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All Journal Sistemasi: Jurnal Sistem Informasi JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL IT: Media Infromasi STMIK Handayani Makassar Journal of System and Computer Engineering Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Journal Peqguruang: Conference Series Malcom: Indonesian Journal of Machine Learning and Computer Science Ranah Research : Journal of Multidisciplinary Research and Development Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Sahibu, Supriadi
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APLIKASI PEMBELAJARAN PROSES DAUR AIR DAN PERISTIWA ALAM UNTUK MATA PELAJARAN IPA KELAS V SD BERBASIS ANDROID Sahibu, Supriadi; YP, Disyan
JURNAL IT Media Informasi STMIK Handayani Makassar Vol 9 No 3 (2018): Volume 9 Nomor 3, Desember 2018 IT JURNAL
Publisher : LPPM- STMIK HANDAYANI MAKASSAR

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

Abstract

Perancangan aplikasi media pembelajran ini bertujuan, (1) Untuk merancang Aplikasi Pembelajaran Proses Daur Air Dan Peristiwa Alam Pada Mata Pelajaran IPA Kelas V SD Berbasis Android. (2) Untuk mengimplementasikan Metode Linear Congruent Method (LCM) Aplikasi Pembelajaran Proses Daur Air Dan Peristiwa Alam Pada Mata Pelajaran IPA Kelas V SD Berbasis Android. Pada perancangan aplikasi ini, pemgembangan sistem yang digunakan yaitu UML (Unified Modeling Language). Sedangkan pembuatan aplikasi perangkat lunak dalam skripsi ini, penulis menggunakan perangkat lunak Adobe Profesional CS6, CorelDraw, Adobe AIR, PhotoShop dengan menggunakan metode LCM (Linear Congrate Methode).Hasil dari penelitian ini adalah sebuah media pembelajaran yang dapat memudahkan siswa untuk saling berinteraksi dalam belajar dan menciptakan pembelajaran yang tidak membosankan, serta mampu meningkatkan motivasi belajar siswa. Hasil penelitian Ratna Mustikawati (2013) menunjukkan bahwa media pembelajaran berbasis Adobe Flash dapat meningkatkan motivasi belajar siswa pada mata pelajaran IPA
Analysis Of Themes and Trends in Life Sciences and Biomedical Research Virtual Reality Sahibu, Supriadi; Munsyir, Mulawarman; Gani, Hamdan; Taufik, Imran; Iskandar, Akbar
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol. 12 No. 2 (2022): Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Pusat Penelitian dan Pengabdian Pada Masyarakat Sekolah Tinggi Manajemen Informatika dan Komputer AKBA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (786.578 KB) | DOI: 10.35585/inspir.v12i2.5

Abstract

The purpose of this study was to investigate the theme of the abstract, the theme of the Title on Virtual Reality in the Sciences and Biomedical Sciences and to investigate the trends of authors and countries who are major contributors to research on virtual reality in the sciences and biomedical sciences, the researchers used metadata from 497 journals. scientifically indexed with topic modeling algorithms. The results of the study found that for virtual reality themes listed in the abstracts of science and biomedical fields, the words that often appear were study and systems related to pediatric surgery, stroke and cancer. Then the research theme in the virtual reality title regarding science and biomedicine is to get words that often appear, namely evaluation and videos that contain about the fields of dental health, stroke and cancer, Furthermore, from a technological point of view, it relates to head-mounted devices to display 2 or 3 dimensions, and educational psychometric technology relates to learning to care for children for students. While the sports side is related to the movement of the body's physical activity in adults. Analysis of research trends for authors and countries that are major contributors to virtual reality research on science and biomedical based on wordcloud analysis with names that often appear in virtual reality is Wiederhold BK and the dominant country is United State.
Analisis Tren Penelitian Neuro Linguistic Programming Menggunakan Pendekatan Automatic Text Annotation Ian, Muslihan; Sahibu, Supriadi; Taufik, Imran
Journal Peqguruang: Conference Series Vol 6, No 1 (2024): Peqguruang, Volume 6 Nomor 1 Mei 2024
Publisher : Universitas Al Asyariah Mandar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35329/jp.v5i2.4857

Abstract

Analisis tren penelitian merupakan jenis pengolahan bahasa alami untuk menarik suatu kata kunci dari penelitian mahasiswa tentang topik tertentu. Analisis tren penelitian melibatkan dalam membangun sebuah sistem untuk mengumpulkan dan memeriksa topik penelitian mahasiswa yang dibuat dalam repository perpustakaan atau jurnal pada suatu lembaga Pendidikan.Tujuan dari penelitian ini adalah untuk menentukan tren penelitian pada jurnal penelitian suatu lembaga pendidikan, dengan menerapkan pendekatan Automatic Text Anotation dapat menfilter kalimat yang ingin ditemukan dalam suatu jurnal dengan cepat dan efisien.Hasil dari penelitian dari Penelitian ini Melalui penggunaan algoritma LSTM ini, berbagai publikasi dengan tema Sentimen Analisis berhasil dikumpulkan yaitu jurnal nasional dan jurnal internasional tahun tahun 2020-2022 dan diolah secara otomatis untuk mengidentifikasi tren dari penelitian seperti Focus, domain dan Technique yang digunakan dalam penelitian tersebut memperoleh hasil penelitian yakni, dengan menggunakan Skenario split dataset sebesar 90% data latih dan 10% data testing dengan epoch 200 maka didapatkan tingkat akurasi dari permodelan LSTM yaitu sebaesar 93.73%. dan diperoleh validasi akurasi 94.94% dan diperoleh nilai Loss sebesar 0.189% dan validasi Loss sebesar 0.195%. maka dapat disimpulkan bahwa model LSTM dapat melakukan prediksi atau Automatic Text Annotation dikarenakan memiliki akurasi sebesar 100% dari hasil pengujian algoritma.
Implementasi Algoritma Convolutional Neural Network untuk Klasifikasi Jenis Sampah Organik dan Non Organik: Implementation of the Convolutional Neural Network Algorithm for Classifying Types of Organic and Non-Organic Waste Muslihati, Muslihati; Sahibu, Supriadi; Taufik, Imran
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 3 (2024): MALCOM July 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i3.1346

Abstract

Penelitian ini bertujuan untuk mengimplementasikan algoritma Convolutional Neural Network (CNN) dalam klasifikasi sampah organik dan non-organik serta mengukur tingkat akurasi deteksi dan pengenalan objek sampah. Metode CNN digunakan untuk mendeteksi dan mengenali objek dalam citra. Hasil penelitian menunjukkan bahwa model CNN mencapai tingkat akurasi tertinggi sebesar 96.43% setelah enam kali percobaan. Hasil tersebut menunjukkan bahwa aplikasi CNN ini layak untuk diimplementasikan dalam klasifikasi sampah. Penting untuk melakukan beberapa uji coba guna memperoleh hasil akurasi yang optimal dengan memperhatikan dataset dalam proses pelatihan dan pengujian. Kesimpulan dari penelitian ini adalah bahwa model CNN dapat memberikan hasil akurasi yang baik dalam klasifikasi sampah organik dan non-organik, sehingga aplikasi ini memiliki potensi untuk diimplementasikan secara luas
Sistem Kontrol dan Monitoring Penggunaan Daya Peralatan Elektronik pada Rumah Berbasis Internet Of Things (IOT) Dahlan, Dahlan; Yuyun, Yuyun; Sahibu, Supriadi
Journal of System and Computer Engineering Vol 6 No 1 (2025): JSCE: January 2025
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v6i1.1613

Abstract

The objectives of this study are (1) to achieve energy efficiency and cost savings (2) Internet of Things (IoT)-based control and monitoring systems using Node MCU ESP32 as a data processing center (3) enabling data processing from PZEM-004T sensors and sending control commands to solid state relays (SSR) based on user input via a website application. The implementation of this system shows significant potential in reducing energy consumption and costs in households. With real-time feedback on energy consumption, users can make wiser decisions about the use of electronic equipment, thereby reducing energy waste. Remote control capabilities allow users to manage electronic equipment more effectively, improve security, and reduce unnecessary energy consumption. This study shows that manual electricity usage reaches 9.59%, while with the implementation of the IoT system it is only 5.49%, so there is a saving in electricity consumption of 4.1%. This proves that the IoT system is more effective and efficient in managing the power consumption of electronic equipment.
Air Conditioner Control and Monitoring System based on Temperature Balance in Server Room using Fuzzy Logic and Internet of Things Methods Putu Rika Permana, I Gusti; Sahibu, Supriadi; Jalil, Abdul; Munawirah, Munawirah
Journal of System and Computer Engineering Vol 6 No 1 (2025): JSCE: January 2025
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v6i1.1623

Abstract

This research develops a temperature and humidity control system in the server room based on the Internet of Things and using fuzzy logic algorithms at AMIK Luwuk Banggai. The system is designed using NodeMCU ESP32, DHT11 sensor, Arduino IDE, and Blynk application, with objective of monitoring and controlling environmental conditions in real time. A series of quantitative experiments were conducted to evaluate the effectiveness of the sensor system. These experiments involved observations, measurements, and a comparison of the results with manual calculations. The results demonstrate that the DHT11 sensor exhibits a margin of error of 1.21% and a hardware accuracy rate of 98.79%. Furthermore, the integration of the Internet of Things (IoT) and the implementation of fuzzy logic in air conditioner control studies, as demonstrated in this study, has the potential to enhance the accuracy of temperature and humidity control within the room server to an accuracy rate of 90.91%. Furthermore, it can improve the responsiveness of the system in maintaining temperature stability. These findings were observed at AMIK Luwuk Banggai, where the application of IoT and fuzzy logic has been implemented. Fuzzy logic offers an effective and dependable approach to regulating temperature fluctuations in the server room, ensuring a stable environment that minimizes the likelihood of operational issues or hardware damage. The objective is to extend the lifespan of the hardware by preventing such complications.
Development of an IoT-based Heart and Lung Monitoring Device at Baubau Regional Hospital Maibara, Rais; Sahibu, Supriadi; Jalil, Abdul
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i4.5155

Abstract

Cardiovascular diseases and lung infections require intensive monitoring, especially for high-risk patients. The limited number of specialist doctors at Baubau Regional Hospital often leads to delays in patient treatment. This study aims to develop an Internet of Things (IoT)-based health monitoring system that detects heart rate, oxygen saturation, and body temperature in real time using MAX30100 and DS18B20 sensors. The collected data is transmitted to Firebase and displayed on an Android application to facilitate remote monitoring. Testing results show an accuracy rate of 98.46% for heart rate, 98.6% for oxygen saturation, and 99.04% for body temperature, with deviations remaining within medically acceptable limits. The system’s preliminary diagnoses closely matched those of medical professionals, indicating its potential as an effective tool for early health risk detection and for supporting clinical decision-making.
Teknologi Irigasi Berbasis IoT: Integrasi Sensor Nirkabel (SN), Energi Surya dan Logika Fuzzy Sahibu, Supriadi; Surahman; Ahmad, Andani
JURNAL FASILKOM Vol. 15 No. 1 (2025): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v15i1.8899

Abstract

Agriculture is a vital sector in the global economy that faces various challenges, especially in the efficient use of water resources. Irrigation is an important aspect of agriculture, especially in rice fields, because optimal water supply directly affects plant productivity. However, in Pao Village, Malangke District, and North Luwu Regency, water availability is increasingly limited due to climate change, urbanization, and inefficient exploitation of resources. Most farmers in the area do not have irrigation networks so during the dry season their rice fields experience drought and are at risk of crop failure. This study aims to design and develop an automatic irrigation system based on the Internet of Things (IoT) supported by wireless sensors and solar energy to improve the efficiency of water use in rice fields. The research method used is a prototype approach consisting of three main stages, namely preparation, prototype development, and system implementation. In the preparation stage, field observations and literature studies were carried out to determine system needs. The development stage includes design, implementation, and internal evaluation of the prototype. Furthermore, the system was implemented and tested in the field to assess its effectiveness in controlling irrigation automatically. The results of the study showed that the developed system was able to detect water levels using ultrasonic sensors and humidity sensors connected to Arduino. Data from the sensors is processed using fuzzy logic to automatically control the water pump based on the water conditions in the farmland. The energy used comes from solar panels, so the system can operate independently and is environmentally friendly. Tests have shown that the system works well in regulating the water supply to the rice fields efficiently and can help farmers overcome drought and increase agricultural productivity.
Crop Recommendation Based on Soil and Weather Conditions Using the K-Nearest Neighbors Algorithm Yuliyanto, Yuliyanto; Sahibu, Supriadi; Imran, Taufik; Arisha, Andriansyah Oktafiandi; Munawirah, Munawirah
Journal of System and Computer Engineering Vol 6 No 3 (2025): JSCE: July 2025
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v6i3.1955

Abstract

The national food self-sufficiency program demands innovation in optimizing the selection of agricultural commodities based on environmental and weather conditions. This challenge is rooted in a fundamental problem faced by farmers—achieving harmony among soil characteristics, weather patterns, and suitable crops. In support of this initiative, it is necessary to develop a crop recommendation system based on machine learning that utilizes key soil and weather condition parameters. This study employs the K-Nearest Neighbors (KNN) algorithm, which functions by identifying the optimal value of ‘K’ to maximize classification accuracy. The KNN algorithm is implemented in a crop recommendation system to classify 1,100 datasets representing ideal growing conditions for 11 crop types. These datasets were generated using a normal distribution approach with a 5% variation from the mean values, and were validated using a clipping function to ensure the data remained within ideal ranges. The results of this study demonstrate that the KNN algorithm achieves high accuracy 96,67% in utilizing soil and weather parameters to generate crop recommendations. The average probability score for the recommended crops was 83.33%. Based on experimental testing, rice was recommended during the rainy and extreme rainy seasons, soybeans were recommended during the dry season, and mung beans were most suitable during extreme dry conditions.
Multi-Modal Sensor Integration in Smart Rooms to Optimize Internet of Things-Based Monitoring and Security Control of Autistic Child Detection Activities Taufiq, Arfah; Sahibu, Supriadi; Jalil, Abdul
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.11013

Abstract

The advancement of Internet of Things (IoT) technology has opened new opportunities for automated monitoring systems, especially for children with Autism Spectrum Disorder (ASD). These children require intensive supervision due to communication limitations and unpredictable behavior. This study aims to design and implement a smart room system integrated with multi-modal sensors to monitor autistic children's activities in real time.Using a Research and Development (R&D) approach with the ADDIE model, the system was developed with an ESP32 microcontroller and sensors including PIR (motion), DHT22 (temperature), microphone (sound), and LDR (light). The Mamdani fuzzy logic algorithm processes sensor data to classify safety levels. Data is visualized and notified via the Blynk platform.Test results show the system effectively detects "safe," "needs attention," and "critical" conditions with high accuracy, providing timely alerts for parents. This solution enhances home-based supervision and offers a practical, IoT-based approach to child safety and care.
Co-Authors Abdul jalil Ahmad, Andani Akbar Iskandar Arisha, Andriansyah Oktafiandi Dahlan Hamdan Gani Ian, Muslihan Imran, Taufik Jusdi, Jusdi Maibara, Rais Munawirah, Munawirah Munsyir, Mulawarman Muslihati Putu Rika Permana, I Gusti Surahman Taufik, Imran Taufiq, Arfah Wardi Wardi YP, Disyan Yuliyanto Yuliyanto Yuyun, Yuyun