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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Inotera Journal of Computer Networks, Architecture and High Performance Computing Brilliance: Research of Artificial Intelligence International Journal of Multidisciplinary Sciences and Arts SAINTI: Majalah Ilmiah Teknologi Industri Majalah Ilmiah METHODA Deli Sains Informatika JATAED: Journal of Appropriate Technology for Agriculture, Environment, and Development PERFECT: Journal of Smart Algorithms SULIWA: Jurnal Multidisiplin Teknik, Sains, Pendidikan dan Teknologi DCS: Jurnal Pengabdian Masyarakat Global Advances in Science, Engineering & Technology (GASET)
Candra, Rudi Arif
Politeknik Aceh Selatan, Indonesia
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Public Health Other

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Flood Detection Tool Using Ultrasonic Sensor Based on Telegram and Sound in Krueng Kluet River Flow Ilham, Dirja Nur; Candra, Rudi Arif; Fardiansyah, Fardiansyah; Sipahutar , Erwinsyah; Budiansyah, Arie
PERFECT: Journal of Smart Algorithms Vol. 1 No. 2 (2024): PERFECT: Journal of Smart Algorithms, Article Research July 2024
Publisher : LEMBAGA KAJIAN PEMBANGUNAN PERTANIAN DAN LINGKUNGAN (LKPPL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62671/perfect.v1i2.29

Abstract

Flooding is a problem that until now still requires special handling from various parties, both from the government and the community. Flooding is not a light problem because flooding can disrupt community activities and cause losses, such as the washing away of household equipment, valuables, and electronic goods. Flooding occurs due to rising water levels in rivers due to abnormal rainfall, damaged dams, obstruction of water flow at the site of the dam's destruction in the River Basin Area (DAK), and the construction of facilities and infrastructure. The series of "Flood Detection Devices using Ultrasonic Based on Telegram and Sound consists of three parts, namely the input section, the control section, and the display section. This design was made to simplify the process in the Ultrasonic Flood Detection Device Design using telegrams and sound. The Ultrasonic Flood Detection Device Design Circuit using telegrams and sound consists of three parts, namely the input section, the control section, and the display section. The first Flood Detection Device Test using Ultrasonic Sensors Based on Telegram and Sound has been tried as many as 10 The first experiment The water depth is 1 meter, the distance of the sensor to the water surface is 3 meters, it is said that the status is safe, there is no notification to the telegram and the siren does not sound. Experiment 2: The water depth is 2 meters, the distance of the sensor from the water surface is 2 meters, it is said to be on standby, then the flood detector provides notification to the telegram via the telegram bot, and the siren sounds. Experiment 3: The water depth is 3 meters, the distance of the sensor from the water surface is 1 meter, it is said to be on standby, then the flood detector provides notification to the telegram via the telegram bot, and the siren sounds.
Prototype Design and Development of an IoT-Enabled Monitoring and Control System for Public Street Lighting Ilham, Dirja Nur; Candra, Rudi Arif; Budiansyah, Arie; Zulfan, Zulfan
PERFECT: Journal of Smart Algorithms Vol. 2 No. 1 (2025): PERFECT: Journal of Smart Algorithms, Article Research January 2025
Publisher : LEMBAGA KAJIAN PEMBANGUNAN PERTANIAN DAN LINGKUNGAN (LKPPL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62671/perfect.v2i1.53

Abstract

This research discusses the Internet of Things (IoT)-based Public Street Lighting (PJU) system to improve energy efficiency and remote monitoring. The background problem is the need to improve operational efficiency and energy savings in the PJU system. This final project aims to design and test an IoT-based PJU system that transmits real-time data between nodes and gateways using LoRa technology and the MQTT protocol. The research process involves hardware and software design, as well as system testing under various conditions. The tests measured the data transmission time and analyzed the delay using LED indicators on the gateway and dashboard devices. The test results showed significant variations in data transmission time compared to the programmed time. The programmed transmission time was 10 seconds for node 1 and 20 seconds for node 2, but the test results showed an average time of about 15 seconds for node 1 and 21.89 to 36.02 seconds for node 2. This variation is due to factors such as network communication delay, processor load, and LoRa system efficiency.
Real-Time Classification of Local Orange Fruit Quality Using YOLO (You Only Look Once) and SVM (Support Vector Machine) Methods Harahap, Muhammad Khoiruddin; Candra, Rudi Arif; Budiansyah, Arie; Aritonang, Romulo P.; Zulfan, Zulfan; Saputra, Devi Satria
PERFECT: Journal of Smart Algorithms Vol. 2 No. 2 (2025): PERFECT: Journal of Smart Algorithms, Article Research July 2025
Publisher : LEMBAGA KAJIAN PEMBANGUNAN PERTANIAN DAN LINGKUNGAN (LKPPL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62671/perfect.v2i2.55

Abstract

Oranges are a fruit that we often encounter and are even consumed by people because of their various benefits. Oranges have commercial value in Indonesia and have a fairly wide reach. In order to increase competitiveness, oranges must also meet market standards, both domestic and foreign, so that they can be accepted by consumers. Of course, in this case, orange selection is very important. increasing sales and market competition by sellers, important indicators in selecting citrus fruit are in terms of size and color. In general, the selection of citrus fruit is done manually and based on human thinking, which causes several weaknesses that must be corrected, including requiring a long time, human visual limitations, and being influenced by human psychology itself. This is what causes inconsistencies in selection. oranges and does not comply with existing market requirements. So a research was carried out regarding the quality classification of local citrus fruit using the YOLO (You Only Look Once) and SVM (Support Vector Machine) methods in real time. In the comparison made between the two methods used, Yolo was found to be the best method for classifying citrus fruit.
Prototype of IoT-Based Fruit Alcohol Level Measurement Tool Nursila, Nursila; Ilham, Dirja Nur; Yunan, Amsar; Harahap, Muhammad Khoiruddin; Candra, Rudi Arif
Brilliance: Research of Artificial Intelligence Vol. 1 No. 1 (2021): Brilliance: Research of Artificial Intelligence, Article Research May 2021
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v1i1.1078

Abstract

The effect of alcohol on health is very large if you consume too much, and the fact that excessive alcohol levels can interfere with digestion can cause eye function disorders, decreased brain and nerve function as well as cancer. Knowing the alcohol content in fruits that are suitable for consumption by the body from an early age is very important. Based on this problem, this study aims to create a prototype measuring instrument for the alcohol content of fruits using the Blynk application. This circuit consists of 3 circuits, namely the input part in the form of an Mq3 sensor, the control part in the form of Nodemcu, and the output port in the form of the Blynk application. From the results of testing tools for four samples including durian, grapes, papaya, and apples for 25 times the test of the fruit is peeled for the next 2 hours the average percentage of durian alcohol content is 28.57%, grapes are 12.68%, papaya is 5.79 %, and apples by 18.6%. In this study, there is also the notification facility to the third smartphone that the alcohol content exceeds the alcohol content which is not good from the value set on the device.
IoT Based Paint Feed Process Monitoring System Implementation Shahrul; Budiansyah, Arie; Suryadi; Candra, Rudi Arif; Ilham, Dirja Nur
Brilliance: Research of Artificial Intelligence Vol. 2 No. 1 (2022): Brilliance: Research of Artificial Intelligence, Article Research February 2022
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v2i1.1492

Abstract

The increasing level of human mobility causes pets to be abandoned because humans have activities that cannot be left behind or work that must always be done, with this, pets, one of which is a cat, are often hungry because the caregiver is busy working and does not have time to feed the cat. This research is about designing an automatic cat feeder with a periodic monitoring system with a Nodemcu control system with two sensors, namely an Ir sensor and an Ultrasonic sensor with a telegram notification output. the working principle of the Sensors Ir 1 and 2 will detect a cat, if it hits the cat, the place for giving food and drink will open automatically while ultrasonic sensors 1 and 2 are for monitoring food and drink if food and drink do not hit the ultrasonic sensor it will enter a notification that the food and drink had run out. the conclusion of making this tool is to make it easier for cat owners to automatically feed cats.
Detection of DNS Spoofing Attacks on Campus Networks Using LightGBM with Hybrid Feature Selection (SelectKBest + SHAP) Budiansyah, Arie; Candra, Rudi Arif; Ilham, Dirja Nur; Misbullah, Alim
Brilliance: Research of Artificial Intelligence Vol. 5 No. 1 (2025): Brilliance: Research of Artificial Intelligence, Article Research May 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i1.5962

Abstract

This study investigates the detection of Domain Name System over HTTPS (DoH) spoofing attacks utilizing the CIRA-CIC-DoHBrw-2020 dataset, which encompasses over 100,000 labeled DNS records categorized as either normal or malicious. Features such as packet timing, packet size, and TLS parameters are utilized for detection purposes. A systematic feature selection process is conducted utilizing the Elbow and Kneedle methods based on F-Score values derived from a built-in model evaluation. This method ensures that the top features are selected objectively and quantitatively, thereby enhancing the robustness of the model. The model is trained using the five most significant features, yielding exceptional performance metrics: a training time of just 0.5727 seconds, an inference time of 0.0157 seconds, and an inference latency of 0.0035 milliseconds per sample. Moreover, the model delivers an outstanding accuracy of 0.9995, an F1-Score of 0.9995, and an AUC-ROC of 1.0000, reflecting near-perfect detection capabilities. The classification report reveals a balanced distribution of precision, recall, and F1-Scores of 1.00 across both normal and malicious classes, based on a test sample of 14,974 entries. The Elbow plot visually confirms the optimal number of features utilized, while the SHAP beeswarm plot provides insights into how each selected feature contributes to the model’s predictions, facilitating interpretability. Additionally, the confusion matrix corroborates the model's reliability, showcasing that nearly all samples were accurately classified. The results demonstrate that the proposed methodology significantly enhances the effectiveness of DNS spoofing detection, offering a promising avenue for securing DNS over HTTPS communications.
Design Of Automatic Laptop Cooling System Using Ds18b20 Temperature Sensor Based On Arduino Nano Oktrison, oktrison; Sipahutar, Erwinsyah; Candra, Rudi Arif; Budiansyah, Arie
Brilliance: Research of Artificial Intelligence Vol. 5 No. 1 (2025): Brilliance: Research of Artificial Intelligence, Article Research May 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i1.6073

Abstract

Technological developments in the field of automation provide opportunities to improve efficiency and comfort in the operation of electronic devices. This research aims to design and implement an automatic cooling system on a laptop that uses an Arduino Nano-based DS18B20 temperature sensor. The system is designed to automatically regulate the laptop temperature by monitoring the temperature in real-time, and activating the cooling fan through a relay when the temperature reaches 33°C or more. This research method includes hardware design that involves the use of Arduino Nano as a microcontroller, a DS18B20 temperature sensor to detect temperature changes, and a relay to control the cooling fan. The software was developed using the Arduino programming language (C++) to process the data from the sensors and manage the work of the cooling system automatically. The test results show that the system can accurately detect the laptop temperature and respond in real-time by turning on the cooling fan when the temperature exceeds the 33°C limit. The system proved to be effective in preventing overheating, keeping the device temperature within safe limits, and optimizing power consumption by turning off the fan when the temperature returns to stable.
The Effectiveness of Machine Learning Techniques in Anomaly Detection for Cyberattack Prevention: Systematic Literature Review 2020-2025 Budiansyah, Arie; Zulfan, Zulfan; Nizamuddin, Nizamuddin; Candra, Rudi Arif; Ilham, Dirja Nur; Nazaruddin, Nazaruddin
Brilliance: Research of Artificial Intelligence Vol. 5 No. 1 (2025): Brilliance: Research of Artificial Intelligence, Article Research May 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i1.6124

Abstract

As digital technology evolves, cyberattacks are becoming more diverse and difficult to detect. Conventional detection methods are often incapable of recognizing new and sophisticated attack patterns. Therefore, machine learning techniques are starting to be widely used because of their ability to study data patterns and detect unusual or anomalous activities. This study aims to systematically examine the effectiveness of various machine learning techniques in detecting anomalies as an effort to prevent cyberattacks. The research was conducted using the Systematic Literature Review (SLR) method on 20 scientific articles from reputable journals published between 2020 and 2025. The articles were selected through a search, selection, and analysis process following PRISMA guidelines. The results of the study show that algorithms such as Random Forest and Decision Tree consistently provide accurate detection results, especially in network systems and the Internet of Things (IoT). Meanwhile, deep learning techniques such as CNN and LSTM show high performance in handling large and complex data. However, challenges are still found in terms of data imbalances, high computing requirements, and lack of model interpretability. The conclusions of this study show that machine learning techniques are very promising for anomaly detection in cybersecurity, but an adaptive and easy-to-explain approach is needed. Researchers are further advised to develop models that are more efficient, transparent, and able to adapt to evolving cyber threats.
Penerapan Simulator Online Wokwi untuk Pembelajaran Mikrokontroler bagi Guru Smk Kabupaten Aceh Selatan Candra, Rudi Arif; Ilham, Dirja Nur; Sipahutar, Erwinsyah; Budiansyah, Arie; Fardiansyah, Fardiansyah
DCS: Jurnal Pengabdian Masyarakat Vol. 1 No. 2 (2024): DCS: Jurnal Pengabdian Masyarakat, Volume 1 Nomor 2, Desember 2024
Publisher : LEMBAGA KAJIAN PEMBANGUNAN PERTANIAN DAN LINGKUNGAN (LKPPL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62671/qr4fbw39

Abstract

Kegiatan pengabdian kepada masyarakat ini dilaksanakan berdasarkan hasil pengamatan terhadap para guru smk di kabupaten aceh selatan  yang dianggap masih belum mengenal dan menguasai penggunaan aplikasi WOKWI dalam Pembelajaran Mikrokontroler. Untuk itu perlu adanya pelatihan tentang mikrokontroler menggunakan aplikasi online WOKWI bagi guru SMK dalam pembelajaran Perangkat keras dan Teknologi Internet Of things dan efisien. Tujuan dari kegiatan ini adalah untuk meningkatkan pengetahuan dan keterampilan serta pembiasaan guru dalam penggunaan Aplikasi WOKWI. Dalam pelaksanaannya, kegiatan pengabdian ini dilakukan dalam bentuk ceramah materi pelatihan secara daring dan evaluasi. Metode survey digunakan untuk mengevaluasi hasil kegiatan melalui pendistribusian angket secara online. Data menunjukkan rata-rata respon baik yang diberikan oleh peserta kegiatan adalah sebesar 92.6%. Dengan kata lain, pelaksanaan pengabdian masyarakatini telah memberikan kontribusi positif terhadap profesionalitas guru dalam pemanfaatan teknologi Informasi
Implementasi simulator online Tinkercad dalam pembelajaran IoT untuk guru dan laboran SMK di Aceh Selatan Candra, Rudi Arif; Ilham, Dirja Nur; Sipahutar , Erwinsyah; Budiansyah, Arie; Anugreni, Fera
DCS: Jurnal Pengabdian Masyarakat Vol. 2 No. 1 (2025): DCS: Jurnal Pengabdian Masyarakat, Volume 2 Nomor 1, Juni 2025
Publisher : LEMBAGA KAJIAN PEMBANGUNAN PERTANIAN DAN LINGKUNGAN (LKPPL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62671/dcs.v2i1.75

Abstract

Penelitian ini bertujuan untuk mengeksplorasi efektivitas penggunaan simulator online Tinkercad dalam pengajaran IoT kepada guru dan siswa di laboratorium SMK di Aceh Selatan. Penggunaan Tinkercad diharapkan dapat meningkatkan pemahaman dan keterampilan siswa dalam teknologi IoT, serta mendukung pengembangan kompetensi guru dalam mengajar materi tersebut.Hasil dari penelitian ini diharapkan dapat memberikan kontribusi positif terhadap peningkatan kualitas pembelajaran IoT di SMK, sejalan dengan perkembangan teknologi yang pesat saat ini.Penelitian ini juga sejalan dengan tren globalisasi yang memerlukan peningkatan kompetensi dalam teknologi informasi dan komunikasi bagi tenaga pendidik dan siswa di seluruh dunia.Penerapan Tinkercad sebagai alat bantu dalam pembelajaran IoT diharapkan dapat memfasilitasi interaksi yang lebih baik antara guru dan siswa, serta meningkatkan hasil belajar secara keseluruhan. Dengan demikian, penelitian ini bertujuan untuk memberikan wawasan baru mengenai penerapan teknologi dalam pendidikan, khususnya dalam konteks pembelajaran IoT di SMK.Hasil penelitian ini diharapkan dapat menjadi referensi bagi institusi pendidikan lain yang ingin mengimplementasikan teknologi serupa dalam kurikulum mereka. Penerapan simulator online seperti Tinkercad diharapkan dapat memperluas wawasan siswa dan guru dalam bidang IoT, sesuai dengan kebutuhan kompetensi yang semakin meningkat di masyarakat. Selain itu, penelitian ini juga akan mengevaluasi dampak penggunaan Tinkercad terhadap motivasi belajar siswa dan efektivitas pengajaran guru, memberikan gambaran menyeluruh tentang inovasi dalam pendidikan.
Co-Authors . Zulfan Achriadi , T. Sukma Alfy Ariswan Amri, Asbahrul Amsar Yunan Amsar, Amsar Ananda, Desnalita Andika, Putra Anugreni, Fera Anwar, Ihsan Arie Budiansyah Aritonang, Romulo P. Balkhaya, Balkhaya Bean, Hasbaini Budianyah, Arie Dewi, Irana Eka Dodi Suryanto Eri Satria Eri Satria Erwinsyah Sipahutar Erwinsyah Sipahutar Faisal Irsan Pasaribu Fardiansyah Adami Fardiansyah, Fardiansyah Fauza , Rial Fauzun Atabiq Ginting, Depi Hafizh, Alfi Hardisal, Hardisal Haristian Pratama Hasbaini, Hasbaini Herma Nugroho Rono Adi Kusumo Herry Setiawan Herry Setiawan Ihsan Ihsan Ihsan Ihsan, M Arinal Ilham, Dirja Nur Irwansyah Irwansyah Irwansyah Syam Jamsan, Firdaus Jannah, Dina Miftahul Khairuman Man Khairuman, Khairuman Khusnul Azima Mario di Nardo Misbullah, Alim Miswar Papuangan Miza, Khairul Muhammad Farhan Muhammad Khoiruddin Harahap Muhammed Saat Talib N. Nazaruddin Nisa, Rahmatul Nizamuddin Nizamuddin Nursila Nursila Nursila, Nursila Nursita, Putri Oktrison Oktrison Oktrison, Oktrison Pratama, Ahya Rizki Putra, Reza Ade Rahmadani, Pia Rater, Salya Saputra, Devi Satria Sepri Kurniadi Shahrul Shahrul Sipahutar , Erwinsyah Siti Rusdiana sriwahyuni Sriwahyuni Sukma, Kemala Suryadi Suryadi Suryadi Talib, Muhammed Saat Taufiq Abdul Gani Urmila, Tasya Wahyu Ariansyah William Sutanto