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All Journal Jurnal Pendidikan dan Konseling JuSTISe: Journal Data Science, Technology, Informatics and Security
Deni Suprihadi
Universitas Kebangsaan Republik Indonesia
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Sistem Pemilihan Pupuk Terbaik pada Tanaman Kapulaga dengan Metode TOPSIS (Studi Kasus Perkebunan XYZ di Wonosobo) Deni Suprihadi; Putri Cahya Isabella
Jurnal Pendidikan dan Konseling (JPDK) Vol. 4 No. 6 (2022): Jurnal Pendidikan dan Konseling: Special Issue (General)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jpdk.v4i6.10300

Abstract

Penelitian ini bertujuan untuk merancang dan menciptakan Sistem Pendukung Keputusan Pemilihan Pupuk Terbaik Pada Tanaman Kapulaga dimana banyaknya jenis pupuk dengan komposisi dan manfaat yang berbeda menjadi suatu permasalahan petani dalam melakukan pemilihan pupuk dengan kualitas terbaik. Untuk mengatasi masalah tersebut maka dibuatnya Sistem Pendukung Keputusan dengan metode TOPSIS yang dilakukan dengan keputusan multikriteria bahwa alternatif yang terpilih harus mempunyai jarak terdekat dari solusi positif dan mempunyai jarak terjauh dari solusi ideal negatif. .jadi didalam web nya petani dapat melihat hasil pupuk terbaik untuk tanaman kapulaga.
Analisis Digital Forensik pada Digital Footprint untuk Identifikasi Pelaku Cybercrime dengan Framework FDFI Bunga Islamiya Putri; Deni Suprihadi
Journal Data Science, Technology, Informatics and Security Vol 1 No 1 (2023): Journal Data Science, Technology, Informatics and Security (Juni 2023)
Publisher : Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31848/justise.v1i1.3272

Abstract

The large number of social media users at this time, resulting in many crimes (cybercrime), and the difficulty of identifying cybercrime perpetrators on social media because most of them are done anonymously (using fake accounts). However, the digital footprint left by users can facilitate the process of identifying perpetrators. This study uses the Social Network Analysis (SNA) Method to collect data and approach social media then uses the Digital Forensics Investigation Framework (FDFI) in conducting investigative analysis. The study will analyze digital evidence searches on the Twitter app. The main finding of the study is that this approach is able to identify digital traces with high accuracy and associate them with the identity of the perpetrator. The results of this study have an important impact on law enforcement and cyber crime prevention. Effective perpetrator identification through digital footprint analysis can assist law enforcement agencies in taking swift and accurate action. In addition, this research can also be the basis for the development of more sophisticated and adaptive forensic digital analysis methods in the face of technological developments and new crime methods in cyberspace.
Implementasi Sistem Otomatisasi Pendeteksi Kebakaran Berbasis Internet Of Things (IoT) Menggunakan Flame Sensor (Studi Kasus Di SMK Negeri 1 Cijati Cianjur) Sima Kristina; Deni Suprihadi
Journal Data Science, Technology, Informatics and Security Vol 1 No 2 (2023): Journal Data Science, Technology, Informatics and Security (Desember 2023)
Publisher : Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31848/justise.v1i2.3390

Abstract

Fire is a tragedy that cannot be predicted, besides being unwanted by the community, it is also often out of control. This fire really threatens the lives of the entire academic community if it occurs at school. Many factors cause fires, one of which is caused by natural factors, non-natural factors or human factors. Fires that occur in schools can cause material damage and result in significant financial losses. Considering the many valuable facilities and property such as books, computers, equipment and other valuables. The use and application of fire detection technology isone answer to reducing more fatal fires. Fire detectors can be part of an early warning system in dealing with emergencies. in an emergency.
Implementasi Sistem Pengendalian Suhu Air pada Akuarium Tanaman Anubias Menggunakan Mikrokontroler Wemos Vio Monica; Deni Suprihadi
Journal Data Science, Technology, Informatics and Security Vol 2 No 1 (2024): Journal Data Science, Technology, Informatics and Security (Juni 2024)
Publisher : Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31848/justise.v2i01.3431

Abstract

Tanaman air Anubias merupakan jenis tanaman akuatik yang populer dalam hobi akuarium. Untuk memastikan pertumbuhan dan kesehatan yang optimal, suhu air harus dikendalikan dengan baik. Perubahan suhu yang ekstrem atau tidak sesuai dapat menyebabkan kerusakan pada tanaman atau bahkan kematian. Pengelolaan suhu air pada akuarium tradisional seringkali memerlukan pengawasan manual dan penyesuaian berkala, yang tidak efisien dan dapat menyebabkan ketidakstabilan suhu yang merugikan tanaman. Oleh karena itu, diperlukan sistem otomatis yang dapat terus-menerus memantau dan mengontrol suhu air. Penelitian yang dilakukan di Toko BNR Aquatic di Lembang telah mengidentifikasi aspek penting dalam perawatan tanaman Anubias. Cuaca ekstrem yang tidak dapat diprediksi menjadi tantangan, karena suhu sering berubah dengan cepat. Terdapat kasus di BNR Lembang di mana suhu air turun di bawah 22°C. Rentang suhu air ideal untuk tanaman akuarium adalah 22°C hingga 28°C; deviasi dari rentang ini dapat menyebabkan kerusakan atau layu pada tanaman. Platform App Inventor memungkinkan pengembangan aplikasi mobile sederhana untuk pemantauan dan pengendalian presisi suhu air Anubias. Data suhu yang terkumpul dapat diunggah dan disimpan di platform Thingspeak. Studi kasus lingkungan dingin relevan karena suhu air cenderung lebih rendah, sehingga sulit menjaga rentang yang sesuai untuk pertumbuhan tanaman. Oleh karena itu, penelitian ini bertujuanmengembangkan sistem untuk membantu penggemar dan petani tanaman akuatik, memastikan kondisi optimal bahkan di lingkungan suhu rendah.Penerapan solusi IoT untuk pengendalian suhu air akuarium menawarkan pengelolaan yang lebih akurat dan presisi. Ini memberdayakan budidaya Anubias untuk memantau suhu air secara real-time melalui internet dan mengotomatiskan pengendalian air dengan mengatur pemanas air secara remote. Kata Kunci : Anubias, Suhu, UML dan IoT
Efektivitas RANSAC dan Outlier Detection dalam Mendeteksi Keaslian pada Gambar Foto Produk Digital Hamako Eco Babywear Anhar Abul Gani; Deni Suprihadi
Journal Data Science, Technology, Informatics and Security Vol 2 No 1 (2024): Journal Data Science, Technology, Informatics and Security (Juni 2024)
Publisher : Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31848/justise.v2i1.3547

Abstract

This study addresses the increasing risk of digital crimes, particularly image forgery, as a result of advancements in information and communication technology. The research focuses on comparing two methods, RANSAC and Outlier Detection, for analyzing the authenticity of digital images related to Hamako Eco Baby Wear products, which potentially violate Intellectual Property Rights (IPR). The case involves the misuse of product logos and attributes. The Integrated Digital Forensic Investigation Framework (IDFIF) is employed as the main framework, supplemented by tools such as the Image Hash Generator and RANSAC Detection. This study also examines metadata from sample and suspect images, providing crucial information about the time and tools used for capturing or editing the images. The findings reveal that the Outlier Detection method is effective in quickly identifying image anomalies, while RANSAC generates a mathematical model that is robust against outliers, enabling deeper analysis. These two methods complement each other in proving image forgery or misuse. This research contributes significantly to the development of digital forensic techniques, particularly in analyzing the authenticity of digital images in the modern era.
Investigasi Digital Forensik pada Perangkat IoT dalam Sistem Rumah Pintar (Smart Home) Menggunakan Framework Application Specific Investigation Model (FASIM) Deni Koswara; Deni Suprihadi
Journal Data Science, Technology, Informatics and Security Vol 2 No 2 (2024): Journal Data Science, Technology, Informatics and Security (Desember 2024)
Publisher : Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31848/justise.v2i2.3592

Abstract

The rapid development of the Internet of Things (IoT) presents new opportunities and challenges in cybersecurity, particularly in smart home systems. This study aims to investigate the security and privacy of IoT devices in smart home environments using the Application Specific Investigation Model (FASIM) framework. The research focuses on the processes of acquisition, analysis, and reporting of digital evidence from IoT devices such as light controllers, security cameras, temperature controllers, and door locks. The methods include identifying IoT devices, analyzing data using tools such as Hercules, WireShark, FFMPEG, and Fing, as well as utilizing MD5 hashing to ensure data integrity. The findings reveal that IoT devices in smart home systems can provide valid digital traces that can be further processed in digital forensic investigations. This study is expected to contribute significantly to enhancing the security and privacy of smart home systems and serve as a foundation for future research on digital forensic investigations of IoT devices.
Penerapan Teknologi Application Programming Interface (API) MikroTik untuk Monitoring Virtual Local Area Network (VLAN) di SMK Al-Munawaroh Cianjur Aris Suhendra; Deni Suprihadi
Journal Data Science, Technology, Informatics and Security Vol 2 No 2 (2024): Journal Data Science, Technology, Informatics and Security (Desember 2024)
Publisher : Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31848/justise.v2i2.3984

Abstract

This study aims to enhance network control at SMK Al-Munawwarah Cianjur by implementing MikroTik API technology, focusing specifically on the Control aspect of the PIECES method. This aspect includes user access management, data security, and access control to network resources. The research begins with an analysis of the existing network control system, followed by identifying the need for more effective control mechanisms. To improve network control, a MikroTik API-based solution is developed to optimize VLAN configuration and network monitoring. This solution is implemented with the expectation of addressing existing weaknesses in the network management system, as well as providing greater ease and flexibility in network surveillance and access control. The results of the study demonstrate that the use of MikroTik API significantly enhances VLAN configuration efficiency, user access management, and network monitoring within the school environment. This implementation also successfully improves the security and integrity of data transmitted across the network, creating a more secure and controlled network environment. Thus, the findings of this research can serve as a reference for the development of network control systems in other educational institutions with similar needs.
Sistem Peringatan Dini Bencana Banjir Berbasis Mikrokontroler ATmega16 dengan Buzzer dan Web-Based Alfi febriawan Febriawan; Deni Suprihadi
Journal Data Science, Technology, Informatics and Security Vol 3 No 2 (2025): Journal Data Science, Technology, Informatics and Security (Desember 2025)
Publisher : Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31848/justise.v3i2.3988

Abstract

Flooding is one of the natural disasters that often occurs due to high rainfall and overflowing rivers. Sumbersari Village, especially in Sapan Village, often experiences flooding due to the overflowing Citarum River. Therefore, a flood detection tool is needed to provide early warning to the community in order to reduce the risk and losses due to flooding. This study aims to design and develop an Arduino Uno-based flood early warning system with a fuzzy approach. This system uses an HC-SR04 ultrasonic sensor to measure water levels and a raindrop detection sensor to detect rain intensity. Data from the sensor is processed by the Arduino Uno microcontroller and displayed via a buzzer and a web-based platform. The test results show that this tool has high accuracy in monitoring water levels and providing real-time warnings to the community around the river flow. It is hoped that this system can be an effective solution in flood disaster mitigation.
Implementasi Algoritma K-Nearest Neighbor dan Naive Bayes dalam Memprediksi Status Seleksi pada PPDB Rifqi Maulana Adam; Deni Suprihadi
Journal Data Science, Technology, Informatics and Security Vol 3 No 1 (2025): Journal Data Science, Technology, Informatics and Security (Juni 2025)
Publisher : Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31848/justise.v3i1.4298

Abstract

Abstracts, This study aims to implement the K-Nearest Neighbor (KNN) and Naive Bayes algorithms to predict the selection status of New Student Admissions (PPDB) at the junior high school level in Cianjur Regency. PPDB is an annual agenda that plays a crucial role in determining the transition of students to higher education levels. However, the selection process often poses challenges, particularly due to limited information and subjectivity in decision-making by students and parents. This research adopts a quantitative approach by utilizing historical registration data from 20 public junior high schools in Cianjur Regency. The research procedure includes data collection, preprocessing, implementation of the KNN and Naive Bayes algorithms, and evaluation using the Confusion Matrix. The results indicate that both algorithms are capable of predicting students’ acceptance status through the zoning and achievement tracks with accuracy levels above 85%. Naive Bayes demonstrates advantages in computational efficiency, while KNN provides greater flexibility in handling variations in data. The developed prediction system is expected to assist students and parents in determining the most suitable school objectively and support schools and education authorities in providing data-driven recommendations. Furthermore, this study reinforces findings from previous research, emphasizing the potential of data mining as an effective approach to support educational selection processes and decision-making.
RESTful API dengan Dukungan AES-GCM dan XChaCha20-Poly1305 dalam Pengelolaan Data Identitas Penduduk (Studi Kasus Desa Galudra) Restu Oktafiandi; Deni Suprihadi
Journal Data Science, Technology, Informatics and Security Vol 3 No 2 (2025): Journal Data Science, Technology, Informatics and Security (Desember 2025)
Publisher : Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31848/justise.v3i2.4302

Abstract

The management of citizen identity data plays a critical role in governmental administration, including in Galudra Village, Cugenang District, Cianjur Regency. Traditionally, data recording has relied on Microsoft Excel, which, while adequate in the early stages, becomes inefficient as the population grows and the demand for fast, accurate, and secure services increases. This study develops a RESTful API integrated with AES-GCM and XChaCha20-Poly1305 cryptographic algorithms to enhance both security and efficiency in managing resident data. AES-GCM is employed to secure stored data, whereas XChaCha20-Poly1305 is applied to protect data during transmission. The system was developed using the waterfall model, with blackbox testing applied to validate its functionality. The implementation results indicate that the system effectively accelerates data processing and safeguards sensitive information. Network monitoring with Wireshark confirmed that all transmitted data is well-encrypted, making it inaccessible in its original form. Therefore, this solution not only addresses efficiency and security challenges at the village level but also aligns with Law Number 27 of 2022 concerning Personal Data Protection, and serves as a reference for implementing secure information technology in local government environments.
Co-Authors Alfi febriawan Febriawan Anhar Abul Gani Aris Suhendra Bunga Islamiya Putri Deni Koswara Putri Cahya Isabella Restu Oktafiandi Rifqi Maulana Adam Sima Kristina Vio Monica