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All Journal Techno.Com: Jurnal Teknologi Informasi Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi Jurnal Informatika dan Teknik Elektro Terapan JURNAL MEDIA INFORMATIKA BUDIDARMA Information System for Educators and Professionals : Journal of Information System IKRA-ITH Informatika : Jurnal Komputer dan Informatika IKRA-ITH Teknologi Jurnal Sains dan Teknologi Jurnal Teknoinfo Jurnal Ilmiah Media Sisfo IKRA-ITH ABDIMAS Jurnal Telematika JURTEKSI Jurnal Riset Informatika Zonasi: Jurnal Sistem Informasi JIKA (Jurnal Informatika) Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) Teknomatika (Jurnal Teknologi dan Informatika) Jurnal Inovasi Informatika Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Teknik Informatika (JUTIF) Jurnal Ilmiah Wahana Pendidikan Jurnal Media Informatika Jurnal PkM (Pengabdian kepada Masyarakat) TIERS Information Technology Journal Prosiding Konferensi Nasional PKM-CSR Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Dirgamaya: Jurnal Manajemen dan Sistem Informasi Joutica : Journal of Informatic Unisla Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Nasional Teknologi Komputer Jurnal Sistem Informasi dan Teknologi (SINTEK) Moneter : Jurnal Keuangan dan Perbankan COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi Informasi interaktif : jurnal informatika dan teknologi informasi Prosiding SeNTIK STI&K Sintek Kuwera Jurnal Ilmu Komputer dan Teknik Informatika Jurnal Komtika (Komputasi dan Informatika) Indonesian Applied Research Computing and Informatics Jurnal Komputasi
Atmojo, Wahyu Tisno
Universitas Pradita
Religion Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Nursing Public Health Social Sciences Transportation Other

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IMPLEMENTASI ALGORITMA NAIVE BAYES DALAM ANALISA SENTIMEN TERHADAP TREND TIKTOK Wahyu Tisno Atmojo; Ericka Keisya; Afifah Trista Ayunda
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 13, No 2 (2025): Jurnal Tikomsin, Vol 13, No.2, Oktober 2025
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v13i2.1015

Abstract

Social networking is becoming more and more important. Social media's purpose has evolved from its first appearance as a place just for self-actualization to include online buying and selling, self-actualization, and other functions. Tik tok is one of the social media platforms that is currently in high demand; opinions about its rise are mixed and include both positive and negative aspects. The goal of this study is to closely examine and comprehend how people react to the phenomena of Tiktok's development by keeping an eye on user-generated material in tweets and the evolution of sentiment over time. This experimental study suggests using the Naïve Bayes Algorithm as a sentiment analysis method to examine how Twitter users are responding to the TikTok craze. In-depth insights into the dynamics of Twitter users' reactions to the TikTok trend are sought by this research, which combines sentiment analysis technology with Confusion Matrix performance evaluation. According to the sentiment analysis results, the majority of user comments are neutral (57.03%), followed by critical (33.20%) and affirmative (9.77%) remarks. This illustrates the nuanced reactions that people have had to the TikTok movement, in which the majority of users share their ideas in an unbiased manner. The significance of this research lies in its ability to provide an answer.
Pembandingan Arsitektur Transformer dan CNN untuk Pengolahan Data Non-Visual Rahmawati, Lailia; Atmojo, Wahyu Tisno; Cynthia, Eka Pandu; Cynthia, Maulidania Mediawati; Cynthia, Dessy Nia
Jurnal Ilmu Komputer dan Teknik Informatika Vol. 2 No. 1 (2026): Januari 2026
Publisher : CV. Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/juikti.v2i1.80

Abstract

Perkembangan pesat kecerdasan buatan dan pembelajaran mendalam telah mendorong eksplorasi berbagai arsitektur jaringan saraf untuk pengolahan data non-visual, seperti data numerik, sekuensial, dan tekstual. Dua arsitektur yang paling banyak digunakan dan berkembang adalah Convolutional Neural Network (CNN) dan Transformer. Meskipun CNN telah lama digunakan secara luas karena efisiensinya dalam mengekstraksi fitur lokal, arsitektur Transformer dengan mekanisme self-attention menawarkan kemampuan unggul dalam menangkap hubungan global dan dependensi kompleks antar elemen data. Penelitian ini bertujuan untuk membandingkan kinerja dan efisiensi arsitektur CNN dan Transformer dalam pengolahan data non-visual melalui pendekatan eksperimental kuantitatif. Dataset non-visual digunakan dan melalui tahapan pra-pemrosesan sebelum dilakukan pelatihan dan pengujian model. Evaluasi performa dilakukan menggunakan metrik akurasi, precision, recall, dan F1-score, serta analisis efisiensi komputasi berdasarkan waktu pelatihan dan kompleksitas model. Hasil penelitian menunjukkan bahwa Transformer secara konsisten mencapai performa yang lebih tinggi dibandingkan CNN pada seluruh metrik evaluasi, khususnya dalam menangani pola kompleks dan hubungan jangka panjang pada data non-visual. Namun, CNN menunjukkan keunggulan dalam efisiensi komputasi dan kestabilan pelatihan dengan kebutuhan sumber daya yang lebih rendah. Temuan ini mengindikasikan bahwa tidak terdapat satu arsitektur yang sepenuhnya unggul dalam semua aspek, melainkan pemilihan model harus disesuaikan dengan karakteristik data dan kebutuhan aplikasi. Selain itu, penelitian ini menyoroti potensi pendekatan hibrida yang mengombinasikan CNN dan Transformer untuk meningkatkan performa dan generalisasi model. Penelitian ini diharapkan dapat menjadi referensi empiris bagi pengembangan sistem cerdas berbasis pembelajaran mendalam dalam pengolahan data non-visual.
Improving Thesis Title Classification Accuracy Using Ensemble Classifier and Modified Chi-Square Feature Selection Method Ritzkal; Wahyu Tisno Atmojo; Panji Novantara; Sabir Rosidin; Ahmad Dedi Jubaedi; Enggar Novianto
Indonesian Applied Research Computing and Informatics Vol. 1 No. 1: July (2025)
Publisher : PT. Teras Digital Nusantara

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

Abstract

Text classification of academic documents, particularly thesis titles, poses challenges due to high dimensionality, sparsity, and topic heterogeneity. Conventional feature selection techniques, such as the standard Chi-Square, often fall short in capturing discriminative features effectively. This research aims to enhance classification accuracy by proposing a Modified Chi-Square feature selection method that integrates term frequency and class distribution information. The selected features are then classified using ensemble decision tree algorithms, including Random Forest, Gradient Boosting, and XGBoost. Experiments were conducted on a labeled dataset of thesis titles using TF-IDF for vector representation. Evaluation metrics such as accuracy, precision, recall, F1-score, and AUC were used to assess model performance. The results showed that the combination of Modified Chi-Square and XGBoost outperformed other models, achieving the highest accuracy of 93.8% and an AUC of 0.94. These findings demonstrate that the integration of advanced feature selection and ensemble learning techniques can significantly improve academic text classification performance, providing valuable implications for the development of intelligent digital repositories and recommendation systems.
PROTOTYPE APLIKASI BUKU PENGHUBUNG BERBASIS MOBILE Wahyu Tisno Atmojo; Afifah Trista Ayunda; Indras Nur Hidayat
Jurnal Komputasi Vol. 12 No. 1 (2024): Jurnal Komputasi
Publisher : Jurusan Ilmu Komputer Fakultas MIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v12i1.250

Abstract

Abstract — The Liaison Book is a media of communication between the school, especially the class teacher and parents, parents can monitor student activities at school through the liaison book. The liaison book needs to be made an application because of the many problems that exist today where these problems include frequent damage to the liaison book, students forgetting to bring the liaison book, parents not reading the liaison book or students not giving the liaison book to parents or teachers. This application prototype is made using the Waterfall method with the java programming language and Android Studio tools. The result of this research is an application that is feasible to use where 62% of respondents strongly agree that this application is used, 31% of respondents agree to use it and as many as 7% expressed doubt. From the percentage of these answers it can be seen that this application is indeed feasible to use.
PEMANFAATAN PLATFORM METAVERSE UNTUK VISUALISASI PERENCANAAN PARIWISATA PESISIR TERINTEGRASI Atmojo, Wahyu Tisno; Olivia, Deasy; Ayunda, Afifah Trista
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 14, No 1 (2026): Jurnal Tikomsin, Vol 14, No.1, April 2026
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v14i1.1082

Abstract

Using immersive technology in regional planning is now essential to provide an accurate picture of how areas will develop in the future. This study aims to design and develop a Virtual Reality (VR) Tour application that visualizes the integrated coastal tourism plan in Tangerang Regency. The coastal area of Tangerang has a lot of potential but needs more interactive social media communication to involve stakeholders and the community in planning. The development method used is the Multimedia Development Life Cycle (MDLC), which consists of six stages: concept, design, collecting materials, assembly, testing, and distribution. The development was done using Roblox Studio because of its strengths in rendering multi-user environments and the ease of access across different devices. The result of this research is a VR application that allows users to explore a digital prototype of the tourism area, including infrastructure facilities and mangrove conservation areas, in an immersive way. Testing the app showed that using VR devices gives a more detailed spatial experience compared to traditional models or 2D maps. This study concludes that using Roblox Studio with the MDLC method is effective in speeding up the process of creating VR prototypes for coastal tourism planning that is both communicative and educational.
Pelatihan Pemanfaatan Business Intelligence Untuk Visualisasi Data Menggunakan Tableau Pada Ekstrakurikuler Kewirausahan Di SMA Pahoa Afifah Trista Ayunda; Wahyu Tisno Atmojo; Master Edison Siregar; Hendra Mayatopani; Rido Dwi Kurniawan; Januponsa Dio Firizqi; Masriah Masriah; Qonita Azizah; Shabila Octavia
IKRA-ITH ABDIMAS Vol. 10 No. 2 (2026): IKRAITH-ABDIMAS Vol 10 No 2 Juli 2026
Publisher : Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikra-ithabdimas.v10i2.7194

Abstract

Teknologi visualisasi data telah menjadi bagian integral dari perkembangan bisnis modern, memungkinkan pemahaman yang lebih baik terhadap informasi yang kompleks dan mendukung pengambilan keputusan yang lebih efektif. Di era digital ini, pemanfaatan teknologi ini semakin penting, khususnya dalam konteks kewirausahaan, di mana pengelolaan dan analisis data menjadi keterampilan yang esensial. Namun, tingkat pemahaman siswa SMA terhadap konsep dan aplikasi teknologi visualisasi data dalam konteks kewirausahaan masih menjadi perhatian. Penelitian ini bertujuan untuk mengeksplorasi pemanfaatan teknologi Business Intelligence, khususnya Tableau, dalam memvisualisasikan data untuk mendukung pendidikan kewirausahaan di SMA Pahoa Tangerang. Melalui pendekatan observasi, pelatihan, dan metode kuantitatif menggunakan kuesioner untuk evaluasi, penelitian ini berupaya mengukur sejauh mana pemahaman siswa meningkat setelah pelatihan. Hasil penelitian menunjukkan bahwa penggunaan teknologi visualisasi data memberikan kontribusi signifikan terhadap pemahaman siswa, terutama dalam memanfaatkan data untuk menggambarkan informasi dalam bentuk gambar yang mudah dipahami. Hasil evaluasi menggunakan kuesioner menunjukkan skor 77,31%. Dengan demikian, penerapan teknologi visualisasi data, seperti Tableau, efektif dalam meningkatkan kompetensi siswa dalam bidang kewirausahaan dan pengelolaan data.
CLASSIFICATION OF VEHICLE TYPES USING BACKPROPAGATION NEURAL NETWORKS WITH METRIC AND ECCENTRICITY PARAMETERS Hendra Mayatopani; Rohmat Indra Borman; Wahyu Tisno Atmojo; Arisantoso Arisantoso
Jurnal Riset Informatika Vol. 4 No. 1 (2021): December 2021
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (758.834 KB) | DOI: 10.34288/jri.v4i1.139

Abstract

One of the efforts to break down traffic jams is to establish special lanes that can be passed by two, four, or more wheeled vehicles. By being able to recognize the type of vehicle can reduce congestion. Citran based vehicle classification helps in providing information about the vehicle type. This study aims to classify the type of vehicle using a backpropagation neural network algorithm. The vehicle image can be recognized based on its shape, then the backpropagation neural network algorithm will be supported by metric and eccentricity parameters to perform feature extraction. Then from the results of feature extraction with metric parameters and eccentricity, the object will be classified using a backpropagation neural network algorithm. The test results show an accuracy of 87.5%. This shows the algorithm can perform classification well.
Co-Authors Aditya Bima Adrielvino, Nathanael Abel Agus Dendi Rachmatsyah Ahmad Dedi Jubaedi Alfa Yohannis Andi Guna Andi Guna Andreas Indra Wardana Andrew Lowell Aprikasari, Manda Aprikasari, Manda Arisantoso Arisantoso Ayunda, Afifah Trista Belsana Butar Butar Benedicta, Laurence Butar Butar, Belsana Caesar Gracia Chandra, Frans Kenny Christopher Christopher Cynthia, Dessy Nia Cynthia, Maulidania Mediawati Darmawan, Umar Dazki, Erick Deasy Olivia Deasy Olivia Deasy Olivia, Deasy Dermawan, Steven Destriana, Rachmat Dewi Monica Didik Setiyadi Dodi Aprilianto Dwi Nisfatul Hijjah Edison Siregar Eka Pandu Cynthia Endang Retnoningsih Enggar Novianto Ericka Keisya Erika Kristina Ernando, Ryan Felix Felix Feri Prasetyo Feri Prasetyo Halim, Onky Ardhana Hasna Tania Yasmine Heriyando, Damien Hugo Hisyam, Ahmad Abdilah hizkia imanuel Indras Nur Hidayat Januponsa Dio Firizqi Jonathan Juan Antoni Samuel Posumah Kelly Kirsten Audrey Kirsten Audrey, Kelly Kurniawan, Ericka Kesya Masriah Masriah - Masriah Masriah Masriah Masriah masriah masriah, masriah Master Edison Master Edison Master Edison Siregar Master Edison Siregar Mayatopani, Hendra Muhadi Hariyanto Muhamad Filman Ghaida Firdaus Muhamad Irvansyah Muhammad Haikal Nadda Akilka Ulima Nurhajanti Muljadi Nadda Akilka Ulima Nurhajanti Muljadi Natanael Iwan Santosa Nazwa Wanda Tazkiya Niklas, Hubert Nofry Thrusmida Ocktavia, Shabila Ocktavia, Shabila Oki Sumistriani Panduwitama, Aldira Panji Novantara Posumah, Juan Qonita Azizah Qonita Azizah Qonita Azizah Rachmatsyah, Agus Dendi Rahmawati, Lailia Richardo, Albert Rido Dwi Kurniawan Rido Dwi Kurniawan Ritzkal, Ritzkal Rohmat Indra Borman Sabir Rosidin Shabila Octavia Shella Cintiya Stevan Amadeo Prasetyo Susiana Tarisa Mareti, Gusti Teh Yu Ka Untoro, Elianna Katherine Valencia, Shanty Waris Widekso Waris Widekso Wellson, Matthew George Zaenab Islami