Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal Jurnal Bingkai Ekonomi (JBE) Nusantara Journal of Computers and its Applications
Aries Alfian Prasetyo
Teknik Listrik Industri, Politeknik Negeri Madura
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Metode K-Means Berbasis Ordered Weighted Averaging (OWA) pada Data Potensi Desa untuk Penentuan Status Desa Aries Alfian Prasetyo; Suprapedi Suprapedi; Siska Narulita; Bayu Praharsena
Jurnal Bingkai Ekonomi (JBE) Vol 7 No 2 (2022): Jurnal Bingkai Ekonomi (JBE)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM) - Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jbe.v7i2.224

Abstract

Indeks Pembangunan Desa yang dibangun dari Pendataan Potensi Desa (Podes) tahun 2014. untuk menilai tingkat perkembangan desa, dibagi menjadi 3 klasifikasi yaitu Desa Mandiri, Berkembang, dan Tertinggal, memiliki 5 dimensi. Penulis bertujuan untuk menilai tingkat perkembangan desa melalui status desa berdasar data IPD, penentuan status desa menggunakan teknik clustering dengan metode K-Means berbasis Ordered Weighted Averaging (OWA), OWA dapat mengurangi kompleksitas data dengan memadukan nilai multi attribut ke nilai agregat berupa nilai tunggal dengan menggunakan expert judgement untuk menentukan nilai orness (α). Hasil dari penelitian ini pengelompokan data IPD tahun 2014 kedalam 3 status desa dengan algoritma K-Means berbasis OWA menunjukkan metode clustering K-Means dengan OWA memiliki Index Davies 1,42 lebih baik daripada metode K-Means dengan euclideance yang memiliki nilai 1,65. Hasil akhir penelitian diperoleh jumlah desa untuk setiap cluster, yaitu cluster Desa Tertinggal sebanyak 98, cluster Desa Berkembang sebanyak 32, dan cluster Desa Mandiri sebanyak 100 desa.
TWITTER BUZZER DETECTION SYSTEM USING TWEET SIMILARITY FEATURE AND SUPPORT VECTOR MACHINE Ahmad Mustofa; Fitrah Maharani Humaira; Myrna Ermawati; Peni Sriwahyu Natasari; Akhmad Arif Kurdianto; Aries Alfian Prasetyo; A Labib Fardany Faisal
NJCA (Nusantara Journal of Computers and Its Applications) Vol 8, No 1 (2023): June 2023
Publisher : Computer Society of Nahdlatul Ulama (CSNU) Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36564/njca.v8i1.306

Abstract

Over the past few years, people have been able to get and share information through social media easily. Some of that information can be a false issue created by a buzzer account that intends to influence people into a specific opinion. Politicians often use social media to maintain a good image in society by utilizing buzzer accounts. The main characteristic of a buzzer account is that they upload the same content repeatedly within a certain period. Before analyzing data taken from social media such as Twitter, we need a buzzer detection system to filter data from buzzer users.  This research attempts to build a buzzer detection system using text processing and classification method. We use the similarity of tweets as a feature for the buzzer detection system by applying Cosine Similarity to the Term Frequency - Inverse Document Frequency (TF-IDF) feature of the tweets. In addition, we will use other features such as the number of followers, number of followings, the intensity of tweets, the ratio of retweets, and the ratio of tweets that contain links as additional features in this study. This research uses these features as inputs to the Support Vector Machine model to determine whether an account is a buzzer or not. This system has promising results by having 89% accuracy, 86.67% precision, 70.91 % recall, and 78% F1-score.
Co-Authors A Labib Fardany Faisal Ahmad Mustofa Akhmad Arif Kurdianto Bayu Praharsena Fitrah Maharani Humaira Myrna Ermawati Peni Sriwahyu Natasari Siska Narulita Suprapedi Suprapedi