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All Journal International Journal of Electrical and Computer Engineering Jurnal Computech & Bisnis (e-Journal) Indonesia Symposium on Computing Indonesian Journal on Computing (Indo-JC) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JRSI (Jurnal Rekayasa Sistem dan Industri) JURNAL MEDIA INFORMATIKA BUDIDARMA JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) TELEKONTRAN: Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan JMECS (Journal of Measurements, Electronics, Communications, and Systems) Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Reswara: Jurnal Pengabdian Kepada Masyarakat eProceedings of Engineering LOGIC: Jurnal Penelitian Informatika Proceeding of Community Service and Engagement Journal of Innovation and Community Engagement
Ibnu Asror
Universitas Telkom
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Social Sciences

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Interest Classification on Named Data Network Using the Supervised Learning Method Astuti, Sri; Mayasari, Ratna; Asror, Ibnu
JMECS (Journal of Measurements, Electronics, Communications, and Systems) Vol. 11 No. 1 (2024): JMECS
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/jmecs.v11i1.8100

Abstract

Named Data Network (NDN) is a next-generation network architecture that shifts the traditional data communications paradigm Unlike conventional networks that rely on IP addresses, NDN delivers content based on data names rather than specific locations. In NDN, consumers express their requests by sending interest packets containing content names. These names are then propagated through the network nodes, which forward them to the appropriate destinations. The forwarding strategy in an NDN network plays a crucial role in ensuring efficient data delivery. This strategy includes a set of rules that determine the next hop for each interest packet. These rules are designed to optimize the forwarding process, minimizing delays and improving network efficiency. However, if the forwarding strategy is implemented without accurately identifying the appropriate face (i.e., the network interface) to forward interests toward the producer or the nearest cache node, it can lead to significant delays and packet drops. This, in turn, negatively impacts Quality of Service (QoS) parameters and the overall performance of the NDN network. This study applies supervised learning to classify consumer-requested interests to overcome this issue. This technique leverages several related variables to accurately classify these interests. The outcomes of the conducted research demonstrated that raw data from the mini-NDN output can be processed and transformed into a usable dataset. This data is then utilized to train a classification model with supervised learning. In a scenario with 9 NDN nodes and varying numbers of interests, distributed both uniformly and according to Zipf's law, the Random Forest model performs effectively, achieving an accuracy rate of 86.2% with an error rate of 14.8%.
Lexicon-Based Sentiment Analysis of Indonesian Language Student Feedback Evaluation Firdaus, Raginda; Asror, Ibnu; Herdiani, Anisa
Indonesian Journal on Computing (Indo-JC) Vol. 6 No. 1 (2021): April, 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2021.6.1.408

Abstract

Student feedback for lecturer plays an important role, it used to improve the quality of lecturer in teaching. In general, student feedback consists of two types, quantitative feedback and qualitative feedback. For quantitative feedback, it can easily analyze using statistical calculations, because it contains closed questions with multiple choices. But for qualitative feedback, it is difficult to analyze, because it contains open questions with essay answers. Lecturers can analyze manually, but it takes extensive times and the results can be very subjective. To overcome this problem, sentiment analysis is applied to analyze textual data automatically in order to improve teaching evaluations. This research uses student feedback as dataset, and lexicon approach with InSet Lexicon. In this research, the evaluation result shows that system accuracy is 90.9%.
Klasifikasi Tingkat Kualitas Udara DKI Jakarta Berdasarkan Open Government Data Menggunakan Algoritma Random Forest Nugroho, Adityo; Asror, Ibnu; Wibowo, Yanuar Firdaus Arie
eProceedings of Engineering Vol. 10 No. 2 (2023): April 2023
Publisher : eProceedings of Engineering

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Abstract

Abstrak-Kualitas udara pada kota yang memiliki padat penduduk tinggi dengan banyaknya pabrik industri serta padatnya jalan raya oleh kendaraan seperti DKI Jakarta harus diperhatikan kondisinya. Terdapat banyak data yang muncul mengenai kualitas udara di DKI Jakarta yang selalu menurun disebabkan oleh pencemaran udara. Data yang di dapatkan berasal dari website Jakarta Open Data yang menampilkan Indeks Standar Penecamaran Udara (ISPU) pada setiap harinya. Metode yang digunakan yaitu data mining klasifikasi, karena metode tersebut dapat digunakan untuk mengetahui informasi mengenai pencemaran udara berdasarkan pengolahan data parameter yang ada pada ISPU. Klasifikasi yang dilakukan yaitu menggunakan algoritma random forest. Membuat sebuah model uji pada klasifikasi menggunakan random forest bertujuan untuk mencari hasil terbaik. Hasil dari klasifikasi berdasarkan data Indeks Pencemaran Udara di DKI Jakarta memiliki performa terbaik yang menghasilkan akurasi tertinggi yaitu 90%. Pada kategori Sedang memiliki nilai precision 90,9%, recall 89,28% f1-score 90,09%, dan categori Tidak Sehat memiliki nilai precision 89,09%, recall 90,74%, dan f1-score 89,9%.Kata kunci- kualitas udara, klasifikasi, random forest
Penerapan PCA (Principal Component Analysis) pada Deteksi Outlier untuk Data Text Lestari, Marinda Endi; Asror, Ibnu; Sardi, Indra Lukmana
eProceedings of Engineering Vol. 10 No. 3 (2023): Juni 2023
Publisher : eProceedings of Engineering

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Abstract

Abstrak-Data Mining adalah kegiatan pengumpulan data, pemakaian data historis, untuk menemukan keteraturan pola dalam dataset yang berukuran besar dan mempunyai jumlah yang banyak. Dalam data mining terdapat data yang berbeda dari data pada umumnya yang disebut outlier. Outlier sendiri berkaitan dengan nilai ekstrem, baik ekstrem besar maupun kecil. Adanya data outlier membuat analisis terhadap serangkaian data menjadi bias, atau tidak mencerminkan fenomena yang sebenarnya. Outlier detection digunakan untuk mendeteksi ada atau tidaknya outlier dalam sebuah data. Outlier Detection dapat digunakan untuk mendeteksi data berupa categorical, numeric, maupun data teks.Principal Component Analysis (PCA) merupakan salah satu metode pendeteksian outlier berdasarkan pendekatan statistical. Objek yang dianggap sebagai outlier adalah objek yang memiliki probabilitas yang rendah sehubungan dengan model distribusi probabilitas pada data tersebut. Evaluasi yang digunakan untuk mengetahui performansi sistem yaitu : accuracy, precision, dan recall.Kata kunci-outlier, PCA, outlier detection, data teks
Rekomendasi Sistem terhadap Wisata Alam Gunung dengan Metode Collaborative Filtering Chrisdiyanto, Joshua; Asror, Ibnu; Reditya M, Yusza
eProceedings of Engineering Vol. 10 No. 4 (2023): Agustus 2023
Publisher : eProceedings of Engineering

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Abstract

Wisata alam gunung telah menjadi salah satu tempat hiburan yang saat ini menjadi favorit bagi setiap masyarakat. Jumlah gunung di Indonesia mencapai ratusan gunung yang terbagi di beberapa daerah. Hal ini menjadi kendala bagi pendaki pemula dalam memilih gunung mana yang sesuai dengan kriteria pendaki, terlalu banyak gunung yang ada diindonesia membuat para pendaki bingung dan sering bertanya mengenai rekomendasi gunung mana yang cocok dengan pendakian pertamanya. Wisata alam gunung sudah menjadi salah satu tempat wisata yang banyak di gemari oleh para wisatawan. Namun masalah dalam wisata gunung sendiri masih banyak wisata alam gunung yang kurang menyajikan website tentang gunungnya. Hal ini yang menyebabkan penulis mengambil judul Sistem Rekomendasi terhadap Wisata Alam Gunung dengan Metode Collaborative Filtering. salah satu solusi dari permasalahan ini adalah menggunakan sistem rekomendasi yang memanfaatkan opini dan rating orang lain terhadap wisata alam gunung. Collaborative filtering adalah salah satu pendekatan untuk sistem rekomendasi yang mengevaluasi item menggunakan opini orang lain sistem ini diharapkan dapat memberikan kemudahan bagi pendaki dalam menentukan wisata alam yang dianggap sesuai dengan kriteria (trek/jalur, daerah, Ketinggian) pendaki tersebut.Kata kunci—sistem rekomendasi, wisata alam gunung, collaborativei filtering.
Layer-4 Load Balancer on Programmable Data Plane using IP Hash and Weighted Round Robin Muchlis Ramadhan Usman; Nugroho, Muhammad Arief; Ibnu Asror
LOGIC: Jurnal Penelitian Informatika Vol. 3 No. 2 (2025): Desember 2025
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/logic.v3i2.9897

Abstract

Layer-4 load balancer used in data center to distribute requests coming from client to multiple servers located in data center. There are two requirements to build proper Layer-4 load balancing. The first is ensuring the uniformity of request distribution across multiple servers and connection affinity. IP Hash is a common load balancing algorithm that is used to implement Layer-4 load balancing but can cause load imbalances across multiple servers. Weighted Round-Robin is proposed to prevent load imbalance across multiple servers. The implementation of load balacing is using a programmable data plane rather than additional hardware or software load balancing. The result shows that WRR is able to mitigate load imblance across multiple servers by achieving uniform request distribution. WRR achieves 13% higher throughput but gives 2% higher response times than IP Hash and has less packet loss than IP Hash when handling HTTP requests.
PENYEDIAAN INFRASTRUKTUR JARINGAN PADA MADRASAH IBTIDAIYAH(MI) ASH-SHIDIQ UNTUK MENDUKUNG PROSES BELAJAR MENGAJAR DAN PELAPORAN MADRASAH Ibnu Asror; Sri Astuti; Tora Fahrudin; Yanuar Firdaus; Dawam Dwi Jatmiko Suwawi; Moza Sajidah P
The Proceeding of Community Service and Engagement (COSECANT) Seminar Vol. 3 No. 1 (2023): Prosiding COSECANT : Community Service and Engagement Seminar
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/cosecant.v3i1.7072

Abstract

Kegiatan abdimas ini dilakukan di MI Ash-Shidiq. MI Ash-Shidiq membutuhkan adanya dukungan infrastruktur jaringan untuk proses belajar mengajar dan juga untuk kegiatan operasional harian madaasah. Madrasah memiliki kewajiban untuk melakukan pelaporan setiap bulannya dan juga ujian sekolah juga membutuhkan infrastruktur jaringan supaya proses ujian online dapat berjalan dengan lancar tanpa kendala. Dari hal tersebut kami coba membantu MI Ash-Shidiq dengan mendesainkan dan mengimplementasikan kebutuhan jaringannya. Hasil dari desain dan implementasi jaringan di MI Ash-Shidiq merasa mendapatkan kemudahan-kemudahan dalam kegiatan operasional, jaringan internet yang lebih stabil dan juga telah berhasil melakukan Ujian Online tanpa ada kendala sama sekali.
Design and Implementation of Network Infrastructure at MTSS Salafiyah Al-Falah to Support Digital-Based Education Programs Ibnu Asror; Sri Astuti; Ratna Mayasari; Yanuar Firdaus; Dawam Dwi Jatmiko Suwawi
Journal of Innovation and Community Engagement Vol. 6 No. 1 (2025)
Publisher : Faculty of Smart Technology and Engineering, Universitas Kristen Maranatha, Bandung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/ice.v6i1.9433

Abstract

Currently, in education, all reporting is mandated to be digital-based. Therefore, all reporting related to academic matters, school activities, and operations must use information systems. This community service activity is conducted at MTSS Salafiyah Al-Falah a madrasah type of school. Based on the initial survey conducted at the school, it was found that the school needs computer internetworking infrastructure support for the teaching and learning process as well as for school operational activities, such as recording school, student, and teacher data. MTSS Salafiyah Al-Falah must report monthly, and school exams also need a network infrastructure to ensure that online exams can run smoothly without issues. To address these problems, the community service team from Telkom University offered a solution to the school by designing and implementing the necessary network infrastructure. The network design and implementation results at MTSS Salafiyah Al-Falah provided ease in operational activities, a more stable internet network, and the successful execution of online exams without any issues.
Co-Authors Adityo Nugroho, Adityo Agustyna Diyah Sri Kamulyan Ahmad Marzuqi Ainun Nisa Alya Ghaitsa Rizky Pertiwi Anisa Herdiani Arie Ardiyanti Arie Ardiyanti Suryani Asri Inna Khoirun Nissa Atik Zilziana Muflihati Noor Aufa Eka Putri Lesatari Candra Widya Iswara Candra Widya Iswara, Candra Widya Chrisdiyanto, Joshua Dana Kusumo Dawam Dwi Jatmiko Suwawi Delvine Toleng Edyt Daryfayi Eka Himawanto Eko Darwiyanto Erricson Hardiansyah Faris Muhammad Firdaus Anggraini Firdaus, Raginda Gede Agung Ari Wisudiawan Gede Agung Ary Wisudawan Gregorius Pradana Satriawan Hafiyy Viazola Aziz I Putu Prima Ananda Ilham Akbar Indra Lukmana Sardi Jiddy Abdillah Jihan Ratnasari1 Kemas Rahmat Saleh Wiharja Kiki Adhinugraha Kiki Adinugraha Kiki Maulana Adhinugraha Laksitowening, Kusuma Ayu Lestari, Marinda Endi Markus Bernard1 Miftahul Adnan Rasyid Moch Arif Bijaksana Mohamad Fauzy Mohammad Fauzy Moza Sajidah P Muchlis Ramadhan Usman Muhamad Hamda Muhammad Arief Nugroho Muhammad Rezaldy Muhammad Thomy Farhan Murahartawaty Murahartawaty Paramita Mayadewi Pramudita Oktaviani Puput Fajriati Tri S Rachmadini P Utami Raginda Firdaus Rahmi Rohdiniyah Ramadhan Usman , Muchlis Ramadhyni Rifani Ratna Mayasari Reditya M, Yusza Rio Pratama Seno Anunggroho Shaufiah . Shinta Yulia Puspitasari Sri Astuti Sri Astuti Tody Ariefianto Wibowo Tora Fahrudin Yanuar Firdaus Yanuar Firdaus Yanuar Firdaus Arie Wibowo