Article Per Year (5 Year)
p-Index From 2020 - 2025
2.557
P-Index
This Author published in this journals
All Journal Techno.Com: Jurnal Teknologi Informasi JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Teknik Informatika (JUTIF) Journal of Information Systems and Technology Research Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Wahana Internet of Things and Artificial Intelligence Journal Servire: Jurnal Pengabdian Kepada Masyarakat Journal of Technology Informatics and Engineering Rekognisi : Jurnal Pendidikan dan Kependidikan Sevaka: Hasil Kegiatan Layanan Masyarakat Outline Journal of Community Development Proceedings of The International Conference on Computer Science, Engineering, Social Sciences, and Multidisciplinary Studies
Muhammad Akbar Syahbana Pane
Institut Teknologi Sawit Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities 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 Library & Information Science Public Health Social Sciences Other

Published : 17 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 17 Documents
Search

 1   2 
Penerapan Metode Prewitt Dan Sobel Dalam Menganalisa Penyakit Bercak Daun Tanaman Rambutan Candra Wijaya Gulo; Hafizah Hafizah; Muhammad Akbar Syahbana Pane
Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Vol. 2 No. 3 (2023): EDISI MEI 2023
Publisher : STMIK Triguna Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jursi.v2i3.7886

Abstract

Tanaman rambutan adalah tanaman asli Indonesia yang tumbuh di berbagai wilayah di Indonesia dan bahkan sudah menyebar hingga ke daerah subtropis. Produksi rambutan dalam negeri terus meningkat setiap tahun, namun penyebaran penyakit pada tanaman rambutan seperti penyakit bercak daun dapat mengganggu produksi tanaman. Oleh karena itu, dibuatlah sebuah sistem berbasis desktop yang dapat menganalisa penyakit bercak daun pada tanaman rambutan menggunakan metode prewitt dan sobel dalam pengolahan citra digital. Metode prewitt dan sobel digunakan untuk mengurangi noise sebelum melakukan perhitungan deteksi tepi. Hasil dari penelitian ini adalah sebuah aplikasi yang dapat menganalisa penyakit bercak daun pada tanaman rambutan secara sistematis, sehingga hasil akurasi yang didapat sebesar 90%.
Low-Cost CCTV for Home Security With Face Detection Base on IoT Pane, Muhammad Akbar Syahbana; Saleh, Khairul; Prayogi, Andi; Dian, Rahmad; Siregar, Ratu Mutiara; Aris Sugianto, Raden
Journal of Information Systems and Technology Research Vol. 3 No. 1 (2024): January 2024
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v3i1.769

Abstract

Monitoring is a necessary part of Home surveillance that can be done through the internet network as a security measure. Many CCTV cameras on the market today continue to employ analog and conventional technology, specifically coaxial wire. As a result, extra expenditures for CCTV system wiring are required; besides being more expensive, the installation takes more handling, as the picture data cable and control signal cable cannot be merged. This project aims to develop a security system capable of detecting object movement in real-time utilizing a webcam camera attached to a raspberry pi. The findings of this study enable the development of a low-cost CCTV system that can be monitored remotely via the Internet of Things.
Direct implementation of AI-Based Facial Recognition for ITSI students Prayogi, Andi; Navea, Roy Francis; Dian, Rahmad; Pane, Muhammad Akbar Syahbana; Siregar, Ratu Mutiara; Sugianto, Raden Aris; Simbolon, Hasanal Fachri Satia
Journal of Information Systems and Technology Research Vol. 3 No. 3 (2024): September 2024
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v3i3.898

Abstract

The development of artificial intelligence (AI)-based facial recognition technology has become a significant research topic in the field of computing and security. At the Indonesian Palm Oil Institute (ITSI), AI-based facial recognition is introduced to students to improve their skills in developing AI-based applications. This study aims to implement and test a facial recognition system using a Python program by utilizing a dataset generated independently. This research method involves several stages, namely collecting ITSI students' facial data, data processing, creating a facial recognition model using a machine learning algorithm, and evaluating model performance. The dataset used was developed through a live shooting session involving active student participation. The facial recognition model was trained using a convolutional neural network (CNN) algorithm that was optimized to improve accuracy. The results of the study showed that the developed model was able to achieve high facial recognition accuracy, with an average accuracy rate of 92%. The discussion includes an analysis of factors that affect accuracy, such as variations in lighting and shooting angles, as well as the potential use of this technology in a campus environment, including for attendance and security purposes. The conclusion of this study shows that the implementation of AI-based facial recognition can be effectively applied in an academic environment, as well as providing students with practical experience in developing and testing AI applications. This study also opens up opportunities for further research on improving the performance of facial recognition systems and their application in various real-world scenarios.
IoT Oxymeter Starter Prototype As An Employee Health Monitoring Tool In The Blynk Integrated Palm Industry Muhammad Akbar Syahbana Pane; Rahmad Dian; Ratu Mutiara Siregar; Balqis Nurmauli Damanik; Asnita Yani; Alisarjuni Padang; Khairul Saleh
Journal of Technology Informatics and Engineering Vol 3 No 1 (2024): April : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i1.158

Abstract

One of the main challenges faced by workers in the palm oil industry is routine health monitoring. Therefore, innovation is needed in the form of health monitoring tools that can facilitate and increase the efficiency of employee health monitoring. The Internet of Things (IoT) has become an increasingly popular solution to overcome these challenges. The use of this technology is expected to increase employee health resilience, detect potential health problems early, and provide a quick response to health conditions that require medical attention.
Penggunaan Random Forest dan Analisis Perilaku untuk Prediksi Serangan DDoS dalam Lingkungan Cloud Computing Prayogi, Andi; Pane, Muhammad Akbar Syahbana; Dian, Rahmad; Siregar, Ratu Mutiara; Sugianto, Raden Aris; Simbolon, Hasanal Fachri Satia
Techno.Com Vol. 23 No. 3 (2024): Agustus 2024
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v23i3.11317

Abstract

Dalam dunia komputasi awan yang semakin berkembang, ancaman serangan Distributed Denial of Service (DDoS) menjadi isu yang sangat krusial. Penelitian ini bertujuan untuk mengembangkan dan mengimplementasikan model prediksi serangan DDoS menggunakan algoritma Random Forest dan analisis perilaku jaringan. Dataset CICIDS2017 digunakan sebagai sumber data utama untuk melatih dan menguji model prediksi yang dikembangkan. Pemilihan algoritma Random Forest didasarkan pada kemampuannya yang tinggi dalam menangani data besar dan kompleks serta kemampuannya dalam mengenali pola anomali yang sering menjadi indikasi serangan siber. Hasil pengujian menunjukkan bahwa model ini mencapai akurasi yang signifikan dengan precision sebesar 97,8%, recall sebesar 98,2%, dan F1-score sebesar 98,0%. Analisis perilaku jaringan yang diterapkan, melibatkan fitur-fitur dinamis seperti waktu antar paket (Inter-Arrival Time/IAT), ukuran rata-rata segmen, dan jumlah paket per detik, yang terbukti efektif dalam meningkatkan kemampuan deteksi model. Implementasi model dalam lingkungan komputasi awan menunjukkan bahwa metode ini dapat diintegrasikan dengan sistem deteksi intrusi (Intrusion Detection Systems/IDS) yang sudah ada untuk memberikan lapisan perlindungan tambahan terhadap serangan DDoS. Berdasarkan hasil yang diperoleh, penelitian ini merekomendasikan penggunaan kombinasi algoritma Random Forest dan analisis perilaku jaringan sebagai solusi yang efektif untuk mendeteksi serangan DDoS dalam lingkungan komputasi awan. Penelitian lanjutan disarankan untuk mengembangkan dan menguji model dengan dataset yang lebih beragam serta mengoptimalkan algoritma untuk meningkatkan performa deteksi.   Kata kunci: Random Forest, DDoS, Cloud Computing
DESIGN OF CONTROL SYSTEM AND TEMPERATURE IN COFFEE DRYER ARDUINO BASED AUTOMATIC USING FUZZY Ratu Mutiara Siregar; Budi Mulyara; Rahmad Dian; Maisarah Maisarah; Muhammad Akbar Syahbana Pane; Andi Prayogi
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 3 (2025): JITK Issue February 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i3.6166

Abstract

The coffee bean drying process is a crucial stage in ensuring the final quality of coffee products. Conventional drying methods, which rely on sunlight, face several challenges, such as dependence on weather conditions and prolonged drying times. This study proposes the design of a control and temperature system for an automatic coffee dryer based on the Arduino Mega 2560, aimed at enhancing the efficiency and consistency of the drying process. The system utilizes a semi-enclosed drying technology equipped with DHT22 temperature and humidity sensors, controlled by Arduino-Uno and Fuzzy Logic. This control system monitors temperature and humidity in real-time, maintaining the drying conditions at 55°C and 15% RH. If the temperature or humidity exceeds the set limits, the system activates an LED and buzzer alarm, indicating that the drying process has reached optimal conditions. The prototype was tested under various conditions, and the results demonstrate that the system has a high accuracy level in controlling temperature and humidity, significantly accelerating the drying process compared to traditional methods. By implementing this technology, the coffee industry in Indonesia is expected to achieve the Coffee Drying Operational Standards in accordance with SNI, maintain flavor quality, optimize the use of drying land, and reduce drying duration. This development offers an innovative solution that can enhance the quality and productivity of coffee processing, providing significant economic benefits to farmers and coffee industry stakeholders.
Identification of Tajweed Recognition using Wavelet Packet Adaptive Network based on Fuzzy Inference Systems (WPANFIS) Siregar, Ratu Mutiara; Satria, Budy; Prayogi, Andi; Pane, Muhammad Akbar Syahbana; Awal, Elsa Elvira; Sari, Yessi Ratna
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 1 (2024): Volume 4 Issue 1, 2024 [February]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i1.703

Abstract

This research aims to develop a system capable of processing voice input to recognize Al-Quran reading by recitation of Tajwid, using wavelet signal extraction and classification of Tajwid rules using ANFIS. The process stages include data acquisition, audio data pre-processing, extraction using wavelet packets, division of training data and test data, and classification. The data obtained were 20 observations from 10 observations carried out in data pre-processing. The wavelet decomposition process produces six main features as ANFIS input variables and 64 rules. Then the data was separated into 17 observations for training data and three for testing data. The test results obtained from the training that had been carried out produced plots that were too fit; in this experiment, the WPANFIS classification model got 100% appropriate classification and SSE values that were the same as the training result, 0.00081225.
Sosialisasi Digital Marketing pada UMKM Keripik Selasih di Kelurahan Sentang, Kecamatan Kisaran Timur, Asahan Simbolon, Hasanal Fachri Satia; Pane, Muhammad Akbar Syahbana; Saleh, Khairul; Siregar, Ratu Mutiara; Prayogi, Andi; Sugianto, Raden Aris; Wahyuni, Ritna
Wahana Jurnal Pengabdian kepada Masyarakat Vol. 4 No. 1 (2025): Edisi Juni
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/wahana.v4i1.906

Abstract

UMKM memiliki peran strategis dalam mendorong pertumbuhan ekonomi masyarakat, termasuk di Kabupaten Asahan, Sumatera Utara. Salah satu UMKM yang berpotensi untuk dikembangkan adalah Keripik Selasih, yang memiliki produk unggulan namun masih mengalami kesulitan dalam pemasaran digital. Kurangnya pengetahuan dan keterampilan dalam memanfaatkan teknologi digital menjadi hambatan utama dalam memperluas jangkauan pasar. Kegiatan Pengabdian Kepada Masyarakat (PKM) ini bertujuan untuk meningkatkan kapasitas pelaku UMKM Keripik Selasih dalam bidang digital marketing, melalui pelatihan yang mencakup penggunaan media sosial, pembuatan konten kreatif, dan pemanfaatan platform promosi daring. Metode pelaksanaan meliputi tahap persiapan, pelatihan tatap muka, praktik langsung, serta evaluasi hasil. Diharapkan melalui kegiatan ini, pelaku UMKM mampu memasarkan produk secara lebih efektif, memperluas jaringan konsumen, dan meningkatkan pendapatan usaha. Kegiatan ini juga menjadi bentuk kontribusi nyata mahasiswa dalam mendukung pemberdayaan ekonomi lokal melalui pendekatan teknologi informasi.
Measuring Soil Moisture in Real-Time: Arduino Uno Based Tool Innovation Pane, Muhammad Akbar Syahbana; Saleh, Khairul
Journal of Information Systems and Technology Research Vol. 4 No. 1 (2025): January 2025
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v4i01.1035

Abstract

Humidity measurement is vital across various sectors, such as agriculture, meteorology, industry, and households, where accurate monitoring ensures product quality, environmental stability, and process efficiency. Over time, humidity measurement technologies have evolved significantly, transitioning from basic evaporation-based methods to advanced electronic sensors like capacitive and resistive sensors, which offer real-time accuracy. Hygrometers and moisture meters are key devices in this field, with hygrometers measuring air humidity and moisture meters assessing water content in materials like soil, wood, and grains. Their integration with automation systems further enhances operational efficiency and simplifies environmental monitoring. Despite these advancements, challenges persist, including the need for higher accuracy, adaptability to diverse environments, and cost reduction. Research and development continue to tackle these issues, driving innovation toward more reliable, user-friendly, and affordable solutions. This article reviews the latest advancements in humidity measurement technologies, highlights the challenges faced, and explores future innovations that promise to enhance the accuracy and efficiency of these devices. Such progress is crucial for sustainability and improved performance in fields dependent on precise humidity data, ultimately supporting better decision-making and resource management.
Assessing Palm Plant Health through Color Analysis of Leaves Using MATLAB-Based Digital Image Processing Pane, Muhammad Akbar Syahbana; Saleh, Khairul; Satia Simbolon, Hasanal Fachri; Wilhelm Weber, Gerhard; Ehkan, Phaklen; Warip, Mohd Nazri
Journal of Information Systems and Technology Research Vol. 4 No. 2 (2025): May 2025
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v4i02.1133

Abstract

The health of oil palm plants can be visually assessed through changes in leaf color, which reflect the plant's physiological condition. Leaf color serves as a critical, non-destructive indicator for evaluating plant health. This study aims to develop an innovative method for detecting oil palm leaf health using MATLAB-based digital image processing techniques. The process begins with leaf image acquisition, followed by pre-processing to enhance image quality, and then color space conversion from RGB to HSV. The analysis focuses on the Hue and Saturation components, which represent the leaf's color tone and intensity. Two sample images—healthy and unhealthy leaves—are compared. The results demonstrate that healthy leaves exhibit higher average Hue and Saturation values compared to unhealthy ones, providing a key parameter for automated leaf condition classification. This study introduces a cost-effective system adaptable for small-scale farmers' plantations, offering an effective, efficient, and economical solution. This approach shows significant potential for implementation in automated plant health monitoring systems and further development for precision agriculture, particularly in oil palm plantations, to enhance productivity and sustainability in modern agriculture.
Co-Authors A. Khalid, Noor Aldeen Ali Ikhwan Alisarjuni Padang Aly, Moustafa H. Andi Prayogi Andi Prayogi Andysah Putera Utama Siahaan Ashari, Novialdi Asnita Yani Awal, Elsa Elvira Balqis Nurmauli Damanik Binti Saari, Erni Marlina Busrizal Faisal Candra Wijaya Gulo Friska Anggraini Barus Hafizah Hafizah Harahap, Sarwedi Hassan, Moustafa Hussein Ali Kan, Phak Len Al Eh Khairul Saleh Maisarah Mulyara, Budi Navea, Roy Francis Novialdi Ashari Phaklen Ehkan, Phaklen Prayogi, Andi Rahmad Dian Rahmad Dian Rahmad Dian Ratu Mutiara Siregar Ritna Wahyuni Sari, Yessi Ratna Satia Simbolon, Hasanal Fachri Sihaloho, Fahmi Ashari S Sihaloho, Ulfah Oktarida Simbolon, Hasanal Fachri Satia Sri Wahyuna Saragih Warip, Mohd Nazri Wilhelm Weber, Gerhard