Article Per Year (5 Year)
p-Index From 2021 - 2026
1.922
P-Index
This Author published in this journals
All Journal Jurnal Kesehatan Lingkungan indonesia Jurnal Informatika dan Teknik Elektro Terapan Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer JURNAL REKAYASA TEKNOLOGI INFORMASI Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika KOMPUTEK Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming JPM (Jurnal Pendidikan Modern) Borneo Student Research (BSR) Jurnal Informatika Teknologi dan Sains (Jinteks) Saber: Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi
Rudiman Rudiman
Unknown Affiliation
Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Mechanical Engineering Public Health Social Sciences Other

Published : 14 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 14 Documents
Search

 1   2 
Analisis Sentimen Terhadap Calon Wakil Presiden Gibran Rakabuming Raka Menggunakan Algoritma Naive Bayes Muhammad Khumaidi Nursyarif; Muhamad Wahyu Tirta; Muhammad Rahman Hidayat; Rudiman Rudiman
KOMPUTEK Vol 8, No 1 (2024): April
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/jkt.v8i1.2509

Abstract

The turnover of the president and vice president in Indonesia occurs every 5 years. In the year 2024, there will be an election, and one of the vice presidential candidates, listed as candidate number 2, is Gibran Rakabuming Raka, who is the son of Mr. Jokowi, currently serving as the 7th President. Many opinions have been expressed by the public regarding Mas Gibran, especially considering his age of 36 years, which is perceived as relatively young to lead the nation of Indonesia. Therefore, we intend to conduct research with the aim of identifying practical implications related to public perceptions of the potential vice presidential candidate. Data from comments on the YouTube video titled "[FULL] Gibran in Between Ganjar and Prabowo, Which One to Choose? | ROSI" underwent a classification process using the Naive Bayes algorithm for sentiment analysis. The accuracy obtained is 92.5%, with an f1 Score of 92.4%, Precision of 93.5%, and Recall of 92.5%.
ANALISIS KEPUASAAN PENGGUNA APLIKASI DONORKU DENGAN PENDEKATAN METODE RANDOM FOREST DENGAN SMOTE Muhammad Fauzan Nur Ilham; Kholifah Dwi Annurrahma; Pandu Wirayuda; Rudiman Rudiman
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 6 No 3 (2024): EDISI 21
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v6i3.4229

Abstract

Penelitian ini menganalisis kepuasan pengguna terhadap Aplikasi Donorku di Google Play Store menggunakan analisis sentimen dengan algoritma Random Forest. Di era digital, aplikasi mobile seperti Donorku sangat penting untuk memfasilitasi donasi darah di Indonesia. Ulasan pengguna di Google Play Store seringkali tidak cukup representatif. Data dikumpulkan menggunakan scraping, diikuti oleh prapemrosesan teks seperti pembersihan, tokenisasi, normalisasi, dan stemming. Data yang telah diproses dibobotkan menggunakan metode TF-IDF dan dibagi menjadi data latih dan data uji. Teknik SMOTE digunakan untuk mengatasi ketidakseimbangan kelas. Model Random Forest mengklasifikasikan sentimen pengguna, dievaluasi dengan akurasi, presisi, recall, dan F1-Score. Hasilnya menunjukkan model dapat mengidentifikasi pola ketidakpuasan pengguna secara efektif. Memahami persepsi pengguna membantu pengembang meningkatkan layanan Donorku. Penelitian ini menunjukkan efektivitas teknologi analisis sentimen dalam memahami preferensi pengguna dan meningkatkan aplikasi donasi darah.
ANALISIS SENTIMEN ULASAN “OJOL THE GAME” DI GOOGLE PLAY STORE MENGGUNAKAN ALGORITMA NAIVE BAYES DAN MODEL EKSTRAKSI FITUR TF-IDF UNTUK MENINGKATKAN KUALITAS GAME Rafi Rahmadani; Abdul Rahim; Rudiman Rudiman
Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 3 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3.4988

Abstract

Abstrak. Penelitian ini bertujuan untuk menganalisis sentimen ulasan pengguna terhadap game "OJOL THE GAME" di Google Play Store memanfaatakan algoritma Naive Bayes dan model ekstraksi fitur TF-IDF. Data ulasan dikumpulkan melalui teknik web scraping menggunakan Python, kemudian diproses dengan tahapan preprocessing meliputi pembersihan data, case folding, stop word removal, tokenizing, dan stemming. Data yang telah diproses kemudian dianalisis menggunakan algoritma Metode Naive Bayes digunakan untuk mengklasifikasikan sentimen positif dan negatif. Hasil penelitian mengindikasikan bahwa kombinasi antara algoritma Naive Bayes dan TF-IDF memberikan akurasi sebesar94,12%, menunjukkan efektivitas tinggi dalam mengidentifikasi sentimen pengguna. Temuan ini memberikan wawasan berharga  dalam memahami opini pengguna, meningkatkan kualitas game.Abstract. This study aims to analyze user sentiment towards the game "OJOL THE GAME" on Google Play Store using the Naive Bayes algorithm and the TF-IDF feature extraction model. User review data was collected through web scraping techniques using Python, then processed through preprocessing stages including data cleaning, case folding, stop word removal, tokenizing, and stemming. The processed data was then analyzed using the Naive Bayes algorithm to classify positive and negative sentiments. The results of the study show that the combination of the Naive Bayes algorithm and TF-IDF yielded an accuracy of 94.12%, demonstrating high effectiveness in identifying user sentiment. These findings provide valuable insights into understanding user opinions and improving the quality of the game.
Analisis Sentimen Terhadap Kualitas Layanan Driver Gojek Di Aplikasi Play Store Menggunakan Algoritma Naïve Bayes Dan Aplikasi Orange Ipan Hasmadi; Rudiman Rudiman; Khoirul Huda Dwi Putra; Muhammad Farhat jundullah
SABER : Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi Vol. 2 No. 1 (2024): Januari : Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi
Publisher : STIKes Ibnu Sina Ajibarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59841/saber.v2i1.673

Abstract

The significant changes in daily life patterns, driven by technological advancements, particularly in the transportation sector, are evident through the emergence of on-demand services such as Gojek. This research aims to explore users' perspectives and opinions regarding service quality, focusing on aspects like driver behavior, responsiveness, and reliability within the Gojek platform. The Naive Bayes method is employed to analyze user sentiments toward the driver services, supported by the Orange software to comprehend the complex patterns in user reviews. Evaluation is conducted on reviews from the Play Store, resulting in an accuracy of 87.4%, F1 score of 87.6%, precision of 87.9%, and recall of 87.4%. These findings indicate the success of the model in identifying and predicting predefined variables. Through the combination of methods and software, the study concludes that sentiment analysis of Gojek's driver services can be performed efficiently and reliably, providing valuable insights for online motorcycle taxi service providers.
Co-Authors Abdul Basir Salsabila Abdul Rahim Daramusseng, Andi Ikhsan Nuttakwa Takbirata Ihram Nabawi Indiana Nawang Yuli Safitri Ipan Hasmadi Januar Abdilah Santoso Julianur Khoirul Huda Dwi Putra Kholifah Dwi Annurrahma Kurnia Jusuf, Jeane Betty M. Riadhus Sholihin Mahardhika, Nanda Alfian Malik Fajar Muhamad Wahyu Tirta Muhammad Farhat Jundullah Muhammad Fauzan Nur Ilham Muhammad Khumaidi Nursyarif Muhammad Rahman Hidayat Muhammad Rayhan Elfansyah Muhammad Reifin Perdana Pandu Wirayuda Rafi Rahmadani Rofilde Hasudungan Syamsir Syamsir Wasiatul Aqmaliah