Claim Missing Document
Check
Articles

Found 20 Documents
Search

ANALISA SENTIMEN TERHADAP TAGAR #dirumahaja MELALUI TWITTER DI INDONESIA ANDREYESTHA; ADHI DHARMA SURIYANTO; WITRIANA ENDAH PANGESTI
JURNAL EKONOMI, SOSIAL & HUMANIORA Vol 2 No 09 (2021): INTELEKTIVA : JURNAL EKONOMI, SOSIAL DAN HUMANIORA (EDISI - APRIL 2021 )
Publisher : KULTURA DIGITAL MEDIA ( Research and Academic Publication Consulting )

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

New Normal now inevitably apply in various fields. During the Covid-19 pandemic, people were required to do various things in their own homes. Social media is increasingly being used by the community, one of which is that Twitter has many functions and purposes. Twitter can disseminate information in the form of appeals, such as dirumahaja hashtags echoed by the government and the people of Indonesia. The use of these dirumahaja hashtags has various kinds of opinions, such as positive and negative opinions. This study tries to analyze Indonesian language tweets that use dirumahaja hashtags to find out how people in Indonesia view these hashtags. The method used is scraping data from Twitter with a total of 200 data tweets then analyzed using the lexicon-based text mining method, the sentiment results obtained from tweets using the Bing Vector method. The results of the sentiment analysis in this study got a positive score of 49, and a negative score of 48. The negative score almost offset the positive score due to the high percentage of Anticipation emotions of 40% which illustrates the concern of Twitter netizens about the COVID-19 pandemic which they pour through dirumahaja tagged tweets.
FTK Image For Forensic Data Processing In Forensic Tools Rachmat Suryadithia; Witriana Endah Pangesti; Muhammad Faisal; Aji Nurrohman; W Wibisono; Arman Syah Putra
IJISTECH (International Journal of Information System and Technology) Vol 5, No 6 (2022): April
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v5i6.199

Abstract

The background of this research is how the use of a software can help find forensic data, which is needed so that the tool used is the right tool in helping forensic problems. The method used in this study is the NIJ method using 5 stages in a process of determining the answer. The first stage is preparation, the second stage in collecting data, the third is testing and the fourth stage is analyzing and the last is the reporting stage with the five stages. The direction of the research will be clearer. The problem raised in this research is how to find evidence using FTK images software. Using this software, you can search for the desired forensic data so that it can be proven that there is forensic evidence. The purpose of this study is how to prove data, especially photo data, can be used as forensic data that can be used as evidence, by using the right tools, namely the existing FTK images software, with the software, it can help parties in proving, especially in terms of forensics
PERBANDINGAN SEGMENTASI CITRA PSORIASIS MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING DAN ALGORITMA THRESHOLDING Witriana Endah Pangesti; Dwiza Riana; Sri Hadianti
Jurnal Khatulistiwa Informatika Vol 9, No 2 (2021): Periode Desember 2021
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jki.v9i2.11380

Abstract

Letaknya kulit pada bagian tubuh manusia berada dibagian luar tubuh untuk menyelimuti bagian lain yang ada didalam salah satunya urat atau lemak, sehingga kulit menjadi salah satu bagian terpenting dalam organ tubuh manusia,  karena letaknya di luar maka kulit menjadi rentan untuk mengalami penyakit, baik itu penyakin yang berbahaya atau tidak. Contoh penyakit yang berbahaya untuk kulit manusia adalah penyakit psoriasis. Psoriasis adalah penyakit kulit inflamasi kronis yang ditandai dengan lesi khas berupa plak, eritematous, dan sisik tebal. Dalam penelitian ini menggunakan dua klaster penyakit psoriasis yaitu klaster Chronic Plaque psoriasis dan Guttate Psoriasis. Dimana dataset yang didapatkan adalah dataset public dan selanjutnya masuk pada tahap cropping dan di peroleh sebanyak 71 dataset citra psoriasis. Penelitian ini melakukan perbandingan algoritma antara algoritma k-means clustering dan algoritma thresholding, dengan pengujian menggunakan hasil nilai dari ektrasi ciri GLCM dengan meilihat 4 fitur bentuk yaitu contrast, correlation, energy, homogeneity yang selanjutnya diolah menggunakan aplikasi weka dengan metode J48 classifier dalam menentukan akurasi terbaik dan mendapatkan pohon keputusan. Hasil yang diperoleh adalah k-means clustering merupakan algoritma terbaik dalam mengsegmentasi citra psoriasis yaitu sebesar 79%, dibandingkan algoritma thresholding yaitu sebesar 61% saja.
IMPLEMENTASI KOMPRESI CITRA DIGITAL DENGAN MEMBANDINGKAN METODE LOSSY DAN LOSSLESS COMPRESSION MENGGUNAKAN MATLAB Witriana Endah Pangesti; Galih Widagdo; Dwiza Riana; Sri Hadianti
Jurnal Khatulistiwa Informatika Vol 8, No 1 (2020): Periode Juni 2020
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jki.v8i1.7759

Abstract

Teknologi pengolahan citra saat ini telah banyak berkembang, salah satunya teknologi kompresi. Kompresi citra digital merupakan suatu upaya untuk melakukan tranformasi terhadap data atau simbol, tanpa menimbulkan perubahan yang signifikan atas citra digital bagi mata manusia yang mengamatinya. Citra merupakan istilah lain untuk gambar sebagai salah satu komponen multimedia memegang peranan sangat penting sebagai bentuk informasi visual. Dalam penelitian ini penulis menggunakan metode Lossy compression dan Lossless compression dimana metode Lossy compression yaitu suatu metode kompresi data yang menghilangkan sebagian informasi sedangkan metode Lossless compression yaitu suatu metode kompresi data dengan tidak ada informasi data yang hilang atau berkurang jumlahnya selama proses kompresi. Sehingga setelah proses dekompresi jumlah bit (byte) data atau informasi dalam keseluruhan data hasil sama persis dengan data aslinya (Saragih and Harahap 2019). Dari penelitian sebelumnya yaitu Implementasi Kompresi Citra Digital Dengan Mengatur Kualitas Citra Digital (Raharja and Harsadi 2018) penulis melanjutkan dengan melalukan perbandingan dengan menggunakan 20 citra berbeda lalu di kompres dengan metode lossless compression, diketahui rata-rata setelah kompres adalah empat puluh sembilan persen. Paper penelitian sebelumnya  yang menggunakan metode lossy menghasilkan rata-rata kompres enam puluh persen dan  paper penelitian yang penulis lakukan dengan metode lossless yang menghasilkan rata-rata kompresi empat puluh sembilan persen, maka dapat di simpulkan bahwa metode lossy lebih baik dibandingkan dengan metode lossless dalam mengkompresi citra
PERBANDINGAN ALGORITMA KLASIFIKASI NAIVE BAYES DAN SVM PADA STUDI KASUS PEMBERIAN PENERIMA BEASISWA PPA safitri linawati; Rizky Ade Safitri; Ahmad Rifqy Alfiyan; Witriana Endah Pangesti; Monikka Nur Winnarto
Swabumi Vol 8, No 1 (2020): Volume 8 Nomor 1 Tahun 2020
Publisher : Universitas Bina Sarana Informatika Kota Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/swabumi.v8i1.7708

Abstract

Beasiswa PPA merupakan sebuah program beasiswa yang diberikan kepada mahasiswa aktif. Dalam melakukan seleksi penerima beasiswa PPA, akan ada tahapan-tahapan yang harus diproses untuk mendapatkan mahasiswa yang menerima beasiswa sesuai harapan. Data pendaftar beasiswa PPA dari tahun sebelumnya menjadi penunjang untuk keakuratan pengambilan keputusan dalam seleksi penerima beasiswa agar sesuai dengan kriteria yang telah ditetapkan. Untuk mendapatkan keakuratan pengambilan keputusan maka dibutuhkan data mining sebagai penunjang dalam pengambilan keputusan. Pada penelitian ini, penulis melakukan perbandingan 2 algoritma untuk mengetahui algoritma mana yang mempunyai keakuratan lebih tinggi dalam pengambilan keputusan penerima beasiswa PPA. Algoritma yang digunakan adalah algoritma klasifikasi Naïve Bayes dan Support Vector Machine (SVM). Berdasarkan hasil komparasi antara algoritma Naive Bayes dan SVM (Support Vector Machine) yang dilakukan untuk mengklasifikasikan nilai akurasi tertinggi dengan 5 variabel dan jumlah data sebesar 122 dapat disimpulkan bahwa algoritma Naive Bayes memiliki tingkat akurasi lebih tinggi yaitu 90.90% dibandingkan dengan metode SVM yaitu 89.25%.
Collaborative Filtering Based Recommender Systems For Marketplace Applications Witriana Endah Pangesti; Rachmat Suryadithia; Priyono; Muhammad Faisal; Bilal Abdul Wahid; Arman Syah Putra
International Journal of Educational Research & Social Sciences Vol. 2 No. 5 (2021): October 2021
Publisher : CV. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51601/ijersc.v2i5.184

Abstract

The background of this research is to give the best advice to users who still don't know about other marketplaces that they can still use, to find the items they are looking for and at a cheaper price or with promos they can get. The method used in this research is to use a trial based on data obtained from users who use the media marketplace to purchase an item, with this, the real data can be known so that the best advice for an unknown marketplace can be given. In how many countries, a recommender system has been implemented in a marketplace that will provide advice using advertising media on social media, by using social media, users can find out about the marketplace, and are given continuous advice to install the application so that they can make transactions with purchase of a product in the marketplace. The purpose of this research is to give the best advice so that all people, especially marketplace users, can find out which other marketplaces are in order to know and be able to shop at other marketplaces, by doing price comparisons and being able to get promo prices and knowing based on habits, and ratings from the marketplace.
PENGARUH GAME ONLINE TERHADAP PRESTASI BELAJAR REMAJA KOMPLEK KORPRI KABUPATEN KUBURAYA (STUDI KASUS: MOBILE LEGENDS) Witriana Endah Pangesti; Rizky Ade Safitri; Qudziah Nur Azizah
Jurnal Akrab Juara Vol 4 No 4 (2019)
Publisher : Yayasan Akrab Pekanbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Current technological developments especially those related to smart computer technology are growing rapidly. Until the cellphone was originally used to meet communication needs only, now mobile phones can be used to do many things, such as used to find any information that is in the world very easily, playing online games anywhere and so on. Mobile Legend game is very popular not only by teenage boys, but there are also many teenage girls who like to play online games. According to Fendy, now the "Mobile Legends application: I have downloaded 35 million times and there are 8 million daily active users in Indonesia". The Korpri complex of Kubu Raya West Kalimantan is an object chosen by the writer to be an object of research that focuses on young men and women aged 12 to 24 years. This research was conducted using simple linear regression method and the data was processed using SPSS version 24 software. The results of this study note that a significant value of 0.686 is greater than> 0.05 probability, so it can be concluded that there is no influence of playing mobile legends (X ) towards youth learning achievement (Y).
KLASIFIKASI PENERIMA DANA BANTUAN DESA MENGGUNAKAN METODE KNN (K-NEAREST NEIGHBOR) Riyan Latifahul Hasanah; Muhamad Hasan; Witriana Endah Pangesti; Fanny Fatma Wati; Windu Gata
Jurnal Techno Nusa Mandiri Vol 16 No 1 (2019): Techno Nusa Mandiri : Journal of Computing and Information Technology Periode Ma
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (953.294 KB) | DOI: 10.33480/techno.v16i1.25

Abstract

Determining the status of poor families as recipients of assistance is very important so that poverty reduction assistance from the government can be channeled on target. Data mining utilizes experience or even mistakes in the past to improve the quality of the model and the results of its analysis, one of which is the ability possessed by data mining techniques, namely classification. The purpose of this study was to test K-Fold Cross Validation in the K-Nearst Neighbors algorithm in predicting receipt of village aid funds. In the beneficiary dataset used in this study, there were 159 records or tuples with four attributes (house condition, income, employment and number of dependents). The new data category prediction is done by using the Euclidean Distance manual calculation stage of five different K values. While using the Rapidminer application aims to test the accuracy of the dataset in five different K values. The results show that with K=15 and K=30 the new data (D160) has a "Not Eligible" category with an accuracy of 100%. Then with K=45, K=60 and K=75, the new data (D160) has the category "Eligible" with an accuracy rate of 81.25%.
FTK Image For Forensic Data Processing In Forensic Tools Rachmat Suryadithia; Witriana Endah Pangesti; Muhammad Faisal; Aji Nurrohman; W Wibisono; Arman Syah Putra
IJISTECH (International Journal of Information System and Technology) Vol 5, No 6 (2022): April
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (910.09 KB) | DOI: 10.30645/ijistech.v5i6.199

Abstract

The background of this research is how the use of a software can help find forensic data, which is needed so that the tool used is the right tool in helping forensic problems. The method used in this study is the NIJ method using 5 stages in a process of determining the answer. The first stage is preparation, the second stage in collecting data, the third is testing and the fourth stage is analyzing and the last is the reporting stage with the five stages. The direction of the research will be clearer. The problem raised in this research is how to find evidence using FTK images software. Using this software, you can search for the desired forensic data so that it can be proven that there is forensic evidence. The purpose of this study is how to prove data, especially photo data, can be used as forensic data that can be used as evidence, by using the right tools, namely the existing FTK images software, with the software, it can help parties in proving, especially in terms of forensics
Pemanfaatan Google Maps Sebagai Media Visualisasi Guna Mendukung Pembelajaran Pada Anak Asuh Yayasan Yatim dan Duafa SIGMA Siti Marlina; Syarif Hidayatulloh; Witriana Endah Pangesti; Fatimah Azzahro
Abditeknika Jurnal Pengabdian Masyarakat Vol. 2 No. 2 (2022): Oktober 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/abditeknika.v2i2.1319

Abstract

Istana Yatim merupakan salah satu program yang di jalankan pada Yayasan SIGMA. Anak asuhnya terdiri dari anak-anak usia sekolah mulai dari Sekolah Dasar sampai dengan Sekolah Menengah. Masa pandemic sekarang ini memaksa kita untuk membiasakan diri beraktifitas secara dari termasuk kegiatan belajar mengajar. Visualisasi dalam hal pembelajaran daring akan sangat penting karena dapat mendukung menggambarkan sebuah bahasan atau materi yang diajarkan secara online. Smartphone tentunya menjadi salah satu benda yang sangat berperan penting dalam kegiatan belajar mengajar tersebut. Kecanggihan smartphone untuk mengakses berbagai macam informasi akan lebih cepat dan mudah. Dengan keterbatasan media daring dalam pembelajaran para anak asuh dalam hal ini sebagai siswa sekolah membutuhkan sebuah media visualisasi guna mendukung pembelajaran mereka yang terbattas karena dilakukan secara daring. Salah satu aplikasi yang bisa dimanfaatkan sebagai media visualisasi dalam pembelajaran adalah google maps.