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All Journal Jurnal Pekommas Jurnal Teknologi Informasi dan Ilmu Komputer JOIV : International Journal on Informatics Visualization Journal of Data Science and Its Applications Journal of Informatics, Information System, Software Engineering and Applications (INISTA) Journal of Informatics and Communication Technology (JICT) Journal of Informatics and Communication Technology (JICT)
Ade Rahmat Iskandar
Institut Teknologi Telkom Jakarta, West Jakarta, 11710, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Languange, Linguistic, Communication & Media Mathematics

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Implementasi Virtual Private Network Pada Jaringan Multi Protocol Label Switching Traffic Engineering ade Nurhayati; Risnu Pradana Holiyastuta; Ade Rahmat Iskandar
Journal of Informatics and Communication Technology (JICT) Vol. 2 No. 1 (2020): Juni
Publisher : PPM Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52661/j_ict.v2i1.47

Abstract

Along with the development of telecommunications technology, we need a network that provides traffic services to send data to distant places quickly but does not forget about security, some solutions are the Multi Protocol Label Switching method, Virtual Private Network, and Traffic Engineering. MPLS VPN TE is a combination of several methods that can be used for this problem. In this research, simulation is carried out using GNS3 software and the results of the analysis are carried out using a Wireshark software. This scenario uses the measurement load using FTP and HTTP. The measurement parameters of QoS are transfer time, throughput, delay, and packet loss ratio. The measurement results show that QoS value for transfer time of 25 MB file is 16.94s, and transfer time for HTTP is 4.2 s. The Throughput of 25 MB file is 1.606MB/s, and throughput for HTTP is 5.6 MB/s. The Delay of 25MB file is 1.22 ms, and delay HTTP is 105.37 ms
ONLINE COLABORATION SEBAGAI UPAYA MENINGKATKAN PRODUKTIFITAS KERJA DALAM MASA WORK FROM HOME (WFH) Ade Rahmat Iskandar; Hary Nugroho
Journal of Informatics and Communication Technology (JICT) Vol. 4 No. 1 (2022)
Publisher : PPM Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52661/j_ict.v4i1.124

Abstract

Dalam masa Lock down, banyak instansi-instansi pemerintah, perusahaan badan usaha milik negara (BUMN), maupun perusahaan swasta lainnya memberlakukan proses kerja yang dinamakan work from home (WFH) atau bekerja dari rumah. Penelitian ini dilaksanakan dari tanggal 16 Maret samapai dengan 17 April 2020 bagi para pegawai Akademi Telkom selama masa bekerja dari rumah, untuk menghindari penyebaran virus Corona atau covid-19 yang sedang melanda di Indonesia dan negara-negara lainnya. Metode yang dilakukan dalam penelitian ini adalah explorasi terhadap beberapa pola kerja WFH menggunakan beberapa tipe online colaboration. Luaran dari penelitian ini adalah penggunaan media Whatsapp, Zoom dan wfh’s website yang paling banyak digunakan selama masa bekerja dari rumah bagi para pegawai Akademi Telkom Jakarta.
Perbandingan Akurasi Prediksi Kerusakan CPU Antara Teknik Certainty Factor dan Forward Chaining Laksana, Tri Ginanjar; Iskandar, Ade Rahmat; Ahmad, Wan Nooraishya Wan
Jurnal Pekommas Vol 9 No 1 (2024): Juni 2024
Publisher : Sekolah Tinggi Multi Media “MMTC” Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jpkm.v9i1.5531

Abstract

The CPU plays a vital role in determining the performance of a computer system in contemporary computing. If the CPU sustains damage, it may result in significant interruption to the computer's functioning. This study presents a computational technique that aims to enhance the accuracy of CPU damage predictions. The system utilises fundamental knowledge of damage diagnosis and is validated via evaluating 11 early damage symptoms that are often seen. The Certainty Factor and Forward Chaining approaches ascertain CPU damage by quantifying the degree of truth in the expert's opinion conclusions via a comparison of the symptoms of harm. The second algorithm assesses the confidence level in a development by considering the weight assigned to the system by two parties: the user and the expert. The suggested algorithm yields the mean accuracy of the certainty factor approach in diagnosing computer damage utilising the constructed system. The diagnostic system has a precision rate of 84.9%, indicating that 9 out of 10 diagnoses made by the system align with those made by an expert. Next, the outcomes of the forward chaining algorithm test. All questions about symptoms were answered affirmatively, except for one test which had a negative response. A total of 39 diagnoses were obtained, with an average value of 82.9%. The study findings indicate that the suggested confidence factor method is more suited for use in embedded systems or web-based applications, however it is constrained by low processing.
Sistem Pakar Diagnosis Penyakit Ikan Gurami (Osphronemus Goramy) Menggunakan Case Based Reasoning Saraswati, Adinda Rahmi; Saintika, Yudha; Thohari, Afandi Nur Aziz; Iskandar, Ade Rahmat
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 4: Agustus 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020701953

Abstract

Ikan Gurami (Osphronemus Goramy) merupakan ikan yang banyak dibudidayakan dan dikomsumsi masyarakat ini menjadi sektor unggulan di beberapa wilayah kabupaten Banyumas. Ikan gurami yang dibudidayakan oleh masyarakat Banyumas, sebenarnya bukan tanpa hambatan. Salah satu hambatan bagi peternak gurami adalah penyakit yang disebabkan oleh bakteri. Pada penelitian ini penulis membuat sistem pakar untuk mendiagnosis penyakit ikan Gurami yang disebabkan bakteri. Penelitian ini menggunakan metode Case Based Reasoning dan Similarity Nearest Neighbor untuk mendapatkan solusi yang terbaik dari kasus yang di identifikasi. Metode tersebut membandingkan antara kasus lama dengan kasus baru dan menghitung suatu nilai similarity kasus. Nilai similarity tertinggi dapat dijadikan kesimpulan untuk kasus yang paling mirip dengan diagnosa pakar. Sehingga dari kedua metode tersebut dapat dihasilkan sistem pakar yang dapat mendiagnosis dan menganalisis sesuai dengan nilai kemiripan gejala terhadap penyakit, serta menampilkan solusi penanganan dari penyakit yang didiagnosis. Hasil pengujian antar kasus dan sistem menggunakan perhitungan similarity mencapai nilai terbaik yaitu 100%. Hasil pengujian akurasi sistem untuk diagnosis yang sesuai dengan pikiran pakar, memperoleh hasil sebesar 93,33% dari 30 kasus yang diuji dengan sistem. Kesimpulan dari hasil tersebut adalah sistem dapat dikatakan layak untuk mendiagnosis penyakit Gurami yang disebabkan bakteri sesuai dengan yang dipikirkan pakar. AbstractGurami (Osphronemus Goramy) is a fish that is widely cultivated and consumed by the community. This fish is a leading sector in several regions of Banyumas district. Gouramy which is cultivated by the Banyumas people, is actually not without obstacles. One obstacle for gouramy breeders is a disease caused by bacteria. Reporting from the online news portal, circulating in February 2018 circulated that news about Gurami farmers was losing money because thousands of broodstock fish that had been raised to death were attacked by bacterial diseases, namely Aeromoniasis. Experts who handle this are limited, namely only 2 people in the Banyumas Regency. In this study the authors made an expert system to diagnose Gurami fish disease caused by bacteria. This study uses the Case Based Reasoning (CBR) and Nearest Neighbor methods used to get the best solution from the identified case. The CBR method compares the old case with the new case and calculates a case similarity value. The system was built with 13 symptoms and 3 Gurami diseases caused by bacteria. Each symptom each has a weight of 5, 3, and 1. The highest similarity value can be used as a conclusion for the case most similar to the expert diagnosis. So that from these two methods an expert system can be produced that can diagnose and analyze according to the similarity of symptoms to the disease, as well as display solutions to the treatment of diagnosed diseases. The test results are between cases and the system uses the similarity calculation to achieve the best value of 100%. The results of the system accuracy test for diagnoses that are in accordance with the expert's mind, obtained results of 93.33% from 30 cases tested with the system. The conclusion of these results is that the system can be said to be feasible to diagnose Gurami disease caused by bacteria according to what experts think.
Simultaneous Hydroponic Nutrient Control Automation System Based on Internet of Things Adidrana, Demi; Iskandar, Ade Rahmat; Nurhayati, Ade; Suyatno, -; Ramdhani, Mohamad; Adam, Kharisma Bani; Ardianto, Rizki; Ekaputri, Cahyantari
JOIV : International Journal on Informatics Visualization Vol 6, No 1 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.1.865

Abstract

Hydroponic is one of the solutions of gardening methods using water as a nutrition medium. Usually, maintaining hydroponic plant quality and water nutrients are done manually and require human efforts, such as the degree of acidity or wetness (pH), TDS (Total Dissolved Solids), and nutrient temperature. With the Internet of Things technology, we can automate hydroponic control by measuring the nutrients' TDS, pH, and temperature values and controlling water nutrition by pump nutrition needs for hydroponic plants. This research uses the NFT (Nutrient Film Technique) for the hydroponic system and uses lettuce as the nutrition parameter. The lettuce parameters are pH, TDS, and Water Temperature equal to the sensor we used in the proposed IoT system. The condition has 27 classifications, and we use this classification as a reference in decision-making, using the K-Nearest Neighbor (KNN) algorithm to activate the actuator. We improve the simultaneous actuator from previous research with specified intervals and duration to achieve ideal nutritional conditions. The other improvement is that we collect more data and more testing times. The accuracy was 91.2%, with k = 3. From the evaluation results, the accuracy of KNN is quite high and has an advantage, which has better accuracy than the other algorithms and can activate actuator simultaneously. We conclude that the hydroponic nutrient automation system using the Internet of Things method is ready for real planting use with this improvement.
Co-Authors - Suyatno Ade Nurhayati Ade Nurhayati, Ade Afandi Nur Aziz Thohari, Afandi Nur Aziz Ahmad Fauzi Maryadi Ahmad, Wan Nooraishya Wan Apri Junaidi, Apri Ardianto, Rizki Ari Purno Asep Herman Cahyantari Ekaputri Demi Adidrana Hary Nugroho Kharisma Bani Adam Mohamad Ramdhani Risnu Pradana Holiyastuta Saraswati, Adinda Rahmi Tri Ginanjar Laksana Yudha Saintika