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VOIP TECHNOLOGY SIMULATION BASED ON HYBRID FIBER COAXIAL CABLE Suryaputra Paramita, Adi
Proceedings of KNASTIK 2012
Publisher : Duta Wacana Christian University

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This Research aims to determine how the implementation of the Hybrid FiberCoaxial (HFC) network for Voice Over Internet Protocol (VOIP), as is well-knownthat these days VOIP networks increasingly widespread use as an alternative in thefield of communication, in building a VOIP network would need an infrastructure Agood network and reliable, one important factor is the network speed andbandwidth required, in this study will be tested how the implementation of the use ofHFCs for VOIP networks, and the results of existing trials indicate that HFCprovides the smallest delay compared to another medium transmission, from theresult can be seen that at present one of the medium best transmission forimplementing a VOIP network is a Hybrid Fiber Coaxial

PERANCANGAN INTEGRASI TEKNOLOGI OPEN SOURCE PADA SISTEM INFORMASI PROGRAM STUDI TEKNIK INFORMATIKA UNIVERSITAS CIPUTRA Paramita, Adi Suryaputra
Proceedings of KNASTIK 2009
Publisher : Duta Wacana Christian University

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Sistem Informasi pada saat ini adalah suatu kebutuhan wajib bagi tiap institusi, karena hal inilah sebuah SistemInformasi harus dirancang dengan baik agar informasi yang masuk dan keluar bisa dikelola dengan baik dan efektif. Salahsatu upaya untuk membuat informasi yang dikelola bisa efektif adalah dengan melakukan integrasi sistem yang ada. ProgramTeknik Informatika Universitas Ciputra saat ini memiliki 3 aplikasi untuk Sistem Informasi yaitu WikiIFT sebagai saranapenampung aspirasi dari dosen dan mahasiswa, PortalIFT sebagai website Program Studi dan E-Learning sebagai saranabelajar mengajar secara onlineKetiga aplikasi tersebut menggunakan teknologi opensource dan masih berdiri secara sendiri-sendiri, dengansemakin bertambahnya waktu dan semakin banyaknya informasi yang beredar saat ini, dirasa perlu adanya integrasi ketigateknologi tersebut agar tidak terjadi adanya duplikasi informasi yang ada pada ketiga sistem tersebut, salah satu bagian yangdimungkinkan untuk diintegrasikan adalah username dan password untuk tiap user pada aplikasi-aplikasi tersebut, integrasiyang dimungkinkan adalah dengan meracang sistem single sign on dalam integrasi ketiga aplikasi tersebut

Improving K-NN Internet Traffic Classification Using Clustering and Principle Component Analysis Adi Suryaputra Paramita
Bulletin of Electrical Engineering and Informatics Vol 6, No 2: June 2017
Publisher : Institute of Advanced Engineering and Science

K-Nearest Neighbour (K-NN) is one of the popular classification algorithm, in this research K-NN use to classify internet traffic, the K-NN is appropriate for huge amounts of data and have more accurate classification, K-NN algorithm has a disadvantages in computation process because K-NN algorithm calculate the distance of all existing data in dataset. Clustering is one of the solution to conquer the K-NN weaknesses, clustering process should be done before the K-NN classification process, the clustering process does not need high computing time to conqest the data which have same characteristic, Fuzzy C-Mean is the clustering algorithm used in this research. The Fuzzy C-Mean algorithm no need to determine the first number of clusters to be formed, clusters that form on this algorithm will be formed naturally based datasets be entered. The Fuzzy C-Mean has weakness in clustering results obtained are frequently not same even though the input of dataset was same because the initial dataset that of the Fuzzy C-Mean is less optimal, to optimize the initial datasets needs feature selection algorithm. Feature selection is a method to produce an optimum initial dataset Fuzzy C-Means. Feature selection algorithm in this research is Principal Component Analysis (PCA). PCA can reduce non significant attribute or feature to create optimal dataset and can improve performance for clustering and classification algorithm. The resultsof this research is the combination method of classification, clustering and feature selection of internet traffic dataset was successfully modeled internet traffic classification method that higher accuracy and faster performance.

Analisis Sentimen Pada Maskapai Penerbangan di Platform Twitter Menggunakan Algoritma Support Vector Machine (SVM) Hendry Cipta Husada; Adi Suryaputra Paramita
Teknika Vol 10 No 1 (2021): Maret 2021
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v10i1.311

Perkembangan teknologi saat ini telah memberikan kemudahan bagi banyak orang dalam mendapatkan dan menyebarkan informasi di berbagai social media platform. Twitter merupakan salah satu media yang kerap digunakan untuk menyampaikan opini sebagai bentuk reaksi seseorang atas suatu hal. Opini yang terdapat di Twitter dapat digunakan perusahaan maskapai penerbangan sebagai parameter kunci untuk mengetahui tingkat kepuasan publik sekaligus bahan evaluasi bagi perusahaan. Berdasarkan hal tersebut, diperlukan sebuah metode yang dapat secara otomatis melakukan klasifikasi opini ke dalam kategori positif, negatif, atau netral melalui proses analisis sentimen. Proses analisis sentimen dilakukan dengan proses data preprocessing, pembobotan kata menggunakan metode TF-IDF, penerapan algoritma, dan pembahasan atas hasil klasifikasi. Klasifikasi opini dilakukan dengan machine learning approach memanfaatkan algoritma multi-class Support Vector Machine (SVM). Data yang digunakan dalam penelitian ini adalah opini dalam bahasa Inggris dari para pengguna Twitter terhadap maskapai penerbangan. Berdasarkan pengujian yang telah dilakukan, hasil klasifikasi terbaik diperoleh menggunakan SVM kernel RBF pada nilai parameter ð¶(complexity) = 10 dan ð›¾(gamma) = 1, dengan nilai accuracy sebesar 84,37% dan 80,41% ketika menggunakan 10-fold cross validation.

Faktor-faktor Penting Dalam Penyampaian Pelatihan Atau Workshop Pemrograman Secara Daring Laura Mahendratta Tjahjono; Adi Suryaputra Paramita
Teknika Vol 10 No 3 (2021): November 2021
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v10i3.392

Pelatihan dalam bentuk pembelajaran melalui daring kini semakin sering dilakukan, terutama di bidang pemrograman yang merupakan dasar utama di rumpun ilmu komputer. Salah satu hal yang mendorong pelaksanaan pembelajaran daring ini adalah situasi global yang mengharuskan pembatasan jarak akibat adanya pandemi Covid-19. Kemajuan teknologi berupa penyebaran jaringan internet dan ketersediaan berbagai aplikasi yang menjadi penunjang pembelajaran daring ini. Hal ini juga dibantu dengan tersedianya berbagai aplikasi lain yang bisa membantu untuk pengajaran dalam bentuk presentasi maupun untuk penilaian ujian yang siap digunakan untuk pembelajaran daring. Kemajuan teknologi ini tentunya merupakan hal yang baik, namun ternyata masih banyak kendala yang dihadapi bagi para peserta pembelajaran daring untuk mengadopsi teknologi tersebut. Berdasarkan permasalahan tersebut dirumuskan sebuah rumusan masalah untuk penelitian ini yaitu bagaimana melakukan identifikasi faktor-faktor yang mempengaruhi kesuksesan proses pelatihan pemrograman yang dilakukan secara daring? Dan Faktor-faktor apa yang berdampak pada pemahaman materi bagi peserta pelatihan? Proses identifikasi faktor-faktor yang dapat mendorong kesuksesan pelatihan berbasis online merupakan fokus dari penelitian ini. Langkah awal adalah dengan melakukan proses pengumpulan data menggunakan survei dan kuesioner yang sudah disusun berdasarkan pada metode Technology Acceptance Model (TAM), kemudian data dianalisis berdasarkan statistika deskriptif. Penelitian ini berhasil melakukan identifikasi bagaimana seharusnya pelatihan berbasis daring dilakukan dengan efektif berdasarkan faktor-faktor penting yang sudah teridentifikasi.

Improving K-NN Internet Traffic Classification Using Clustering and Principle Component Analysis Adi Suryaputra Paramita
Bulletin of Electrical Engineering and Informatics Vol 6, No 2: June 2017
Publisher : Institute of Advanced Engineering and Science

K-Nearest Neighbour (K-NN) is one of the popular classification algorithm, in this research K-NN use to classify internet traffic, the K-NN is appropriate for huge amounts of data and have more accurate classification, K-NN algorithm has a disadvantages in computation process because K-NN algorithm calculate the distance of all existing data in dataset. Clustering is one of the solution to conquer the K-NN weaknesses, clustering process should be done before the K-NN classification process, the clustering process does not need high computing time to conqest the data which have same characteristic, Fuzzy C-Mean is the clustering algorithm used in this research. The Fuzzy C-Mean algorithm no need to determine the first number of clusters to be formed, clusters that form on this algorithm will be formed naturally based datasets be entered. The Fuzzy C-Mean has weakness in clustering results obtained are frequently not same even though the input of dataset was same because the initial dataset that of the Fuzzy C-Mean is less optimal, to optimize the initial datasets needs feature selection algorithm. Feature selection is a method to produce an optimum initial dataset Fuzzy C-Means. Feature selection algorithm in this research is Principal Component Analysis (PCA). PCA can reduce non significant attribute or feature to create optimal dataset and can improve performance for clustering and classification algorithm. The resultsof this research is the combination method of classification, clustering and feature selection of internet traffic dataset was successfully modeled internet traffic classification method that higher accuracy and faster performance.

Rancang Bangun Sistem Informasi Afiliasi Penjualan Tiket Seminar berbasis Website menggunakan Framework Laravel Dimas Kurnia Pratama; Adi Suryaputra Paramita
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 1: Februari 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

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Penjualan tiket sebuah acara dilakukan secara konvensional adalah dengan proses pertemuan antara penjual dan pembeli. Proses konvensional tersebut memiliki beberapa kendala, dimulai dari kontrol hasil penjualan tiket pada tiap tenaga penjual dan perhitungan pembagian hasil dari penjualan tiket (afiliasi). Kegiatan yang diselenggarakan di Indonesia sangat banyak mulai dari seminar, workshop dan camp. Dimana pada kegiatan tersebut membutuhkan data peserta pada saat proses pendaftaran, data tersebut diperlukan untuk pembuatan sertifikat pada akhir kegiatan. Kemajuan penggunaan teknologi internet pada sebagian besar masyarakat yang berada pada kota-kota besar pada saat ini sudah menjadi kebutuhan sehari-hari. Meninjau dari hal tersebut, teknologi internet dapat dimanfaatkan dengan untuk perhitungan afiliasi penjualan tiket acara pada internal perusahaan, sehingga mempermudah tenaga penjual untuk mengetahui akumulasi hasil yang didapat. Pada penelitian ini akan dikembangkan sebuah sistem penjualan tiket berbasis website sebagai sistem afiliasi penjualan tiket untuk mempermudah perhitungan dan kontrol hasil penjualan. Sistem yang dibangun menggunakan Framework Laravel dimana Framework tersebut berbasis PHP yang open source dan memiliki konsep model-view-controller. Sistem juga menggunakan database yang berfungsi menampung data-data acara, lokasi, tanggal dan konfirmasi peserta. Tujuan dari penelitian ini adalah sistem afiliasi diharapkan dapat menjadi solusi bagi penyelenggara acara dapat menggunakan sistem ini untuk membantu dalam perhitungan afiliasi penjualan tiket. Hasil akhir dari penelitian ini, sistem afiliasi mampu menjembatani kebutuhan penyelenggara acara dan penjual lepas dalam perhitungan penjualan tiket acara. AbstractConventional way to sell a ticket is by direct meeting with a customer. However there has been an obstacle starting from monitoring the result of ticket sales to every salesperson and do the calculation of revenue share from ticket sales (affiliation). Workshop training event that been held in Indonesia is numerous, whether it's a talkshow, workshop or camp. Where this workshop event need the data of participant at registration, which will used as a certificate submission at the end of the event. For the most part of indonesian especially big city, internet usability has became a daily part of their life. According to those factor, intenet usability and technology equity can be use as internet usability to calculate event ticket sales affiliation at internal company. Thus facilitate salesperson to understand the accumulation of the ticket sales. System that develop using web application as ticket sales affiliation system to simplify the calculation and monitoring sales result.To develop the system, researcher used laravel framework which it is a ipen source framework based on PHP languange, using a model view controller concepts. Systems also used database to save the event data, location, date and participant confirmation. The purpose of this research is affiliation system that hopefully can be a solution to all event entrepreneur to help calculate the ticket sales affiliation. Based on research result, affiliation system is able to mediate the needs between eo and sales in event ticket sales calculation.

Improving K-NN Internet Traffic Classification Using Clustering and Principle Component Analysis Adi Suryaputra Paramita
Bulletin of Electrical Engineering and Informatics Vol 6, No 2: June 2017
Publisher : Institute of Advanced Engineering and Science

K-Nearest Neighbour (K-NN) is one of the popular classification algorithm, in this research K-NN use to classify internet traffic, the K-NN is appropriate for huge amounts of data and have more accurate classification, K-NN algorithm has a disadvantages in computation process because K-NN algorithm calculate the distance of all existing data in dataset. Clustering is one of the solution to conquer the K-NN weaknesses, clustering process should be done before the K-NN classification process, the clustering process does not need high computing time to conqest the data which have same characteristic, Fuzzy C-Mean is the clustering algorithm used in this research. The Fuzzy C-Mean algorithm no need to determine the first number of clusters to be formed, clusters that form on this algorithm will be formed naturally based datasets be entered. The Fuzzy C-Mean has weakness in clustering results obtained are frequently not same even though the input of dataset was same because the initial dataset that of the Fuzzy C-Mean is less optimal, to optimize the initial datasets needs feature selection algorithm. Feature selection is a method to produce an optimum initial dataset Fuzzy C-Means. Feature selection algorithm in this research is Principal Component Analysis (PCA). PCA can reduce non significant attribute or feature to create optimal dataset and can improve performance for clustering and classification algorithm. The resultsof this research is the combination method of classification, clustering and feature selection of internet traffic dataset was successfully modeled internet traffic classification method that higher accuracy and faster performance.

ARSITEKTUR SISTEM INFORMASI TERINTEGRASI UNTUK DATA JEMAAT LINGKUP REGIONAL PADA GEREJA X Adi Suryaputra Paramita
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 9 No 1 (2022): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v9i1.1665

The development of technology presents challenges for non-profit organizations such as churches. Indirectly churches are required to be more organized and present accurate data and carry out an in-depth analysis of the condition of the church congregation. Church X has 40 local churches in regional areas spread across several East Java and Bali cities such as Surabaya, Malang, Kediri, Tuluagung, Sidoarjo, and Denpasar. In providing effective services to the local congregation, Church X needs to create an integrated information system for congregational data management and the information system used to see the current condition of the congregation in all local churches so that effective and targeted services can be carried out. In this study, an administrative information system model for integrated congregational data management in Church X will be designed, an information system designed to be web-based. It is easy to implement and does not require investment in expensive information and communication technology equipment. The integrated information system model will be built using microservices. Through this model, an Information System model will be obtained that can assist the process of collecting data on congregations in the regional church X while maintaining data privacy for each local church.

Model Sistem Informasi Penilaian Rekan Satu Kelompok Secara Kolaboratif Untuk Pembelajaran Berbasis Proyek Adi Suryaputra Paramita
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 9 No 2 (2022): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v9i2.1493

Project-based learning is one of the learning models that is currently considered suitable for Engineering-based study programs, where in project-based learning it is expected that students can produce a product that can be prepared through a collaborative process. The resulting product certainly needs to be assessed at the end of the semester, in this learning model it is hoped that the assessment process will also be carried out collaboratively, so that the research process can be carried out properly and comprehensively, it is necessary to create an integrated information system model that can adopt these needs. The information system is also a solution during the COVID-19 pandemic, which causes not all lecturers to meet and gather in one place, with this information system assessment can be done online without the need to meet physically. This information system is built based on web and mobile applications, making it easier to access without any geographical and location restrictions. The result of this research is an Information System model for a collaborative assessment process for project-based learning that can be accessed from anywhere.

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