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All Journal Jurnal Ilmiah Informatika Komputer JIKO (Jurnal Informatika dan Komputer) JURNAL MEDIA INFORMATIKA BUDIDARMA JURNAL TEKNOLOGI DAN OPEN SOURCE Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) CCIT (Creative Communication and Innovative Technology) Journal Indonesian of Health Information Management Journal (INOHIM) ICIT (Innovative Creative and Information Technology) Journal JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Health Sains Journal of Intelligent Computing and Health Informatics (JICHI) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Universal Raharja Community (URNITY Journal)
Noviandi Noviandi
Universitas Esa Unggul, Jakarta
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Environmental Science Health Professions Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary

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IMPLEMENTASI KERNEL DENSITY PADA ANALISA DAERAH RAWAN KECELAKAAN LALU LINTAS PROVINSI DKI JAKARTA Respati Irfan Alrasyid Sartavie; Noviandi Noviandi; Arif Arfan Dwi Cahyo; Saipudin Anwar
Jurnal Ilmiah Informatika Komputer Vol 27, No 2 (2022)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/ik.2022.v27i2.6600

Abstract

Provinsi DKI Jakarta setiap tahunnya memiliki tingkat kecelakaan lalu lintas yang cukup tinggi. Berdasarkan kecelakaan periode januari 2019 hingga Desember 2021 mencapai 9524 baris data. Penelitian ini menyajikan informasi daerah rawan kecelakaan menggunakan metode Kernel Density. Atribut yang digunakan untuk penelitian ini yaitu tanggal kejadian, instansi yang menangani, identitas korban kecelakaan, sifat kecelakaan, dan kendaraan yang terlibat kecelakaan. Tahapan penelitian sesuai dengan ruang lingkup yang akan dilakukan yaitu: Data Preprocessing Kernel Density Estimation (KDE), Incremental Spatial Autocorrelation, dan Hotspot Analysis. Proses penelitian dari pengumpulan data kecelakaan, data pre processing, menjalankan Kernel Density Estimation, mendapatkan visualisasi daeran rawan kecelakaan, menjalankan Spation Join, menjalankan Hotspot Analysis, mendapatkan Hotspot Kecelakaan, mendapatkan urutan Hotspot Kecelakaan. Berdasarkan hasil implementasi Kernel Density pada daerah rawan kecelakaan yang dilakukan, penulis berhasil mendapatkan daerah rawan kecelakaan tertinggi di Provinsi DKI Jakarta yaitu 33,33% ruas jalan Jatinegara Timur merupakan daerah rawan kecelakaan, selanjutnya pada Jalan Jendral Basuki Rahmat 25,93% pada ruas jalan merupakan daerah rawan kecelakaan, dan pada 20% ruas jalan DI Panjaitan adalah daerah rawan kecelakaan.
Decision Support System for Internet Service Provider Selection with Weight Product Method Noviandi Noviandi; Ray Fadly Franata; Ervan Jefferson Bany; Septyanto Harry Nugroho
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol 5 No 2 (2022): Jurnal Teknologi dan Open Source, December 2022
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v5i2.2544

Abstract

People's need for internet connection is a must nowadays, as everyone surely performs all activities through the internet. All activities require internet connection, be it work, lectures, gaming, household payments, shopping and many other activities that are done online. However, because people still rely on the experiences of other users when choosing Internet providers, it is difficult to find a fiber Internet service provider whose quality of service meets one's needs. The decision support system can help people choose an Internet service provider efficiently. The decision support system for fiber optic Internet service provider selection uses the weighted product method, which is one of the methods in the decision support system. The weighted product method is considered suitable to determine the best fiber optic internet service provider in North Jakarta with the appropriate weighting. The stages of the weighted product method include determining the priority value of each criterion, calculating the weight of the criterion, calculating the vector Si, calculating the vector Vi, and making the decision based on the results of the vector Vi calculations. The largest Vi value is the best alternative option. The results of this study are proven to be able to provide an objective alternative for choosing the best Internet service provider in the North Jakarta area.
Design Application of Augmented Reality-Based Computer Device Assembly Practicum Modules Diah Aryani; Syahrizal Dwi Putra; Noviandi Noviandi; Habibullah Akbar
CCIT Journal Vol 16 No 1 (2023): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (821.209 KB) | DOI: 10.33050/ccit.v16i1.2509

Abstract

The adaptation and use of digital technology have presented various opportunities and challenges for actors involved in educational services, i.e., colleges, educators, and students. Augmented reality has recently emerged as one of the digital technologies that have attracted the attention of many academies and practitioners; in addition, AR technology has brought about a change in the way users and machines interact that can teach and direct students to handle the topic of lessons differently and more proactively. This study aims to design and build an android-based Augmented Reality (AR) computer hardware assembly practicum module application as an alternative learning media in the computer hardware device assembly practicum module, which is expected in a learning activity to be more exciting and increase students' skills about computer assembly through AR technology can be one of the solutions to overcome the practicum module which was previously still in the form of a textbook and was not yet technology-based. The research method used is the Multimedia Development Life Cycle (MDLC), which consists of six stages, namely concept, design, material, collection, assembly, testing, and distribution. The results of the practicum module application with Augmented Reality technology can be run on mobile devices with an Android operating system for version 5.1 and above, and this module has a feature that can introduce 3-D objects of hardware devices and simulate the assembly of hardware devices 3D objects 3D IC processor components and mainboards that are driven with the touch of a finger by pairing elements (Drag and Drop).
SENTIMENT ANALISIS UNTUK IDENTIFIKASI KEPUASAN MASYARAKAT TERHADAP KENAIKAN BBM MENGGUNAKAN ALGORITMA NAÏVE BAYES Ahmad nur badri; Noviandi Noviandi; Farisa Anastya; Muhammad Roland
JURNAL INFORMATIKA DAN KOMPUTER Vol 7, No 2 (2023): SEPTEMBER 2023
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiko.v7i2.873

Abstract

Kenaikan harga BBM tidak hanya menimbulkan beban yang lebih besar bagi masyarakat umum, tetapi juga berdampak pada dunia usaha. Dampak dari naiknya harga bahan bakar minyak (BBM) menyebabkan pro dan kontra dimasyarakat. Salah satu media sosial yang sering digunakan masyarakat untuk menyampaikan pendapat adalah Twitter. Twitter merupakan salah satu platform media sosial yang sering digunakan oleh masyarakat untuk menyampaikan pendapat. Dari beberapa media sosial yang ada, Twitter memiliki jumlah pengguna aktif terbanyak yaitu sekitar 211 juta orang. Dengan mengacu pada masalah tersebut, peneliti sebelumnya telah melakukan penelitian menggunakan analisis sentimen terhadap kenaikan harga bahan bakar minyak (BBM) dengan menerapkan metode Naïve Bayes. Percobaan dilakukan menggunakan 1000 dataset dengan melakukan penambahan penerapan optimasi seleksi fitur Generate N-gram pada tahap preprocessing dan pelabelan memakai lexicon dan split data 80:20, Langkah awal dalam membagi dataset adalah dengan menerapkan Teknik Stratified Random Sampling, di mana dataset dibagi menjadi data train dan data test. Data train kemudian digunakan untuk membuat model Naïve Bayes, sedangkan data test digunakan untuk mengevaluasi kinerja model melalui penggunaan confusion matrix setelah melalui proses pelatihan. Berdasarkan hasil evaluasi dari penelitian yang telah dilakukan menghasilkan nilai accuracy 81%, precision 88%, recall 85% dan f1-score 87%.
Perbandingan Manhattan dan Euclidean Distance Untuk Pengelompokan Penyakit Jantung Menggunakan Algoritma K-Means Nicholas Febrian; Noviandi Noviandi
ICIT Journal Vol 10 No 1 (2024): Februari 2024
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/icit.v10i1.2860

Abstract

Penelitian ini menggunakan metode perbandingan jarak antara Manhattan distance dan Euclidean distance dalam menentukan keakuratan k-means. Fokus penelitian ini adalah untuk menentukan perbandingan keakuratan antara dua jarak yang digunakan untuk metode k-means clustering. Dengan menggunakan metode k-means penelitian ini bertujuan untuk mengelompokan cluster penyakit jantung, dengan menggunakan dataset yang memiliki atribut kolesterol dan umur, untuk menentukan keakuratan dari kedua pengukuran jarak k-means penulis menggunakan silhouette coeffiecient. Hasil dari penelitian ini menunjukan bahwa pemilihan pengukuran jarak untuk k-means clustering mempengaruhi hasil akhir dari clustering dan silhouette score yaitu 0.5374 untuk silhouette score dari k-means yang menggunakan Manhattan distance dan 0.5355 untuk silhouette score dari k-means yang menggunakan Euclidean distance. Hasil tersebut menunjukan bahwa k-means menggunakan Manhattan distance menghasilkan silhouette score yang lebih tinggi dari Euclidean distance. Penelitan lebih lanjut tentang pengaruh dari jarak perbandingan untuk k-means clustering dengan menggunakan dataset berbeda dapat memberikan wawasan lebih lanjut yang berguna dalam layanan kesehatan dan bidang lainya.
SOSIALISASI TEKNOLOGI AUGMENTED REALITY DALAM MENINGKATKAN HASIL BELAJAR SISWA PADA LINGKUP PENGAJARAN YANG TERINTEGRASI Diah Aryani; Dwi Sloria Suharti; Noviandi Noviandi; Hani Dewi Ariessanti
Universal Raharja Community (URNITY Journal) Vol 4 No 1 (2024): URNITY (Universal Raharja Community)
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/urnity.v4i1.3047

Abstract

Because of its emphasis on superimposing virtual information on top of real environments, augmented reality (AR) technology in education has emerged as a cutting-edge and promising field in both research and practice. This sets learning in a different context from traditional learning and opens up a whole new creative realm for learning.. The gap between teaching methods and the technological environment is increasing as a result of students' disinterest and low motivation when using traditional teaching approaches as well as teachers' reluctance to implement learning with technology. The lack of knowledge and ability of teachers at SDN Larangan 5, Tangerang City in the use and use of integrated technology in classroom teaching is still limited, especially for Augmented Reality (AR) technology, so boredom and lack of variety in the disclosure of their teaching materials often occur, which has an impact on learning outcomes. which is not optimal. This community service activity aims to achieve knowledge transfer by socializing learning content by utilizing Augmented Reality (AR) technology using a smartphone or tablet which will later be used to see and observe objects from the markers that have been provided. This activity uses the Community-Based Participatory Action Research (CBPAR) method with three core stages of the CBPAR action cycle, namely: planning, implementation and evaluation. And the results of the analysis of this activity state that there has been an increase in knowledge and interest regarding the use of technology, especially Augmented Reality (AR) technology which is included in learning activities with analysis results of 50%. Keywords: Augmented Reality, Community Based Participatory Action Research (CBPAR), learning content
Co-Authors Adi Widodo Ahmad Fauzan Ahmad nur badri Arif Arfan Dwi Cahyo Bambang Irawan Daniel Happy Putra Diah Aryani Ervan Jefferson Bany Farisa Anastya Habibullah Akbar Haifa Pandhita Ayu Hani Dewi Ariessanti Ichwani, arief Muhammad Hilmyansyah Muhammad Roland Nanda Aula Rumana Nicholas Febrian Ray Fadly Franata Respati Irfan Alrasyid Sartavie S Syahrudin Saipudin Anwar Septyanto Harry Nugroho Stefanny Amalia Noviantika Suharti, Dwi Sloria Syahrizal Dwi Putra