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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) dCartesian: Jurnal Matematika dan Aplikasi Jurnal Sistem Komputer Proceedings of KNASTIK Jurnal Teknologi Informasi dan Ilmu Komputer Scientific Journal of Informatics International Journal of Artificial Intelligence Research INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Jurnal Penelitian Pendidikan IPA (JPPIPA) CogITo Smart Journal INOVTEK Polbeng - Seri Informatika BAREKENG: Jurnal Ilmu Matematika dan Terapan JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Sebatik Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal ULTIMA InfoSys MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Digital Zone: Jurnal Teknologi Informasi dan Komunikasi JURIKOM (Jurnal Riset Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Aptisi Transactions on Technopreneurship (ATT) Building of Informatics, Technology and Science FINANCIAL : JURNAL AKUNTANSI Jurnal Mnemonic JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Sistem Komputer dan Informatika (JSON) Aiti: Jurnal Teknologi Informasi Jurnal Teknik Informatika (JUTIF) Advance Sustainable Science, Engineering and Technology (ASSET) International Journal of Social Science Indexia J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Teknologi Sistem Informasi Jurnal Algoritma Jurnal Ilmiah Sains Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat IT-Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Eduvest - Journal of Universal Studies Jurnal INFOTEL Journal of Technology Informatics and Engineering Jurnal Pendidikan Teknologi Informasi (JUKANTI) Jurnal Indonesia : Manajemen Informatika dan Komunikasi Scientific Journal of Informatics CSRID INOVTEK Polbeng - Seri Informatika Jurnal DIMASTIK Proceedings of The International Conference on Computer Science, Engineering, Social Sciences, and Multidisciplinary Studies
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Universitas Kristen Satya Wacana
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Covid-19 Sentiment Analysis Using Convolutional Neural Network / Reccurent Neural Network Method Ravensca Matatula; Danny Manongga; Hendry Hendry
Eduvest - Journal of Universal Studies Vol. 2 No. 8 (2022): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1819.418 KB) | DOI: 10.59188/eduvest.v2i8.514

Abstract

Social media is a very important tool in this modern era , one of which is namely twitter. Twitter allows user for give opinion / opinion to various issues and topics hot / viral trending . Trending on twitter is so so fast in the process of spreading so that Twitter becomes a medium of information that often become a media issue conspiracy . Covid-19 is a moderate epidemic / disease _ experienced the whole world when this . Issues circulating in the population , they believe that Covid-19 is a real pandemic and a conspiracy , issue this make population confused differentiate Among second issue that . Because of that required a fast and accurate analysis _ for produce valid results , that Covid-19 a real thing _ or conspiracy seen from opinion population and corner views written on Twitter. CNN/RNN or combined from RNN(LSTM) and CNN methods are method used _ for classify opinion population about Covid-19 issues . Study this also done with compare is correct RNN/CNN accuracy same like deep RNN even more fast for in the process . Research results state that accuracy from combined RNN/CNN no different remote , even RNN/CNN in the process more fast than deep RNNs. Research results about opinion / opinion residents on twitter who believe about Covid-19 is conspiracy more low than residents who have confidence about Covid-19 is something the real thing . Percentage classification opinion / opinion from sentiment positive by 63.15% and opinion / opinion sentiment negative by 28.60%, this is results calculation use RNN/CNN method , with accuracy reached 58%. Accuracy from method used _ make Covid-19 issues that exist in the population no Becomes hoax news so population more alert against the ongoing Covid-19 pandemic happen.
Sentimen Masyarakat Terkait Perpindahan Ibukota Via Model Random Forest dan Logistic Regression Martaliana Putri Agustina; Hendry Hendry
AITI Vol 18 No 2 (2021)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v18i2.111-124

Abstract

This study aims to determine public opinion regarding the relocation of the capital of Indonesia. The pros and cons conveyed by the community are important because they can be constructive input for the government. The applications used to support the research are Orange and Twitter. The data obtained must go through several processes such as preprocess text, sentiment analysis, and testing algorithms to ensure data accuracy before making a decision tree. This research uses Random Forest and Logistic Regression as the research models. As for the results, Random Forest obtains higher accuracy value than Logistic Regression and it is considered that time did not affect the classification. The result obtained from the decision tree is that more people choose to have a neutral opinion on this program. People prefer to entrust everything to the government, because the government must have thought about the positive or negative impacts in the long term.
Komparasi linear regression, random forest regression, dan multilayer perceptron regression untuk prediksi tren musik TikTok Nadia Sofie Soraya; Hendry Hendry
AITI Vol 20 No 2 (2023)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v20i2.191-205

Abstract

Predicting how audio features correlate with popular songs on TikTok is essential in the music industry. Armed with data that has several audio features, a study was conducted using the Linear Regression, Random Forest Regression (RFR), and Multilayer Perceptron Regression (MLP Regression) methods to compare models that can effectively predict popularity and features that influence song popularity on TikTok, then Exploratory Data Analysis (EDA) was also carried out to gain insight into the data. The results of the EDA process are that the most popular of songs is in the range of 40-80, the duration of songs is between 2-3 minutes, feature loudness is positively correlated with energy, and so is between artist_pop and track_pop. The set feature importance in the LR and RFR models for the feature target track_pop is artist_pop, loudness, and duration_ms. The LR method has the most effective results between RFR and MLP Regression for the dataset used,  with MSE of 0.0313, RMSE of 0.177, and MAE of 0.118.
User Experience Analysis from User Centered Design Approach in Marketing Website Adenia Kusuma Dayanthi; Eko Sediyono; Hendry Hendry
Ultima InfoSys : Jurnal Ilmu Sistem Informasi Vol 14 No 1 (2023): Ultima InfoSys : Jurnal Ilmu Sistem Informasi
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/si.v14i1.3169

Abstract

In the User Experience (UX) analysis carried out using the User Centered Design (UCD) approach, the research is based on user-oriented design. A website based on the UCD process will definitely generate high levels of satisfaction for its users. In this research, user experience analysis was conducted using a User Centered Design approach with Product Market Fit concept orientation. This concept is often ignored so that it becomes a major factor in the failure of a business start-up. The collection was carried out through several processes, namely in-depth interviews and distribution of questionnaires to a total of 30 respondents. The results of the questionnaire can be used as a reference to find out which aspects are good and which are still lacking. The aspect of displaying information on the monitor screen when opening a website gets the highest score of the other aspects with a percentage of 93% user satisfaction. The conclusion for each aspect states that the curious websites that are analyzed get a decent title.
PENGGUNAAN TEKNOLOGI INFORMASI DALAM PENGELOLAAN KEUANGAN BADAN USAHA MILIK DESA (BUMDES) BERGAS KIDUL SEJAHTERA Suharyadi Suharyadi; Ade Iriani; Danny Manongga; Hendry Hendry; Sutarto Wijono
Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat Vol. 3 No. 3 (2023)
Publisher : Universitas Kristen Satya Wacana Salatiga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/jms.v3i32023p417-427

Abstract

Badan Usaha Milik Desa Bergas Kidul Sejahtera adalah Badan Usaha yang terletak di desa Bergas Kidul, Kecamatan Bergas kabupaten Semarang. Dalam proses pengelolaan keuangannya menghadapi kendala yaitu keterbatasan kemampuan Sumder Daya Manusia yang mengelola keuangan. Program pengabdian masyarakat yang diakukan ini bertujuan untuk memberikan pelatihan penggunaan Teknolgi Informasi dalam hal ini memaksimalkan kemampuan Microsoft Excel untuk pengelolaan laporan keuangan. Metode pelaksanaan program antara lain adalah perencanaan, analisa kebutuhan, persiapan program, pelaksanaan program. Hasil yang dicapai adalah kemampuan sumber daya BUMDes dapat bertambah dalam hal penggunaan fungsi-fungsi akuntansi yang dimiliki oleh Microsoft Excel. .
EVALUASI KETERGUNAAN WEBSITE PERPUSTAKAAN UNIVERSITAS KRISTEN SATYA WACANA DENGAN MENGGUNAKAN METODE SYSTEM USABILITY SCALE Herdin Yohnes Madawara; Danny Manongga; Hendry Hendry
Jurnal Pendidikan Teknologi Informasi (JUKANTI) Vol 6 No 2 (2023): JURNAL PENDIDIKAN TEKNOLOGI INFORMASI (JUKANTI) EDISI NOPEMBER 2023
Publisher : Program Studi Pendidikan Informatika, Universitas Citra Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37792/jukanti.v6i2.933

Abstract

This research was conducted with the aim of evaluating the usability of the Satya Wacana Christian University (UKSW) Library website using the System Usability Scale (SUS) method. This research also aims to identify areas that need to be improved in the UKSW Library website. Respondents in this study were UKSW students who had used the library website. This study used the SUS questionnaire consisting of 10 questions with a 5-point Likert scale. The results of the SUS calculation show that the average value of the usability of the UKSW Library website is 59.514, which is in the medium or "OK" category. Further analysis shows that areas that need to be improved are clarity of information, ease of navigation, and visual appearance. This research is expected to provide input for the UKSW Library in developing the website in order to increase usability and meet the needs of its users. The conclusion of this research is that the UKSW Library website still has some areas that need to be improved to increase usability.
Analysis of Student Satisfaction with the Quality of Education Services and Lecturer Performance Using the Survey and Naive Bayes Methods Syefudin Syefudin; Hendry Hendry; Ade Iriani
Jurnal Penelitian Pendidikan IPA Vol 9 No 11 (2023): November
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v9i11.5367

Abstract

This research aims to evaluate the level of student satisfaction with the quality of educational services and the assessment of faculty performance at STMIK Tegal through a survey method and the application of Naive Bayes. The research sample consists of 100 active students from different study programs. Survey results were processed using the Naive Bayes method to assess the impact of variables related to the quality of educational services and faculty performance on the level of student satisfaction. The findings of the analysis indicate that the quality of educational services has a positive effect on student satisfaction, while faculty performance also contributes positively. This research has practical implications for improving the quality of educational services and faculty performance at STMIK Tegal. Infrastructure and facilities supporting the teaching and learning process can be enhanced, and faculty members can receive training and guidance to improve their teaching quality. In the long term, this can enhance the institution's reputation and overall student satisfaction. This study has limitations related to the limited sample size and the use of non-random sampling techniques. Therefore, future research can expand the sample size and use more representative sampling techniques to enhance the accuracy of research results
Analisis Sentimen Terhadap Film Sri Asih Dengan CNN, KNN, dan Logistic Regression Ester Caroline Dwi Wijaya Wijaya; Hendry
Computer Science Research and Its Development Journal Vol. 15 No. 3 (2023): October 2023
Publisher : LPPM Universitas Potensi Utama

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

Abstract

Technological developments have had a significant impact on various sectors, which is in the film industry, of course this is become a challenge for film producers to make works that suit people's tastes. The recent film that has become the public's attention is the Sri Asih film, due to its fresh genre and story, this film got a lot of opinions from the public. With the social media Twitter, people can express their opinions, comments, and criticisms online. Therefore, Twitter can be used to observe positive and negative responses to analyze public opinion about the film Sri Asih. The analysis is sentiment analysis, which is a process to analyze whether public opinion is negative, neutral, or positive. The goal of this study is to determine the public's response to the Sri Asih film which can be used as an evaluation for film producers. This research was conducted using three methods: Convolutional Neural Network (CNN) with 78% accuracy, K-Nearest Neighbor (KNN) with 61% accuracy, and Logistic Regression with 81% accuracy.
PERBANDINGAN METODE KLASIFIKASI DALAM ANALISIS SENTIMEN MASYARAKAT TERHADAP IDENTITAS KEPENDUDUKAN DIGITAL (IKD) Wahyuningsih, Novia; Hendry, Hendry
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 8, No 4 (2023)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v8i4.4155

Abstract

Identitas Kependudukan Digital merujuk pada penggunaan teknologi digital dan data elektronik untuk mengidentifikasi individu dalam konteks kependudukan. Pada dasarnya, Identitas Kependudukan Digital bertujuan untuk memberikan cara yang lebih efisien dalam mengelola data identitas individu. Dalam mengimplementasikan Identitas Kependudukan Digital, perlu memperhatikan aspek keamanan dan privasi data. Selain itu, tidak semua individu memiliki akses ke teknologi digital atau mungkin menghadapi tantangan dalam menggunakan teknologi tersebut. Penelitian ini bertujuan untuk melakukan klasifikasi data dari Twitter terkait Identitas Kependudukan Digital dengan membandingkan metode SVM, K-NN, Naive Bayes, dan Neural Network menggunakan pendekatan data mining CRISP-DM. Dataset diambil menggunakan Twitter API dan diproses menggunakan Orange Data Mining. Dari jumlah awal data tweet sebanyak 7914, setelah dilakukan pembersihan data, tersisa 1022 tweet yang digunakan dalam penelitian. Hasil pengujian menunjukkan bahwa masyarakat cenderung memiliki sentimen netral terkait Identitas Kependudukan Digital. Dalam hal performa model klasifikasi, metode K-NN menunjukkan kinerja yang sangat baik dengan nilai akurasi, presisi, dan recall mencapai 100%. Metode Neural Network dan Naive Bayes memiliki perbedaan yang kecil dalam performanya, sementara metode SVM memiliki nilai yang lebih rendah dalam evaluasi menggunakan Confusion Matrix. Penelitian ini memberikan wawasan tentang sentimen masyarakat terkait Identitas Kependudukan Digital dan mengidentifikasi metode klasifikasi dengan performa terbaik. Hasilnya dapat digunakan sebagai dasar untuk pengembangan lebih lanjut dalam meningkatkan akses dan pengelolaan Identitas Kependudukan Digital.
ANALISA SENTIMEN MASYARAKAT TERHADAP PENGGUNAAN CHATGPT MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM) Pratama, Arya Damar; Hendry, Hendry
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 1 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i1.4285

Abstract

Bekembangnya teknologi yang semakin modern menyebabkan manusiadimudahkan dalam melakukan aktivitas kehidupanya. Salah satuteknologi yang sedang berkembang untuk memudahkan aktivitasmanusia adalah hadirnya AI (Artificial Intelegence) yaitu kecerdasanbuatan yang mampu belajar dengan sendirinya karena dibentuk denganalgoritma machine learning didalamnya. Salah satu wujud penerapanyaadalah hadirnya chatgpt yaitu sebuah AI yang mampu berinteraksikepada user melalui inputan user seperti menjawab segala pertanyaanyang diberikan. Dalam penelitian ini akan dilakukan analisa sentimenterhadap penggunaan chatgpt untuk mengetahui pandangan masyarakatapakah positif, negatif dan netral terhadap hadirnya chatgptdimasyarakat. Untuk pengambilan data berasal dari twitter denganbantuan application programming language (API) token key yangdiintegrasikan dengan tools olah data yang digunakan yaitu rapidminer.Kemudian untuk metode olah data menggunakan metode CRSIP-DMsedangakan model algoritma yang digunakan adalah support vectormachine (SVM). Data yang diperoleh dalam penelitian ini sebanyak 2000data tweet namun setelah dilakukan pre processing data menjadi 790 datatweet. Kemudian data hasil prepocesing data tersebut diolah denganmemasukan model algoritmanya dan ditemukan hasil denganditunjukanya confusion matriks yang hasilnya yaitu memiliki jumlahsentimen netral lebih dominan daripada positif maupun negatif.Diketahui bahwa masyarakat Indonesia masih netral akan hadirnyachatgpt yang dikatakan sebagai penggunaan teknologi yang baru makadari itu masih belum mampu menggunakanya secara optimal untukmenjadi tools yang membantu aktivitas kehidupan manusia. Denganadanya hasil tersebut maka bisa digunakan sebagai bahan dasar dalampenelitian lebih lanjut mengenai dampak yang diberikan atas penggunaanchatgpt.
Co-Authors Ade Iriani Adenia Kusuma Dayanthi Adriyanto Juliastomo Gundo Agista Nindy Yuliarina Aldi Lasso Anton Hermawan Anugerah Widi April Lia Hananto Atik Setyanti, Angela Aviv Yuniar Rahman Baihaqi, Kiki Ahmad Benedictus Lanang Ido Hernanto Christine Dewi Daniel D. Kameo Danny Manongga Danny Manongga Darmawan Utomo Darwin Lie Dewasasmita, Elsha Yuandini Dewi Puspitasari Eko Sediyono eric secada purba Erick Alfons Lisangan Erits Talapessy Erwien Christianto Ester Caroline Dwi Wijaya Wijaya Faisal Hakim Amrullah Fauzi Ahmad Muda Febrian, Andika Rossy Franly Salmon Pattiiha Fredryc Joshua Pa'o Fredryc Joshua Pa'o Giarti, Giarti Gunawan, Ricardho Handoko, Andrew C Hanita Yulia Hendra Waskita Herdin Yohnes Madawara Hindriyanto Dwi Purnomo Huda, Baenil Ibrahim Ibrahim Irwan Sembiring Ismael Ismael Ivan Sukma Hanindria Ivanna K. Timotius Iwan Setiawan Iwan Setyawan Jessica Margaret Br Sembiring Joko Siswanto Julians, Adhe Ronny Kesumawati, Ramadini Kevin Fransisco Kho, Delvian Christoper Krismiyati Kristoko Dwi Hartomo Kurniawan Teguh Martono Leni Marlina Lidia Gayatri Madawara, Herdin Yohnes Mado, Priscianus Mikael Kia Magda Kitty Hartono Mahulete, Ebenhaezer Yohanes Abdeel Manongga, Daniel Margaretha Intan Pratiwi Hant Martaliana Putri Agustina Merryana Lestari Muhammad Rizky Pribadi Muhammad Sholikin Nadia Sofie Soraya Nalbraint Wattimena Nansy Stephanie Mongi Nifu, Merlyn Gizella Nugraha, Febrina Tesalonika Panja, Eben Paryono, Tukino Pratama Siregar, Hari Nanda Pratama, Arya Damar Purnomo, Hendryanto Dwi Ramos Somya Ravensca Matatula Ravensca Matatula Richard V. Llewelyn Robertus Bagaskara Radite Putra Ronny Julians, Adhe Rostina, Cut Fitri Rung Ching Chen Santoso, Joseph Teguh Saputri, Adelliya Dewi Septhiani, Angeline Shallom, Karsten Jonatthan Simanjuntak, Dahnil Anzar Suharyadi Suherman, Suherman Sutarto Wijono Suvirocana, Suvirocana Syefudin Syefudin Teddy Marcus Zakaria Thea Thiranadya Mardita Bulamey Theophilus Wellem Theopillus J. H. Wellem Titin Restiani Mendrofa Tukino, Tukino Uly, Novem Untung Rahardja Wahyuningsih, Novia Wibowo, Kurniawan Indra Winny purbaratri Winsy C.D Weku Wiwin Sulistyo Yessica Nataliani Yessica Nataliani