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Analisa Prioritas Bandwidth Menggunakan Metode HTB (Hierarchical Token Bucket) Studi Kasus : SMK Taruna Mandiri Pekanbaru Yuda Irawan; Herianto; Siti Aisyah; Refni Wahyuni
SATIN - Sains dan Teknologi Informasi Vol 8 No 1 (2022): SATIN - Sains dan Teknologi Informasi
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (334.511 KB) | DOI: 10.33372/stn.v8i1.814

Abstract

Banyaknya kebutuhan dunia pendidikan yang mengharuskan pihak pengembang aplikasi dalam mengembangkan berbagai terobosan teknologi untuk mendukung stabilitas dalam berinteraksi. Harga Bandwitdh yang cukup tinggi menyebabkan pihak sekolah melakukan pembatasan jumlah Bandwitdh yang diberikan oleh operator. Semakin meningkatnya kebutuhan akan internet hal ini menjadi permasaalahan bagi pengguna. Permasalahannya adalah semakin banyak yang membuka situs di internet tentu akan mengurangi kuota atau paket data. Untuk menyelesaikan permasalahan ini maka dilakukan proses tahapan analisa prioritas bandwidth menggunakan metode HTB (Hierarchical Token Bucket). Metode ini mempunyai kelebihan dalam pembatasan trafik pada tiap level maupun klasifikasi, sehingga bandwidth yang dipakai level yang tinggi dapat digunakan atau dipinjam oleh level yang lebih rendah. Berdasarkan hasil analisa dan pengujian yang telah dilakukan Penulis, maka dapat disimpulkan bahwa Metode antrian Hierarchical Token Bucket dinilai lebih efektif membagi bandwidth secara adil dan merata kepada masing-masing client yang membutuhkan bandwidth, terlihat dari grafik perhitungan nilai QoS yang telah dilakukan. Dari hasil perhitungan dalam pengujian metode HTB melalui download berkas, nilai rata-rata yang diperoleh berdasarkan standar kategori TIPHON untuk indeks parameter. Throughtput indeks parameter delay bernilai 4 dengan indeks parameter jitter indeks parameter packet loss.
Workshop creating references on the final project of stikes hang tuah pekanbaru students using mendeley application Yuda Irawan; Refni Wahyuni; Yulisman; Matthijs B Punt
Jurnal Pengabdian dan Pemberdayaan Masyarakat Indonesia Vol. 1 No. 1 (2021)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jppmi.v1i1.2

Abstract

Making or compiling a final project report has many issues, one of which students frequently complain about: compiling a bibliography. The workshop aimed to provide students with knowledge about citing and compiling an automatic bibliography, as well as to take advantage of one of the advancements in information technology that students could use to compile a bibliography or reference by using an application. The workshop was held online using the Google Meet platform and the Mendeley application to create a list of references. The workshop activity went smoothly without any major impediments, and the participants were 44 Fifth Semester Diploma Midwifery students. Measurement of the introduction of the Mendeley application prior to the workshop using the evaluation questionnaire revealed that 95.45% of participants did not know the Mendeley application at all, while 4.55% knew about it. The result of the evaluation questionnaire found that 70.45% of participants said that the Mendeley application was easy to use, and 29.55% said that it was difficult to use. 100% of participants would use the Mendeley application to prepare the final assignment report (LTA).
Counseling and Controlling Child Development based on Information Technology at Fajar Harapan Infant and Toddler Orphanage Yuda Irawan; Refni Wahyuni; Yesica Devis
Jurnal Pengabdian dan Pemberdayaan Masyarakat Indonesia Vol. 1 No. 7 (2021)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jppmi.v1i7.32

Abstract

The orphanage is the best place for neglected children to get services, education, skills to become quality and useful children for many people. To create all that, it is necessary to improve the quality of the Orphanage. The Fajar Harapan Infant and Toddler Orphanage is currently experiencing several problems, including: Monitoring child growth using only the Manual Towards Health Card (KMS), Lack of knowledge of caregivers about child growth and development, and lack of child health equipment. Based on the existing problems, the following solutions can be given: Designing child development applications; Provide counseling, training and guidance to caregivers related to children's growth and development and nutritional intake, as well as providing orphanage health equipment. From the results of Community Service activities that have been carried out, namely the availability of applications for monitoring web-based growth and development that can be accessed online, making it easier for caregivers to see the growth and development of their foster children and making it easier for administrators to monitor the growth and development of foster children. Availability of health equipment such as scales, height measuring instruments, head circumference measuring instruments, thermometers, mattresses, and first aid kits to support growth and development control. With the existence of growth and development counseling activities, it provides the benefit of increasing caregiver knowledge about child development and increasing caregiver skills in providing nutritional intake and providing stimulation to children so that children's health and growth and development improve better.
Smart Egg Incubator Based on IoT and AI Technology for Modern Poultry Farming Wahyuni, Refni; Irawan, Yuda; Febriani, Anita; Nurhadi, Nurhadi; Tri Saputra, Haris; Andrianto, Richi
ILKOM Jurnal Ilmiah Vol 16, No 2 (2024)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v16i2.1957.134-144

Abstract

The productivity of egg hatching in the poultry industry is often hindered by conventional methods, resulting in low hatch rates and slow production. This study introduces the UHTP (Universitas Hang Tuah Pekanbaru) Smart Egg Incubator, which incorporates Internet of Things (IoT) and Artificial Intelligence (AI) technologies, specifically the Mamdani Fuzzy Logic Algorithm, to enhance egg hatchability. The incubator features a 100-egg capacity, automatic temperature and humidity control, cooling systems, and real-time monitoring via mobile devices. It also includes a camera for movement detection, capturing images of hatching eggs, and sending notifications to users. The automatic egg-turning mechanism ensures even temperature distribution. Experimental results show that the incubator maintains optimal temperatures between 37.7°C and 38.8°C, with successful hatching observed on the 19th day. The fuzzy logic AI system effectively manages environmental changes, ensuring a stable hatching process by dynamically adjusting the conditions within the incubator. The user-friendly interface and remote monitoring capabilities provide convenience and efficiency for poultry farmers. This innovative design significantly improves hatch rates and supports the economic productivity of chicken farming, offering practical solutions for modern poultry farming. The integration of this AI technology can lead to higher profitability and sustainability in poultry farming, addressing common challenges such as inconsistent environmental conditions and labor-intensive processes, thus contributing to the advancement of agricultural practices
Realtime Monitoring and Analysis Based on Cloud Computing Internet of Things (CC-IoT) Technology in Detecting Forest and Land Fires in Riau Province Irawan, Yuda; Muzawi, Rometdo; Alamsyah, Agus; Renaldi, Reno; Elisawati, Elisawati; Nurhadi, Nurhadi; Amartha, Mohd Rinaldi; Mitrin, Abdullah; Asnal, Hadi; Hartomi, Zupri Henra
ILKOM Jurnal Ilmiah Vol 15, No 3 (2023)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v15i3.1636.445-454

Abstract

Forest and land fires in Riau are natural disasters that always repeat every time they enter the dry season. The solution of this research is to apply the leading technology of cloud computing internet of things (CC-IoT) to find out more quickly the existence of forest or land fires. This study uses Particle Argon (Photon) to connect to the internet and several IR Fire Detector sensors, DHT22 MQ2 and GPS Neo 6m. Particle Argon can receive input and perform processing so that it is connected using the CC-IoT concept to a web server so the users can monitor land conditions in real time. Based on the test results, it can be concluded that a fire detector using fire parameters (2000 = Normal and 2000 = Danger) , temperature (≤37 = Normal, 38 – 45 = Alert, and 46 = Danger), humidity (≤50 = Dry, 51 = Humid) , smoke (≤ 1700 = Normal, 1700 = Danger), and soil moisture can work well ( 3500 = Dry Moisture Content, 1500 to 3500 = Medium Moisture Content, and 1500 = High Moisture Content). The fire detection tool developed can detect fires in real time and also has a fire early detection function that is useful for anticipating land conditions to prevent fires. The results obtained from the test are that the sensor can read indications of fire, smoke, soil moisture with a success rate of 93% and send location data and sensor values to the website. The use of sensors has their respective roles so that if there is a problem with one of the sensors, the tool has an alternative sensor and can continue to function.
SISTEM PAKAR MENDIAGNOSA PENYAKIT STROKE DENGAN METODE FORWARD CHAINING (Studi Kasus Rumah Sakit Umum Daerah Selasih Pangkalan Kerinci) Irawan, Yuda
RJOCS (Riau Journal of Computer Science) Vol. 7 No. 1 (2021): RJOCS (Riau Journal of Computer Science)
Publisher : Fakultas Ilmu Komputer, Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/rjocs.v7i1.1821

Abstract

Penelitian ini bertujuan membantu masyarakat dalam mendiagnosa atau menangani penyakit pada stroke dengan teknologi artificial intelligence sistem pakar dengan cara memindahkan pengetahuan yang didapat dari pakar di kumpul dalam database yang memiliki aturan-aturan sehingga ketika aturan-aturan yang dipilih dapat menyimpulkan suatu keputusan. proses yang akan di dapat pengguna lebih cepat dan efisien sistem ini dibuat untuk membantu masyarakat dalam menangani penyakit stroke dengan mudah kapan saja dan dimana dengan mengunakan aplikasi berbasis website
IMPLEMENTASI WIRELESS SECURITY MENGGUNAKAN RADIUS MEDIA ACCESS CONTROL AUTHENTICATION PADA SMK NEGERI 3 BENGKALIS Irawan, Yuda; Yulisman; Ordila, Rian; Akbar, Amri
RJOCS (Riau Journal of Computer Science) Vol. 7 No. 1 (2021): RJOCS (Riau Journal of Computer Science)
Publisher : Fakultas Ilmu Komputer, Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/rjocs.v7i1.1823

Abstract

Seiring dengan Perkembangan teknologi akses internet telah mencapai tahapan yang lebih mempermudah penggunaannya dengan memanfaatkan media akses jaringan wireless atau disebut dengan nirkabel, jaringan komputer wireless merupakan teknologi yang sering digunakan diberbagai instansi, perusahaan, cafe, toko,dan lain-lain. Jaringan wireless tidak hanya digunakan pada intsansi saja, tetapi sebagian rumah tangga juga menggunakannya. Masalah yang perlu diperhatikan pada jaringan wireless adalah keamanannya. Apabila keamanan jaringannirkabel tersebut memiliki celah, maka akan mudah dimanfaatkan celah tersebut ole horang yang tidak bertanggung jawab. Hal ini dapat merugikan bagi Instansi yang memiliki jaringan nirkabel tersebut. Salah satunya Sekolah Menengah Kejuruan (SMK) Negeri 3 Bengkalis merupakan sebuah sekolah menengah yang bertempat di Bengkalis. Pada saat ini SMK sudah menggunakan layanan jaringan wireless. Namun permasalahan yang terjadi di SMK saat ini adalah apabila pengguna ingin mengakses internet harus melakukan login terlebih dahulu dan masih bisa membuka situs yang tidak dibenarkan. Hal ini terjadi karena jaringan wireless berada di SMK menggunakan keamanan proxy. Di karenakan itu perlu menerapkan sistem keamanan wireless dengan Radius MAC Authentication sehingga pengguna tidak perlu login ulang saat berpindah tempat dalam satu area. Dengan adanya keamanan jaringan ini diharapkan dapat mempermudah pengguna jaringan wireless. Penelitian ini menghasilkan suatu sistem keamanan jaringan yang telah di konfigurasi dengan mikrotik, Dari beberapa pengujian keamanan wireless yang dilakukan jaringan wireless hanya bisa digunakan oleh pengguna yang terdaftar dan apabila pengguna berpindah tempat, pengguna tidak perlu login ulang.
PEMODELAN DAN ANALISA EMPIRIS SUDUT BELOK RUDDER PADA SISTEM AUTOPILOT KAPAL BERBASIS STM32 Irawan, Yuda; Arfianto, Afif Zuhri; Riananda, Dimas Pristovani
Jurnal 7 Samudra Vol. 9 No. 1 (2024): Jurnal 7 Samudra
Publisher : PPPM - POLITEKNIK PELAYARAN SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54992/7samudra.v9i1.179

Abstract

Dalam beberapa dekade terakhir, teknologi pengendalian kapal telah mengalami perkembangan signifikan yang bertujuan untuk meningkatkan keselamatan dan efisiensi operasional. Sistem autopilot, khususnya, memiliki peran penting dalam menjaga stabilitas dan arah kapal secara otomatis. Penelitian ini bertujuan untuk mengembangkan dan menguji sistem kontrol rudder berbasis STM32 yang mampu mengoptimalkan kinerja rudder dalam mencapai sudut yang diinginkan dengan tingkat error minimal. Pendekatan yang digunakan dalam penelitian ini melibatkan pengembangan model perhitungan yang divalidasi dengan data empiris, serta pengukuran sudut menggunakan busur derajat sebagai alat bantu validasi. Sistem ini dilengkapi dengan proses kalibrasi awal untuk menentukan batas kiri dan kanan rudder, serta menetapkan posisi tengah sebagai titik referensi. Penelitian dilakukan dengan mengonversi masukan sudut ke dalam nilai potensio menggunakan algoritma yang telah dirancang, dan memerintahkan motor stepper untuk menggerakkan rudder sesuai dengan masukan tersebut. Hasil penelitian menunjukkan bahwa sistem kontrol rudder yang dikembangkan mampu mencapai tingkat kesalahan sudut output dibandingkan sudut input sebesar 1,9%, dan kesalahan sudut output dibandingkan dengan sudut pada busur derajat sebesar 3,3%. Kesalahan ini terutama disebabkan oleh ketidakakuratan mekanisme gearbox pada sistem autopilot. Meskipun demikian, sistem yang dikembangkan telah menunjukkan peningkatan presisi dan keandalan dalam pengendalian rudder.
Improved Hybrid Machine and Deep Learning Model for Optimization of Smart Egg Incubator Febriani, Anita; Wahyuni, Refni; Mardeni, Mardeni; Irawan, Yuda; Melyanti, Rika
Journal of Applied Data Sciences Vol 5, No 3: SEPTEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i3.304

Abstract

This research develops a Smart Egg Incubator that integrates IoT technology, fuzzy logic, and the YOLOv9-S Deep Learning model to enhance the efficiency and accuracy of hatching chicken eggs. The system automatically regulates temperature and humidity, maintaining temperature between 34.3°C and 39.5°C and humidity between 57% and 68% with a fuzzy logic success rate of 90%. The YOLOv9-S model enables realtime chick detection and classification with mAP50 of 93.7% and mAP50:95 of 71.3%. Efficiency improvements are measured through the success rate of fuzzy logic and improved detection and classification accuracy. This research also uses CNN for high-accuracy object classification, with model optimization performed using SGD to accelerate convergence and improve accuracy. The results indicate significant potential in improving the egg hatching process. The high accuracy and robustness of the YOLOv9-S model enhance real-time monitoring and decision-making in hatcheries, leading to higher hatching success rates, reduced chick mortality, and increased operational efficiency. Future designs can leverage these technologies to create more intelligent, automated systems requiring minimal human intervention, enhancing productivity and scalability. Additionally, IoT and deep learning integration can extend to other poultry farming areas, such as broiler production and disease monitoring, providing a comprehensive approach to farm management. Future research could focus on integrating the YOLOv10 model for even higher accuracy and efficiency, exploring diverse data augmentation techniques, optimizing fuzzy logic algorithms, and integrating additional sensors like CO2 and advanced humidity sensors to improve environmental regulation. These advancements would benefit not only smart incubator applications but also broader poultry farming areas.
Machine Learning Algorithm Optimization using Stacking Technique for Graduation Prediction Herianto, Herianto; Kurniawan, Bambang; Hartomi, Zupri Henra; Irawan, Yuda; Anam, M Khairul
Journal of Applied Data Sciences Vol 5, No 3: SEPTEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i3.316

Abstract

Graduating on time is crucial for academic success, impacting time, costs, and education quality. Hang Tuah University Pekanbaru (UHTP) is currently struggling to meet its goal of achieving a 75% on-time graduation rate. This study introduces an innovative approach using machine learning techniques, particularly ensemble learning with Stacking Machine Learning Optuna SMOTE (SMLOS), to address this issue. Our primary objective is to enhance data classification accuracy to predict student graduation timelines effectively. We employ algorithms such as K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Decision Tree (C4.5), Random Forest (RF), and Naive Bayes (NB). These were combined with meta-models, including Logistic Regression (LR), Adaboost, XGBoost, LR+Adaboost, and LR+XGBoost, to create a robust prediction model. To address class imbalance, we applied the Synthetic Minority Over-sampling Technique (SMOTE) and utilized Optuna for hyperparameter tuning. The findings reveal that SMLOS with the Adaboost meta-model achieved the highest accuracy of 95.50%, surpassing previous models' performances, which averaged around 85%. This contribution demonstrates the effectiveness of using SMOTE for class imbalance and Optuna for hyperparameter optimization. Integrating this model into UHTP's academic information system facilitates real-time monitoring and analysis of student data, offering a novel solution for promoting a Smart Campus through more accurate student performance predictions. This technique is not only beneficial for predicting student graduation but can also be applied to various machine learning tasks to improve data classification accuracy and stability.
Co-Authors -, Herianto A.A. Ketut Agung Cahyawan W Abdullah Mitrin Achmad Deddy Kurniawan Achmad Nizar Hidayanto Adhitya, Ryan Yudha Aditya Rickyta Adyanata Lubis Afresi Yunita Agnita Utami Agus Alamsyah Ahmad Fauzan Azim Akbar, Amri Akhmad Zulkifli Aldiga Rienarti Abidin Anam, M Khairul Andre Wahyu Novrianto Anisa, Lia Anita Febriani Aprilia, Ulfa Areta Sonya Rahajeng Arfianto, Afif Zuhri Arnawilis Arnawilis Arnawilis Bakhrizal Bambang Kurniawan Bayu Saputra Budy Mustika Debi Setiawan, Debi Desi Rahmawati Devis, Yesica Dhea Arina Ramadhini Dhini Septhya Diandra, Roni Edriyansyah Eka Sabna Elisawati, Elisawati Fachry Abda El Rahman Fatmawati, Kiki Fitri, Imelda Fonda, Hendry Gilang Citra Lenardo Habib Yuhandri, Muhammad Hadi Asnal, Hadi Hafizh Sallam Hamdani Hamdani Hamid, Abdurrahman Hartomi, Zupri Henra Hasnor Khotimah Hayami, Regiolina Hendro Agus Widodo, Hendro Agus heri, Herianto Herianto Herianto Herianto Herianto - Herianto Herianto Herianto Herianto Hidayati Kurnia Fitri Hohashi, Naohiro Irawan, Rina Irwanda Syahputra Jamaris, Muhamad Jenli Susilo Jenni Oinike Br Sitorus Jepisah, Doni Jeri Trio Sentana Junadhi Junadhi Junadhi Junadhi Junadhi, Junadhi Khairunisa Khairunisa Khairunisa, Khairunisa Kharisma Rahayu Kurniawan, Bambang Leonita, Emy Lia Anisa Lubis, Mustopa Husein Lucky Lhaura Van FC, Lucky Lhaura Mardainis Mardeni Mardeni Mardeni, Mardeni Matthijs B Punt Maulita Yulia Sari Mbunwe Muncho Josephine Mbunwe Muncho Josephine Melyanti, Rika Mitrin, Abdullah Mohd Rinaldi Amartha Muhaimin, Abdi Muhamadiah, Muhamadiah Muhammad Bambang Firdaus Muhardi Muhardi - Muhardi Muhardi Muhardi Muhardi Mulya Rispani Mutiara Sari, Ria Naima Belarbi Naima Belarbi Nella Sari Nico Chandra Nopriadi Noratama Putri, Ramalia Nurhadi Nurhazimah Rafiah Octaria, Haryani Oktavia Dewi Ordila, Rian Perkasa, Reza Prihandoko, P Purnomo, Nopi Purwanti, Siti Putra Rahmaddeni Rahmaddeni Rahmaddeni Rahmaddeni Rahmalisa, Uci Rahman, Rudi Refni Wahyuni renaldi, reno Renaldi, Reno Reza Perkasa Rian Ordila Rian Ordila Riananda, Dimas Pristovani Richi Andrianto Rickyta, Aditya Rofiqoh, Ummi Rometdo Muzawi, Rometdo Roni Diandra Rudi Rahman Ruwahida, Dewi Rizani Ruwahida Sabna, Eka Sakroni Indra Gunawan Salsabila Rabbani Saputra, Haris Tri Sarjon Defit Sentana, Jeri Trio Siti Aisyah Siti Aisyah Siti Purwanti Sugiati Suherman Sohor Suherman Suherman Suriandi Suriandi Susanti, Susanti Susi Oustria Simamora Susilo, Jenli Syamsul Arifin Uci Rahmalisa Ulfa Aprilia Utami, Urfi Vindi Fitria Winda Herrianti Manullang Winda Sari Wulan Sari Yesica Devis Yuhandri, Y Yulanda Yulanda Yulanda Yulanda, Yulanda YULISMAN Yulisman, Yulisman Yunior Fernando Zufari, Faisal Zufi Pratama Noviardi Zupri Henra Hartomi