prioritizes the dominant class and limits the ability to accurately detect minority class behavior, which in this case is the actual purchase. To resolve this matter, During the data preprocessing phase, the Synthetic Minority Over-sampling Technique (SMOTE) was implemented. Accuracy, precision, recall, and F1-score metrics were implemented to assess each model's functionality. The results indicate that following the implementation of SMOTE, the Random Forest model attained the best accuracy of 93%, succeeded by Gradient Boosting at 90% and Logistic Regression with 84%. These findings demonstrate that the use of SMOTE significantly improves model sensitivity and balance. This study provides useful insights into designing fairer and more effective predictive systems in the field of e-commerce.
Implementasi Layanan untuk Pesan Singkat Menggunakan Perangkat Universal Software Radio Pheripheral (USRP) B210 pada Standar Komunikasi 3GPP Berbasis 4G Anugraha, Nurhajar; Seliana, Imalda; Soim, Sopian
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 3 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i3.41660

Abstract

Communication technology continues to develop rapidly, now 4G has become a network standard used in various countries. 4G networks offer higher data speeds, lower latency, and greater capacity compared to previous networks. Now, we can exchange information and establish relationships with others without having to meet in person. However, in remote areas and areas with limited networks, there are still problems in using these celluler phones that are poorly understood by people living in remote areas or areas that are not covered by celluler phone networks. For example, the use of very simple cellular phone facilities such as Short Message Service (SMS). OpenBTS is a new part of BTS technology that is very economical both in terms of funds and resources because openBTS is based on opensource software so that it is easily available and anyone can implement this openBTS, and can provide services to communicate such as Short Message Service (SMS) or short messages and can be used as a substitute for telephone facilities in the event of signal interference. For this reason, in this study, the implementation of services for short messages using the Universal Software Radio Peripheral (USRP) B210 device on 4G-based 3GPP communication standards. The hardware used is USRP B210.
Desain dan Pengembangan Website untuk Mendeteksi Malware Menggunakan Framework Flask yang Diintegrasikan dengan Machine Learning Ciksadan, Ciksadan; Soim, Sopian; Jami, Nurlita
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 3 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i3.42003

Abstract

One of the most widely used media for information dissemination is the website. A dynamic and informative website will make it easier for users to access information. Web development often requires complex technologies. One method that can simplify the development process is using the Flask framework, which offers flexibility and freedom to developers. A website must also have functionality to be useful; one current issue is the increasing number of malware file cases. Therefore, there is a need for a medium that can analyze a file. However, currently, there are limited services available for this purpose. This research aims to build a website that detects malware files using the Flask framework integrated with machine learning for malware file detection. Through this research, a website with five informative menus has been developed, featuring a dynamic and easily accessible interface with a malware file detection capability reaching 99% accuracy.
Pengembangan Model Support Vector Machine untuk Meningkatkan Akurasi Klasifikasi Diagnosis Penyakit Jantung Fahrudin, Gantar Fitra; Suroso, Suroso; Soim, Sopian
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 3 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i3.42254

Abstract

Heart disease is a serious health issue that leads to high mortality risk worldwide. Contributing factors include high cholesterol, diabetes, and high blood pressure. Therefore, early prediction of heart disease is a crucial initial step to reduce mortality risk. This paper proposes a new heart disease classification model based on the Support Vector Machine (SVM) algorithm to enhance disease detection performance. To improve diagnostic accuracy, we apply feature selection techniques and grid search. The performance of the enhanced model is validated by comparing it with a simple model using a confusion matrix. The enhanced model achieves an accuracy of 96.56%, showing an improvement of 8.91% over the previous model, which had an accuracy rate of only 87.65%. Additionally, the number of features used is reduced from 14 to 8, decreasing the computational load from 100% to about 32%. These results indicate that the enhanced SVM provides better and more efficient performance compared to other methods in heart disease classification
Monitoring Kapal Menggunakan Automatic Identification System(AIS) Dengan RTL-SDR dan Low Noise Amplifier (LNA) Sari, Rani Purnama; Lindawati, Lindawati; Soim, Sopian
PROtek : Jurnal Ilmiah Teknik Elektro Vol 9, No 2 (2022): Protek : Jurnal Ilmiah Teknik Elektro
Publisher : Program Studi Teknik Elektro Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/protk.v9i2.4691

Abstract

Automatic Identification System (AIS) is a ship transponder that uses MMSI data, speed, position, destination, ship type, and size to locate, track, and monitor ships. Only Vessel Traffic Services (VTS) and a few other agencies can be supervised presently. This is one of the issues that must be resolved. To resolve this issue, hardware that can receive AIS signals at 161.975 MHz and 162.025 MHz and convert them into information signals is required. RTL-SDR is hardware capable of receiving signals in the frequency range of 25-1700 MHz. Its antenna is used to achieve maximum signal reception by establishing a direct line of sight to the AIS data source. Yagi antennas can only receive signals from a single direction, the front. Low Noise Amplifier (LNA) is also used in order to optimize the signal received by the antenna. The signal can be processed and decoded using SDR-Sharp and AISMon to provide data that can be plotted on OpenCPN. The performance of the AIS data decoding process is controlled by the strength and weakness of the signal that the RTL-SDR receiver can receive. Therefore, the antenna and receiver must be placed in a clear line of sight (LOS) with the ship's AIS transponder emitting source. It is envisaged that this monitoring system would make it easier to monitor ships in real-time
Rancang Bangun Monitoring Lokasi Pesawat Menggunakan ADS-B dengan RTL-SDR dan Raspberry Pi Diraputra, M Yoga Azto; Soim, Sopian; Sarjana, Sarjana
PROtek : Jurnal Ilmiah Teknik Elektro Vol 8, No 2 (2021): Protek : Jurnal Ilmiah Teknik Elektro
Publisher : Program Studi Teknik Elektro Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/protk.v8i2.3233

Abstract

Abstract — Automatic Dependent Surveillance Broadcast (ADS-B) is a surveillance technology that provides information on aircraft in the air in the form of 24 bit ICAO aircraft address, ident or squawk, massage, altitude, nationality, speed, longitude, track and heading. The problem faced now is that surveillance can only be done with a web and android-based application on FlightRadar24 so that if the user wants to display more aircraft information, the user is required to pay a subscription. To overcome this problem, hardware is needed that can receive ADS-B signals with a frequency of 1090 MHz and can translate them into information signals. RTL-SDR is hardware that can receive signals with a frequency range from 25 MHz - 1700 MHz, by applying the Raspberry Pi it is used to configure RTL-SDR as a receiver capable of receiving information from ADS-B signals. To get the maximum reception, an omnidirectional antenna is needed that can receive signals from all directions. With this system, it is expected to make it easier to monitor aircraft in real time and processing ADS-B signal data is determined by the strength and weakness of the signal that can be received by RTL-SDR.
Performance Improvement of Fake News Detection Models Using Long Short-Term Memory Hyperparameter Optimization Lindawati, Lindawati; Ramadhan, Muhammad Fadli; Soim, Sopian; Novianda, Nabila Rizqi
Scientific Journal of Informatics Vol 10, No 3 (2023): August 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v%vi%i.45420

Abstract

Purpose: The proposed model was developed based on prior research that distinguished between fake and real news using a deep learning-based methodology and an LSTM neural network, with a model accuracy of 99.88%. This study uses hyperparameter tuning techniques on a Long Short-Term Long Memory (LSTM) neural network architecture to improve the accuracy of a fake news detection model.Methods: To improve the accuracy of the fake news detection model and optimize the model from previous research, this study uses the hyperparameter tuning technique on models with Long Short-Term Memory (LSTM) neural network architecture. For this technique, three different types of experiments, hyperparameter tuning on the LSTM layer, Dense layer, and Optimizer, were conducted to obtain the best hyperparameters in each layer of the model architecture and the model parameters proposed. The fake and real news dataset, which has also been used in earlier studies, was used in this study.Results: The proposed model could detect fake news with a high accuracy of 99.97%, surpassing the previous research models with an accuracy of 99.88%.Novelty: The novelty of this study was the hyperparameter tuning technique on different layers of the LSTM neural network to optimize the fake news detection model. The research aims to improve upon previous approaches and increase the accuracy of the model. 
Evaluasi Kinerja Filter Finite Impulse Response (FIR) Menggunakan Window Kaiser dan Hamming pada Komunikasi Li-Fi Dalam Ruangan Raihanah, Adinda; Soim, Sopian; Lindawati, Lindawati
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 11 (2025): JPTI - November 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.1174

Abstract

Keterbatasan spektrum radio akibat padatnya penggunaan perangkat nirkabel memicu kebutuhan akan inovasi teknologi komunikasi yang efisien dan hemat energi. Light Fidelity (Li-Fi) hadir sebagai solusi dengan memanfaatkan spektrum cahaya tampak sebagai media transmisi. Teknologi ini menyediakan kecepatan transfer data yang lebih cepat dan efisien dalam penggunaan energi karena dapat diintegrasikan langsung dengan sistem pencahayaan LED. Penelitian ini berfokus pada analisis performa Li-Fi dari segi filter Finite Impulse Response (FIR) menggunakan jenis window Kaiser dan Hamming. Kedua jenis window ini diuji untuk menganalisis Bit Error Rate (BER), Signal-to-Noise Ratio (SNR), dan bentuk eye diagram pada jarak 1 hingga 6 meter menggunakan simulasi MATLAB untuk berbagai bit rate. Hasil simulasi menunjukkan BER rendah pada jarak 1 dan 1.5 meter, dengan nilai 2 x . Untuk SNR pada jarak 1 meter, window Kaiser menghasilkan nilai 17 dB, sedangkan Hamming nilai 15 dB. Bentuk eye diagram pada jarak 1 meter menunjukkan bukaan lebar untuk kedua window, mengindikasikan kualitas sinyal yang baik. Dari hasil simulasi, dapat disimpulkan bahwa penggunaan window Kaiser memberikan performa yang lebih baik dibandingkan Hamming. Studi ini memberikan kontribusi signifikan dalam pengembangan teknologi komunikasi nirkabel yang lebih handal dan efisien.
Rancang Bangun Sistem Peringatan Dini Bencana Hidrometeorologi Berbasis Internet of Thing (IoT) Di BMKG Nakiatun Niswah; Suroso Suroso; Sopian Soim
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 11 No 02 (2021): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v11i02.593

Abstract

A hydrometeorological disaster is a disaster that is influenced or its impact is triggered by weather and climate conditions with various parameters. For example, increased rainfall, extreme temperatures, extreme weather such as heavy rain accompanied by strong winds and lightning or lightning, and so on. Hydrometeorological Disaster Early Warning System is a system that serves to provide early warnings for hydrometeorological disasters in the form of pop ups that will be sent via Gmail and also view maps of hydrometeorological disaster prone points and provide information on roads in Palembang that are affected by hydrometeorological disasters. There are also several additional features that have been integrated from the official website Radar.cuacasumsel.com owned by BMKG Palembang. These features include hot spots, 00 UTC Wind analysis, 12 UTC analysis, Rain potential satellite, and Himawari satellite. Where the system can be displayed via a mobile phone or computer that is connected to the internet network through a website in real time based on the Internet of Things. The website will use MYSQL, PHP, CSS, JavaScript, JASON and GIS languages. Keywords: Internet of Thing (IoT), Early Warning System, Gmail, Website, Maps.
Implementation of Ethereum-Based Blockchain Technology for ADS-B Data Security and Validation Kgs Muhammad Farhan Rabbaniansyah; Lindawati Lindawati; Sopian Soim
ITEJ (Information Technology Engineering Journals) Vol. 11 No. 1 (2026): June
Publisher : Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/itej.v11i1.271

Abstract

Automatic Dependent Surveillance–Broadcast (ADS-B) has significantly enhanced air traffic monitoring by enabling real-time broadcasting of aircraft positions and identifiers. However, it is intrinsically susceptible to spoofing, replay, and tampering attacks because to its lack of cryptographic protections. This paper introduces a blockchain-based ADS-B validation system for safe, decentralized data authentication that makes use of Ethereum smart contracts and MetaMask. The suggested system uses Solidity-coded rules to enforce logical limitations on altitude changes, timestamp order, and geographic displacement in order to validate incoming flight messages. Every data transaction is protected by two layers of security: the smart contract's automated detection and MetaMask's manual permission. This combines operational control with the immutability of blockchain technology by guaranteeing that even reported anomalies cannot be committed without human consent. The OpenSky Network flight data was used to test the system, and 56 attack simulations in the spoofing, replay, and tampering categories were run. All accepted anomalies were purposefully allowed to test forensic transparency, and the contract obtained a 92.9% detection rate. All transaction information were retained in Ethereum's transparent ledger, enhancing its suitability for incident investigation and regulatory compliance. The findings support blockchain's applicability in preventing unwanted changes to aircraft telemetry. Stricter timestamp constraints, machine learning for anomaly detection, and interaction with international aircraft registries to better spoofing detection are possible future improvements. This approach combines the practical needs of air traffic with the potential advantages of blockchain technology.
Co-Authors Abu Hasan Achmad Aflah Jamazy Ade Silvia Handayani Adewasti Adewasti Adewasti, Adewasti Ahmad Adriansyah Ahmad Jazuli Ahmad Taqwa Ali Nurdin Alpharisy, Kevin Farid Alqhaniyyu, Faris Amiza, Ibel Dwi Amperawan Amperawan Amperawan Amperawan, Amperawan Anisah, Masayu APRILIANI, DEFINA Aryanti Aryanti . Aryanti Aryanti Ciksadan, Ciksadan Damsi, Faisal Deta Mediana, Salwa Diraputra, M Yoga Azto Dody Novriansyah EKA SUSANTI Fadhli, Mohammad Fahrudin, Gantar Fitra Faisal Damsi, Faisal Farhan, Novendra Faris Alqhaniyyu Fathria Nurul Fadillah Fistania Ade Putri Maharani Frenica, Agnes Garnis, Aishah Garnis, Aishah Ghina Rezkiah Octavia Gusni Amini Siagian Hafizh Ulwan Handayani, Kurnia Wati Pascitra Hj. Lindawati Humairoh, Sherina Husni, Nyayu Latifah Ihsan Mustaqiim Irawan Hadi Irawan Hadi Irma Salamah Irma Salamah Jami, Nurlita Joni, Bahri Joni, Bahri Junaidi Junaidi Junaidi Junaidi Junaidi, Junaidi Kgs Muhammad Farhan Rabbaniansyah Khairunnisa Khairunnisa L. Lindawati LINDAWATI Lindawati Lindawati Lindawati Lindawati Lindawati Lindawati M Yoga Azto Diraputra Maharani, Fistania Ade Putri Martinus Mujur Rose Mohammad Fadhli Muhammad Arcy Alfaathir Muhammad Juan Farza Rafly Alganiyu Muhammad Zakuan Agung Mujur Rose Nabila, Puspita Aliya Nadiah Nadiah Nakiatun Niswah Nasron Nasron Novianda, Nabila Rizqi Novianda, Nabila Rizqia Novriansyah, Dody Nurhajar Anugraha Nurul Fadhilah Oktariani Oktariani Oktariani, Oktariani Oktavia Manalu, Ria Pipit Wulandari Putri Andela Putri Vandalis, Yoke Annisa Putri, Alda Nabila Rabbaniansyah, Kgs Muhammad Farhan Raihanah, Adinda Ramadhan, Muhammad Fadli Rani Purnama Sari Repi, Intan Putri Ayu Agita Respati, Rayhan Dhafir Riona Alpeni Rivaldo Arviando Rizky, Putri Alifia Rodicky, Nadio Rose, Mujur Rumiasih Rumiasih Salsabila Dina Sari Sari, Rani Purnama Sarjana Sarjana Sarjana, Sarjana Savitri, Yulivia Rhadita Seliana, Imalda Septiani, Dinda Sholihin Sholihin Sholihin Sholihin Subianto, Cahyo Bayu Suci Lutfia Nisa Sudirman Yahya Suroso Suroso Suroso Suroso suzan zefi Tarnita Rizky Prihandhita Tarnita Rizky Prihandhita Tely, Aristo Theresia Enim Agusdi Trisa Azahra Wulandari, Pipit Yanziah, Asma Zakuan Agung, Muhammad