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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) Sistemasi: Jurnal Sistem Informasi SCIENCE TECH: Jurnal Ilmiah Ilmu Pengetahuan dan Teknologi JURNAL MEDIA INFORMATIKA BUDIDARMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Infomedia Progresif: Jurnal Ilmiah Komputer Buletin Ilmiah Sarjana Teknik Elektro Jurnal Abdi Insani Jurnal Aplikasi Teknologi Informasi dan Manajemen (JATIM) Jurnal Algoritma SmartComp The Indonesian Journal of Computer Science Tanggap Masyarakat untuk Aksi dan Sinergi
Ashari, Wahid Miftahul
Universitas AMIKOM Yogyakarta
Agriculture, Biological Sciences & Forestry Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics

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Automatic Vegetable Watering System Using Fuzzy Logic with Integration of Soil Moisture, Rain Sensors, and RTC Arginanta, Dallarizki; Ashari, Wahid Miftahul
Journal of Applied Informatics and Computing Vol. 8 No. 2 (2024): December 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v8i2.8319

Abstract

Conventional vegetable watering often presents challenges, particularly in ensuring that plants receive adequate water without excessive manual intervention. This research proposes a solution in the form of an automatic watering system using fuzzy logic, which integrates soil moisture sensors, rain sensors, and an RTC (Real-Time Clock) for scheduling. The system is designed to replace manual watering methods with an automated process, thus improving the efficiency and effectiveness of vegetable cultivation. The developed device uses a soil moisture sensor to monitor soil conditions, a rain sensor to detect rainfall, and an RTC to determine the optimal watering times. The Arduino Uno acts as the main controller that activates the water pump via a relay driver based on data received from the sensors. Test results show that the system operates according to the established criteria, with a satisfactory accuracy level. The system successfully waters the plants at 07:00 WIB and 15:00 WIB, based on dry soil conditions and no rain. The trials showed that the device has an average soil moisture measurement error of 5%, and a time discrepancy of about 22 seconds on the RTC module. Each 1% increase in soil moisture requires approximately 1 second of watering duration. Watering times are adjusted to prevent the plants from drying out or dying, with a soil moisture threshold of below 40% set as the condition for requiring watering.
Text Data Security Using LCG and CBC with Steganography Technique on Digital Image Wildan, Muhammad; Ashari, Wahid Miftahul
Journal of Applied Informatics and Computing Vol. 8 No. 2 (2024): December 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v8i2.8457

Abstract

This research proposes a text data security method using a combination of Linear Congruential Generator (LCG), Advanced Encryption Standard (AES) Cipher Block Chaining (CBC) mode, and Least Significant Bit (LSB) steganography technique on digital images. The message scrambling process using LCG produces ASCII characters as noise that is inserted in the original message. After that, the message is encrypted using AES-256 CBC to provide additional security. The encryption result is then hidden in the digital image through LSB steganography technique. Tests were conducted on images with JPEG and BMP formats to measure the visual quality after the data insertion process, as measured by PSNR (Peak Signal-to-Noise Ratio). The test results show a PSNR value of 56.60 dB for JPEG images and 70.84 dB for BMP images. In addition, the insertion process in JPEG images degrades the image quality, mainly due to lossy compression, compared to the lossless BMP format. This study concludes that the proposed combination of methods is effective in hiding messages in images, but is susceptible to compression on lossy formats such as JPEG. The use of lossless image formats such as BMP or PNG is recommended to maintain data integrity.
Performance Comparison of Random Forest and Decision Tree Algorithms for Anomaly Detection in Networks Ramadhan, Rafiq Fajar; Ashari, Wahid Miftahul
Journal of Applied Informatics and Computing Vol. 8 No. 2 (2024): December 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v8i2.8492

Abstract

The increase in cyber attacks has made network security a very important focus in this digital era. This research compares the performance of two machine learning algorithms, that is Random Forest and Decision Tree for detecting anomalies in networks using the UNSW-NB15 datasets, which include various types of attacks such as DoS, Backdoor, Exploits and others which will be used to train and test both models. The data collection method, pre-processing, data splitting and modelling using SMOTE method to handle data imbalanced were applied in both algorithms and then evaluated using accuracy, precision, recall and f1-score metrics. From the study result, it can be conclude that the Decision Tree algorithm performs better in detecting anomalies in binary data with an accuracy of 99,71%. However, in multi-class data, Random Forest showed slightly better performance, though it required significantly more time for training and prediction. Despite the small difference in accuracy, Decision Tree demonstrated faster prediction times, making it more efficient for time-sensitive applications. This research concludes that while Random Forest provides higher accuracy for complex datasets, Decision Tree offers a more time-efficient solution with comparable accuracy.
Sistem Monitoring Kadar pH Kolam Udang Secara Real-Time Dengan Algoritma Regresi Linier Fatimah, Fajar Nur Aini Dwi; Ashari, Wahid Miftahul
The Indonesian Journal of Computer Science Vol. 12 No. 3 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i3.3215

Abstract

Budidaya udang merupakan salah satu komoditas utama yang sedang digencarkan oleh pemerintah. Kurangnya implementasi teknologi membuat budidaya menghasilkan hasil yang kurang maksimal. Mahalnya alat ukur dan tidak akurasinya alat ukur membuat para pengelola tambak budidaya udang tidak menerapkan teknologi pada proses budidaya. Penelitian ini nantinya akan mengembangkan sebuah algoritme yang dapat menghasilkan estimasi PH akurat dari kondisi air pada tambak udang. Sehingga dengan menggunakan alat ukur yang sederhana para pengelola tambak udang dapat menghasilkan kondisi PH yang akurat. Pengumpulan data dilakukan dengan cara mengembangkan alat ukur atau PH meter yang akan diterapkan kolam udang, proses pengukuran akan dilakukan dengan menggunakan sensor PH yang akan diproses dengan menggunakan microcontroller yaitu arduino. Pengembangkan algoritme estimasi akan menggunakan algoritme regresi linier yang dapat menghasilkan estimasi PH akurat. Diharapkan dari algoritme yang dihasilkan dari penelitian ini dapat membantu para pengelola tambak udang untuk dapat menghasilkan hasil yang lebih maksimal karena dapat mengantisipasi kondisi-kondisi yang tidak diinginkan sejak dini.
Infiltrasi Union: SQL injection untuk Ekstraksi Kredensial Admin Setiawan, Rangga Wahyu; Ashari, Wahid Miftahul
The Indonesian Journal of Computer Science Vol. 12 No. 6 (2023): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i6.3460

Abstract

Eksploitasi web adalah suatu tindakan untuk memanfaatkan celah keamanan pada sebuah situs web untuk mendapatkan akses yang tidak sah ke sistem tersebut, SQL injection adalah jenis kerentanan keamanan yang terjadi dalam aplikasi web berbasis database di mana penyerang melibatkan kode berbahaya ke dalam aplikasi untuk mendapatkan akses tidak sah ke informasi sensitif. Makalah ini bertujuan untuk memberikan wawasan yang komprehensif dan sistematis tentang metode yang ada untuk mendeteksi serangan injeksi SQL. Dalam penelitian ini, penulis mengambil aplikasi web sebagai objek dan mencoba mendemonstrasikan serangan aplikasi web umum yaitu SQL injection. Penggunaan query union memiliki peran penting dalam melakukan SQL injection pada kasus ini, karena jika dilihat dari database tersebut tidak memiliki field name username dan password. Inti serangan ini mencoba untuk menggabungkan hasil dari query asli dengan hasil dari query yang dicuri dari tabel "pengguna".
Prototype Sistem Monitoring Lampu Penerangan Jalan Umum Menggunakan Zigbee dan Esp32: Prototype of Public Street Light Monitoring System Using Zigbee and Esp32 Ashari, Wahid Miftahul; Jeki Kuswanto; Firman Asharudin; Andriyan Dwi Putra; Muhammad Tofa Nurcholis
The Indonesian Journal of Computer Science Vol. 13 No. 1 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i1.3598

Abstract

Street lighting, or Public Street Lighting (PJU), is crucial infrastructure in an area, particularly for nighttime traffic illumination. Efficiency and monitoring pose significant challenges in PJU management. Most PJUs lack a monitoring system, making control and malfunction detection difficult. Monitoring is expected to efficiently regulate the on-off schedule and detect malfunctions. This research aims to develop a cost-effective PJU monitoring and efficiency system without replacing many existing devices. The method employs Zigbee technology and Esp32. This system is anticipated to enhance efficiency and detect issues more promptly than before.
Enhancing Website Security Using Vulnerability Assessment and Penetration Testing (VAPT) Based on OWASP Top Ten Rohmaniah, Diana; Ashari, Wahid Miftahul; Lukman, Lukman; Putra, Andriyan Dwi
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.9069

Abstract

Website security is one of the main concerns in the digital era, given the increasing potential for cyber threats. This research aims to improve website security by using the Vulnerability Assessment and Penetration Testing (VAPT) method that refers to the OWASP Top Ten standard. The applied method includes four main stages: information gathering, vulnerability scanning, exploitation, and reporting. The results showed that there were several successfully exploited vulnerabilities, such as Clickjacking, Improper HTTP to HTTPS Redirection, Directory Listing, and Sensitive Information Disclosure, which were classified based on the OWASP Top Ten. The severity of the vulnerabilities was analyzed using Common Vulnerabilities and Exposures (CVE), Common Weakness Enumeration (CWE), and Common Vulnerability Scoring System (CVSS). The analysis results show that some vulnerabilities have high severity after considering the factual conditions of the system. This research provides specific remediation recommendations to address these vulnerabilities, such as the implementation of security headers, deletion of sensitive configuration files, and dependency updates. With this approach, the research is expected to contribute to improving website security and provide effective mitigation guidelines.
Evaluation of the Effectiveness of Lightweight Encryption Algorithms on Data Performance and Security on IoT Devices Indrajati, Damar; Ashari, Wahid Miftahul
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9256

Abstract

Data security remains a major concern in the Internet of Things (IoT) landscape due to the inherent limitations in computational power, memory capacity, and energy availability of IoT devices. To address these challenges, lightweight encryption algorithms have emerged as alternatives to conventional cryptographic methods, aiming to balance performance and security. This study evaluates the effectiveness of five encryption algorithms—SIMON64/128, SPECK64/128, XTEA64/128, PRESENT64/128, and AES128—on IoT devices through experimental analysis of their security strength, execution time, CPU utilization, memory usage, and power efficiency. The experiments were conducted on a Raspberry Pi 3B+ using C-based implementations to emulate realistic IoT scenarios. The findings reveal that AES128 offers the strongest security characteristics, including the highest Avalanche Effect (39.29%) and Differential Resistance Score (6.76/10), but at the expense of significant resource consumption. In contrast, SIMON64/128 and SPECK64/128 deliver superior performance in terms of speed and resource efficiency, making them ideal for low-power environments, albeit with concerns about potential cryptographic backdoors. XTEA64/128 emerges as a practical compromise, delivering moderate security and low power consumption without known vulnerabilities. Based on these results, AES128 is suitable for high-capacity IoT platforms prioritizing strong encryption, while SIMON and SPECK are preferable for resource-constrained devices, with XTEA serving as a balanced alternative. This research contributes a comparative framework to guide the selection of encryption algorithms for IoT systems, ensuring an optimal trade-off between security and operational efficiency.
Pengembangan Keterampilan Dasar Pemrograman bagi Siswa SMA N 2 Bantul sebagai Persiapan di Era Digital Putra, Andriyan Dwi; Nur'aini; Ashari, Wahid Miftahul; Sismoro, Heri; Kuswanto, Jeki
Tanggap Masyarakat untuk Aksi dan Sinergi Vol. 1 No. 02 (2025): Volume 01 Nomor 02 - Juni 2025
Publisher : TAM Global Insights - PT. Treeta Amanah Mandiri Group

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

Abstract

Pelatihan Internet of Things (IoT) di SMA Negeri 2 Bantul dilaksanakan sebagai respons terhadap rendahnya literasi teknologi dan keterampilan digital siswa, serta keterbatasan tenaga pengajar dan sumber belajar di bidang IoT. Kegiatan ini bertujuan untuk meningkatkan kompetensi dasar siswa dalam memahami dan mengaplikasikan teknologi IoT melalui pendekatan pembelajaran interaktif, praktik langsung, serta pengembangan proyek mini. Metode pelaksanaan meliputi tahap persiapan, pelaksanaan inti, dan evaluasi, dengan dukungan modul pembelajaran cetak dan digital, video tutorial, serta sesi pendampingan intensif. Hasil evaluasi menunjukkan bahwa 68,3% siswa merasa puas dan 25,5% cukup puas terhadap pelatihan yang diberikan. Pelatihan ini terbukti mampu meningkatkan minat dan pemahaman siswa terhadap IoT, serta memperlihatkan pentingnya sinergi antara sekolah dan perguruan tinggi dalam mendukung transformasi pendidikan berbasis teknologi. Kegiatan ini diharapkan menjadi model pelatihan yang dapat direplikasi di sekolah lain untuk mendorong literasi teknologi sejak dini.
Support Vector Machine Classification Algorithm for Detecting DDoS Attacks on Network Traffic Irawan, Yoki; Pramitasari, Rina; Ashari, Wahid Miftahul; Yansyah, Aiko Nur Hendry
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.10003

Abstract

Distributed Denial of Service (DDoS) attacks represent a significant danger in network security because they can lead to extensive service interruptions. With these attacks increasingly mirroring regular traffic, smart and effective detection systems are essential. This research seeks to assess the efficacy of the Support Vector Machine (SVM) classification algorithm in identifying DDoS attacks in network traffic. The data utilized is CICIDS2017, focusing on the subset Friday-WorkingHours-Afternoon-DDos.pcap_ISCX.csv, which contains both legitimate traffic and DDoS attacks like DoS-Hulk, DoS-GoldenEye, and DDoS. The preprocessing stage included eliminating duplicates and null entries, label binary encoding, normalization through Min-Max Scaler, and feature selection applying the Chi-Square technique. The data was divided into 80% for training and 20% for testing purposes. The Radial Basis Function (RBF) kernel was utilized to train the SVM model, and hyperparameter optimization was performed with GridSearchCV. The evaluation of the model's performance was conducted through accuracy, precision, recall, F1-score, confusion matrix, and visual representations including ROC and Precision-Recall Curves. The findings indicate that prior to tuning, the model reached an accuracy of 97%, which increased to 99% post-tuning, accompanied by an F1-score of 0.99. This shows that the SVM algorithm, when paired with appropriate preprocessing and optimization, is very efficient in identifying DDoS attacks within network traffic.
Co-Authors Amalina, Inna Nur Andriyan Dwi Putra Arginanta, Dallarizki Asharudin, Firman Astari, Devi Wening Dony Ariyus Fajar Nur Aini Dwi Fatimah Fatimah, Fajar Nur Aini Dwi Febrian Putra Pratama Firman Asharudin Firman Asharudin Gilang Ramadhan, Zaka Hakim, Muhamad Nauval Indrajati, Damar Jeki Kuswanto Jeki Kuswanto Koprawi, Muhammad Lukman Lukman Martisa Fiorentina, Rinda Muhammad Koprawi Muhammad Tofa Nurcholis Muhammad Wildan Nenden Ranuma Ratri Nevy Bella Samantha Norhikmah Norhikmah Nugraha, Anggit Ferdita Nur'aini Nurussa'adah, Erfina Putra, Andriyan Dwi Putra, Wahyu Sukestyastama Ramadhan, Rafiq Fajar Rina Pramitasari Rohmaniah, Diana Saputra Aji, Dian Satrya Bhayangkara, Dimas Senie Destya Setiawan, Rangga Wahyu Sismoro, Heri Sunu Pamungkas, Hanfazano Rahmadimasti Yansyah, Aiko Nur Hendry Yoki Irawan