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IMPLEMENTATION OF LOAD BALANCE EQUAL COST MULTI PATH (ECMP) BETWEEN ROUTING PROTOCOL BORDER GATEWAY PROTOCOL (BGP) AND OPEN SHORTEST PATH FIRST (OSPF) USING DUAL CONNECTION Aji Triwerdaya; Dodon Trianto Nugrahadi; Muhammad Itqan Masdadi; Irwan Budiman; Ahmad Rusadi Arrahimi
Journal of Data Science and Software Engineering Vol 1 No 02 (2020)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (601.437 KB)

Currently, Internet is needed by everyone to lighten their work, then a method has been developed to be able to access the internet using 2 ISPs (Internet Service Providers), namely using load balance. This method can perform bandwidth management so that it can balance the bandwidth of 2 ISPs. To support this method, Load Balance Equal Cost Multi Path (ECMP) is used. Another innovation that continues to be developed routing, the process of exchange data packets between different IP networks and to identify the best route to each connected network, that can make routing better by using dynamic routing types, to unify the network if a change occurs of topology by exchanging new topology information with each other on a network using the Open Shortest Path First (OSPF) routing or using the Border Gateway Protocol (BGP). OSPF is an open source routing protocol that is often used[4] and OSPF is a link-state in the routing algorithm. This routing use the Dijkstra or SPF (Short Path First) algorithm to calculate the shortest path from each route. Coinciding with the increase in routers in an area, the information that routers in the same area must have at the same time will increase, then the Border Gateway Protocol (BGP) is the new routing protocol[7]. BGP is a vector-path protocol where each router decides locally the "best AS" line per destination. The local preference attribute is used to set the policy for outgoing traffic. Testing is done by comparing the performance of an ECMP network using OSPF routing and an ECMP network using BGP routing[3]. Testing is done by measuring based on the throughput and data delay parameters using 16, 32, 48 routers. the topology is divided into 3 areas, namely area 1 for user load balance, area 2 for ISP 1 and area 3 for ISP 2. Throughput is used to measure routing performance on the TCP transport protocol and UDP transport protocol. Then, data delay is for measuring the performance of routing on the TCP and UDP transport protocol with the addition of variations. The testing that have been carried out show that the network throughput with OSPF routing (764.13 bps) has a lower performance than the network with BGP routing (818.81 bps) when sending TCP and UDP data, and network delay with OSPF routing (85.61 ms) has a significant increase than the network with BGP routing (89.23 ms) when sending TCP and UDP data.

PELATIHAN OPTIMASI MESIN PENCARI (SEO) PADA KONTEN WEB PKBM TUNAS MELATI PELAIHARI Agustian Noor; Rusadi Arrahimi, Ahmad; Sabella, Billy; Wahyu Sholeha, Eka
Jurnal Pengabdian Kepada Masyarakat (MEDITEG) Vol. 6 No. 2 (2021): Jurnal Pengabdian Kepada Masyarakat (MEDITEG)
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat (P3M) Politeknik Negeri Tanah Laut (Politala)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34128/mediteg.v6i2.92

This service utilizes the steps of the Search Engine Optimizer (SEO) in maximizing the search for website addresses to accelerate recognition and marketing. The output target is the optimization of the Tunas Bangsa website through SEO which includes the ease of finding website addresses for visitors on search engines. The use of automated search engines can lower promotional costs than using traditional and conventional media such as newspapers, radio broadcasts, television, and so on. Website addresses that are used as promotional tools and digital introductions by the Tunas Melati Community Learning Activity Center must be designed properly and correctly, so that they can be an appropriate and optimal promotional tool. This step is followed by website optimization so that it is detected and indexed at the top on search engines like Google. The method used is in the form of steps and the use of SEO plugins on a wordpress-based website. The result of this activity is an optimal website indexing by search engines.

TEKNOLOGI MEMBRAN FILTRASI AIR RAWA/GAMBUT BERBASIS PANEL SURYA UKM PENGOLAH IKAN ASIN DESA MUNING BARU dodon turianto nugrahadi; Totok Wiyanto; Sri Cahyo Wahyono; Ahmad Rusadi Arrahimi; sholih Afif
Jurnal Pengabdian Kepada Masyarakat (MEDITEG) Vol. 7 No. 1 (2022): Jurnal Pengabdian Kepada Masyarakat (MEDITEG)
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat (P3M) Politeknik Negeri Tanah Laut (Politala)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34128/mediteg.v7i1.100

River water and well water are the main sources for the daily water needs for the people of South Kalimantan. However, the peatland water has a muddy and smelly that has an effect on health. This cloudy and smelly condition is due to the condition of the peatlands in the South Kalimantan region. The use of peat water by the community in Muning Baru Village, South Daha, HSU has been carried out for a long time, especially UKM salted fish processing. The quality and quantity of fish production are affected by the quality of clean water. Implementation begins with the design of the filtration membrane, assembly of solar panels, pumps and filtration tubes. It is hoped that this application will support the society towards society 5.0. The results of the implementation are giving the needs of clean water up to 80%, either else NTU 30 become 3.44 NTU, TSS 522 mg/l become 352 mg/l, COD 31.9 mgO2 /l become 6.09 mg02/l.

Machine learning to Detect Palm Oil Diseases Based on Leaf Extraction Features and Principal Component Analysis (PCA) Arrahimi, Ahmad Rusadi; Julianto, Veri; Rahmanto, Oky
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 11, No 1 (2024)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v11i1.659

Palm oil tree is one of the economically important crops that is the backbone of the Indonesian economy. However, palm oil production is often hampered by various diseases. The disease is difficult to detect in the early stages because infected trees often show no symptoms. Therefore, it is necessary to carry out identification and classification to determine whether this palm coconut plant is sick or infected with disease. In this study the disease was identified in palm coconut by identifying it through leaves by modifying the extraction process features using PCA and comparing it with no PCA for sick and healthy types. Subsequently, the classification will be done using SVM (Support Vector Machine) with various treatments such as variation of the features used and the amount of data to be processed in carrying out experiments or tests. The results obtained show that if the feature used for classifying a number of 4 or more then the accuracy value remains at 97%.

PENGOLAHAN AIR GAMBUT MENJADI AIR BERSIH BAGI SANTRI DI PESANTREN NURUL HIJRAH JORONG KALIMANTAN SELATAN Nugrahadi, Dodon Turianto; Wianto, Totok; Wahyono, Sri Cahyo; Gunawan, Gunawan; Azwari, Ayu RianaSari; Arrahimi, Ahmad Rusadi; Apriana, Susi; Utomo, Edy Setyo
Kumawula: Jurnal Pengabdian Kepada Masyarakat Vol 7, No 1 (2024): Kumawula: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/kumawula.v7i1.51325

Pada saat ini kebutuhan akan pengolahan air untuk mendukung perkembangan ekonomi dan kesehatan dialami oleh pondok pesantren. Pondok Pesantren Nurul Hijrah Jorong Kalimantan Selatan menggunakan air dari sumur bor air gambut untuk memenuhi kebutuhan. Air tersebut merupakan air gambut, hal ini disebabkan oleh kondisi daratan di Kalimantan Selatan yang merupakan lahan gambut. Berbagai masalah penggunaan air saat ini diantaranya kebersihan dan kesehatan, seperti meninggalkan noda coklat hasil endapan serta kondisi gatal-gatal kulit yang dialami santri, dengan jumlah lebih 300 santri dan jamaah di Pondok Pesantren Nurul Hijrah Jorong. Hal ini masih merupakan masalah yang harusnya tersolusikan, maka tujuan pengabdian masyarakat ini yaitu upaya untuk meningkatkan kualitas air sumur bor air gambut tersebut sesuai baku mutu air bersih. Metode yang dilakukan yaitu proses pengolahan air yang menggabungkan proses filtrasi, absorpsi dan ultrafiltrasi dengan sistem single flow ultrafiltrasi. Hasil evaluasi berdasarkan laboratorium menunjukkan bahwa terjadi penurunan yaitu nilai jumlah zat terlarut (total dissolved solid/TDS) 0,2%, kekeruhan 25,8%, warna air 63,6%, nitrat 95%, coliform 49,8% serta peningkatan nilai keasaman 2%. Hasil produksi air bersih memiliki kapasitas besar hingga 2400 lt. 80% perwakilan santri dan ustad pengelola mendapatkan pengetahuan dan keterampilan tentang penggunaan dan perawatan teknologi pengolahan air ini. At this time, Islamic boarding schools experience the need for water treatment to support economic development and health. The Nurul Hijrah Islamic Boarding School in Jorong, South Kalimantan, uses water from drilled peat wells to meet its needs. This water is peat water caused by the condition of the land in South Kalimantan, which is peat land. Various problems with water use today include cleanliness and health, such as leaving brown stains from sediment and itchy skin conditions experienced by students, with more than 300 students and congregations at the Nurul Hijrah Jorong Islamic Boarding School. So, this community service aims to improve the water quality of drilled peat wells according to clean water quality standards. The method used is a water treatment process that combines filtration, absorption, and ultrafiltration processes with a single-flow ultrafiltration system. The results of the evaluation based on the laboratory showed that there was a decrease in the value of the total dissolved solids (TDS) 0.2%, turbidity 25.8%, watercolor 63.6%, nitrate 95%, coliform 49.8% and increased acidity value 2%. Besides, clean water production has a large capacity of up to 2400 lt, and the management ustad has knowledge and skills of up to.

Evaluating Random Forest Algorithm: Detection of Palm Oil Leaf Disease Rahmanto, Oky; Julianto, Veri; Arrahimi, Ahmad Rusadi
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4798

This research investigates the application of machine learning techniques for detecting diseases in oil palm leaves, utilizing a dataset of 1,119 images sourced from plantations in the Tanah Laut district. The dataset comprises 488 diseased and 631 healthy leaf samples, which were carefully cropped to isolate leaf areas and labeled with the assistance of domain experts. For feature extraction, both Lab and RGB color spaces were considered, alongside Haralick texture features, resulting in a total of eleven features per pixel. To reduce dimensionality and select relevant features, Principal Component Analysis (PCA) and Random Forest methods were applied. Support Vector Machine (SVM) was subsequently employed for the classification of leaf health status, and model performance was evaluated using accuracy, precision, recall, and F1 score metrics, all derived from a confusion matrix. The study finds that PCA and Random Forest significantly enhance model performance, improving the ability to distinguish between healthy and diseased leaves. These findings provide valuable insights for the development of automated disease detection systems in oil palm plantations, with potential applications in precision agriculture. Additionally, the results suggest pathways for further research into plant disease diagnostics, highlighting the role of advanced machine learning techniques in enhancing crop management and supporting sustainable agricultural practices.

Analysis of the Physical, Chemical and Microbiological parameter of Peat Water Processed by the Single Flow Ultrafiltration Wianto, Totok; Nugrahadi, Dodon Turianto; Wahyono, Sri Cahyo; Gunawan, Gunawan; Azwari, Ayu Riana Sari; Arrahimi, Ahmad Rusadi; Apriana, Susi
Jurnal Fisika Flux: Jurnal Ilmiah Fisika FMIPA Universitas Lambung Mangkurat Vol 21, No 2 (2024): Jurnal Fisika Flux: Jurnal Ilmiah Fisika FMIPA Universitas Lambung Mangkurat
Publisher : Lambung Mangkurat University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/flux.v21i2.18614

Peatlands have a crucial role in the global regulation of climate, the sequestration of carbon, and the conservation of biodiversity. Daily human activities and climate change have caused various environmental changes and ecological relationships for peatlands. An important thing to worry about is the decline in water quality, which harms the health and welfare of local communities that depend on clean water sources and drinking water from natural water. Additionally, the escalating demand for clean water necessitates substantial efforts in processing peatland water resources. The degradation in water quality harms the ecology and health of humans who use it for daily needs. Single Flow Ultrafiltration technology has emerged as a promising water treatment method, showing great potential in treating peat water while maintaining the ecological balance of peatlands. This research aims to evaluate the effectiveness of a combined treatment process consisting of filtration, absorption, microfiltration, and single-flow ultrafiltration. The application of this technology is carried out in the South Kalimantan region, with water processing stages, namely raw water filtration, semi-finished raw water filtration, ultrafiltration, and an ultraviolet irradiation process at the final stage so that the water is ready for consumption. Using both techniques, empirical methodologies were utilized to analyze the results of water quality and production capacity. This study proposes single-flow ultrafiltration to treat peat water for daily use. This research shows that the single-stream ultrafiltration treatment method for peat water gives a better water quality result than ordinary ultrafiltration treatment. This is indicated by the percentage difference in decreasing TDS values by 149%, turbidity by 200%, and color by 500%, increasing pH by 14.9%, decreasing nitrite by 135%

Modified Particle Swarm Optimization on Feature Selection for Palm Leaf Disease Classification Julianto, Veri; Ahmad Rusadi Arrahimi; Oky Rahmanto; Mohammad Sofwat Aldi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 6 (2024): December 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i6.6049

Palm oil plantations in Indonesia face challenges in enhancing productivity and profitability, notably due to pest attacks that reduce production. Early identification and classification of plant conditions, particularly palm oil leaves, are crucial for mitigating losses. This study explores the application of artificial intelligence, specifically computer vision and machine learning, for disease detection. Various machine learning techniques, including Local Binary Pattern (LBP), K-Nearest Neighbors (KNN), and Support Vector Machine (SVM), have been used in different studies with varying accuracy. This research focuses on modifying Particle Swarm Optimization (PSO) for feature selection in identifying diseases in palm oil leaves. The PSO modification combined with logistic regression and Bayesian Information Criterion (BIC) significantly enhances KNN performance. Accuracy improved from 95.75% to 97.85%, while precision, recall, and F1-score reached approximately 98.80%. Additionally, the modified KNN+PSO achieved the shortest computation time of 0.0872 seconds, indicating high computational efficiency. These results demonstrate that the PSO modification not only improves accuracy but also computational efficiency, making it an effective method for enhancing KNN performance in detecting palm oil leaf diseases.

Rancang Bangun Pengering Gabah Berbasis IoT dengan Model Rotary Dryer Noor Amin, Muhammad; Arrahimi, Ahmad Rusadi
Journal Information Technology Trends (JITRENDS) Vol 2 No 02 (2025): Journal Information Technology Trends Volume 02. No 02 Juni 2025
Publisher : mijournal.org

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51817/jitrends.v2i2.37

Pengeringan gabah merupakan proses penting dalam pascapanen untuk menjaga kualitas hasil panen. Metode konvensional seperti penjemuran masih banyak digunakan, namun metode ini memiliki keterbatasan seperti ketergantungan pada cuaca dan waktu pengeringan yang lama. Penelitian ini bertujuan merancang alat pengering gabah berbasis IoT dengan model rotary dryer menggunakan sensor DHT22 untuk pemantauan suhu dan kelembaban secara real-time, ESP32 sebagai pengendali utama, serta hair dryer sebagai pemanas. Data dapat diakses melalui dashboard web. Hasil pengujian menunjukkan alat mampu menurunkan kadar air gabah hingga mencapai standar SNI (14%) dalam waktu rata-rata 22 menit untuk kapasitas 10 kg, lebih efisien dibandingkan metode konvensional.

Evaluating Random Forest Algorithm: Detection of Palm Oil Leaf Disease Rahmanto, Oky; Julianto, Veri; Arrahimi, Ahmad Rusadi
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4798

This research investigates the application of machine learning techniques for detecting diseases in oil palm leaves, utilizing a dataset of 1,119 images sourced from plantations in the Tanah Laut district. The dataset comprises 488 diseased and 631 healthy leaf samples, which were carefully cropped to isolate leaf areas and labeled with the assistance of domain experts. For feature extraction, both Lab and RGB color spaces were considered, alongside Haralick texture features, resulting in a total of eleven features per pixel. To reduce dimensionality and select relevant features, Principal Component Analysis (PCA) and Random Forest methods were applied. Support Vector Machine (SVM) was subsequently employed for the classification of leaf health status, and model performance was evaluated using accuracy, precision, recall, and F1 score metrics, all derived from a confusion matrix. The study finds that PCA and Random Forest significantly enhance model performance, improving the ability to distinguish between healthy and diseased leaves. These findings provide valuable insights for the development of automated disease detection systems in oil palm plantations, with potential applications in precision agriculture. Additionally, the results suggest pathways for further research into plant disease diagnostics, highlighting the role of advanced machine learning techniques in enhancing crop management and supporting sustainable agricultural practices.

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