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All Journal Jurnal Algoritma Jurnal Teknologi Informasi dan Ilmu Komputer JAIS (Journal of Applied Intelligent System) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JURTEKSI Jurnal Mantik Jurnal Teknik Informatika (JUTIF) Journal of Electrical, Electronic, Information, and Communication Technology (JEEICT) Jurnal PkM MIFTEK Jurnal Algoritma INTERNAL (Information System Journal) Journal of Intelligent Systems Technology and Informatics International Journal of Applied Information Systems and Informatics
Indri Tri Julianto
Department Of Computer Science, Institut Teknologi Garut, Indonesia
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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Improving Algorithm Performance using Feature Extraction for Ethereum Forecasting Tri Julianto, Indri; Kurniadi, Dede; Rohmanto, Ricky; Alisha Fauzia, Fathia
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 1 (2024): February 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i1.4872

Abstract

Ethereum is a cryptocurrency that is now the second most popular digital asset after Bitcoin. High trading volume is the trigger for the popularity of this cryptocurrency. In addition, Ethereum is home to various decentralized applications and acts as a link for Decentralized Finance (DeFi) transactions, Non-Fungible Tokens (NFTs) and the use of smart contracts in the crypto space. This study aims to improve the performance of the forecasting algorithm by using feature extraction for Ethereum price forecasting. The algorithms used are neural networks, deep learning, and support vector machines. The research methodology used is Knowledge Discovery in Databases. The data set used comes from the yahoo.finance.com website regarding Ethereum prices. The results show that the neural network Algorithm is the best Algorithm compared to Deep Learning and support vector machine. The root mean square error value for the neural network before feature selection is 93,248 +/- 168,135 (micro average: 186,580 +/- 0,000) Linear Sampling method and 54,451 +/- 26,771 (micro average: 60,318 +/- 0,000) Shuffled Sampling method. Then after feature selection, the root mean square error value improved to 38,102 +/- 31,093 (micro average: 48,600 +/- 0,000) using the Shuffled Sampling method
KKN Tematik Penerapan Teknologi Dalam Rangka Mendukung Pemulihan Ekonomi di Desa Wanajaya Julianto, Indri Tri; Nurfauziah, Hanifah; Nawawi, Irfan Ahmad; Sanusi, Aini Fauziah Putu; Nurdiansyah, Farhan; Hidayat, Rangga; Ardana, Alwan; Hidayat, Ramdan Rahmat; Pardiansyah, Irgi; Sadikin, M. Fitroh; Dikdik, Dikdik; Nursalapiah, Sopa; Sermana, Elsa Maharani; Aditriyana, Muhammad Rizky; Abdulrohman, Muhammad Haviz; Pratama, Rizky Muhammad; Dinata, Messy Suryani Jaya; Fajar, Sigit Sihab; Octaviansyah, Rizqi Moch; Mulyani, Neng Cici
Jurnal PkM MIFTEK Vol 4 No 1 (2023): Jurnal PkM MIFTEK
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/miftek/v.4-1.1322

Abstract

Wanajaya Village is one of the villages in the Wanaraja sub-district, Garut Regency, West Java Province. Administratively, the area of ”‹”‹Wanajaya Village has a sizeable area, directly adjacent to Sukamulya Village and Citangtu Village, Pangatikan Subdistrict, to the south, Sindangratu Village and Wanamekar Village to the south, Sindangratu Village to the east, and Citangtu Village to the east. to the west it is directly adjacent to Wanasari Village, and Wanaraja Village, Wanaraja District. Based on the results of the survey that we have carried out, then with the results obtained from the survey we develop work programs that we will carry out for one month. The work program consists of work programs from various study programs as well as excellent work programs that are worked on directly by all members. In addition to work programs from various study programs and also the superior work programs that we plan, there are several other work programs that we also plan, namely teaching the Koran at mosques, holding August 17 activities, conducting clean Friday activities, conducting computer introduction activities and digitalization to elementary school children, besides that there are several work programs that we did not plan beforehand but there were requests from local residents such as carrying out garbage collection activities, making school profile videos, making the Wanajaya 1 SD school logo, making the Karangtaruna logo, and so on.
DESIGN OF A PLANE FIGURE MATHEMATICS EDUCATION GAME FOR CLASS IV STUDENTS BASED ON ANDROID Heryanto, Deni; Tri Julianto, Indri; Apriliani, Insani; Agreindra Helmiawan, Muhammad
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 5 (2023): JUTIF Volume 4, Number 5, October 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.5.1413

Abstract

Mathematics is a branch of knowledge related to developing abstract concepts, structures, and relationships in the form of numbers, symbols, and patterns. The issue some students still have trouble recalling formulas, doing division in one of the flat shape materials, and doing multiplication using the formula for the perimeter and area of flat shapes. This research discusses the design of educational games to help fourth-grade students learn flat-shape mathematics. Interviews were conducted with class IV teachers at SDN Sirnajaya Five in conveying material to students; they did not use learning media or visual aids. The problem that often arises is that some students still need help learning flat-shape mathematics. This research aims to build a flat-shape math educational game application for fourth-grade students so that these students can quickly understand the basics of flat-shape material, the definition of flat shapes, formulas, and the properties of flat shapes. The method used is the Multimedia Development Life Cycle (MDLC), a pattern for developing software systems consisting of Concept, Design, Material Collecting, Assembly, Testing, and Distribution stages, which form a workflow for planning and controlling the design of Educational Game applications. This research results in an Android-based flat-shape mathematics educational game application.
THE ROLE OF FEATURE SELECTION IN ENHANCING THE ACCURACY OF AI ASSISTANT AUTO-LABELING Julianto, Indri Tri; Kurniadi, Dede; B. Balilo Jr, Benedicto; Rohman, Fauza
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 1 (2024): Desember 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i1.3364

Abstract

Abstract: The development of AI assistants such as Gemini and ChatGPT can significantly assist in daily human tasks. In the field of Sentiment Analysis, AI assistants can be utilized as an automated labeling alternative to provide positive, negative, or neutral sentiments within a dataset. This research aims to enhance the performance of AI assistants in automated labeling processes by employing the Feature Selection algorithm, specifically Forward Selection. The methodology involves utilizing the Naïve Bayes and K-NN algorithms, and subsequently improving accuracy through the Feature Selection algorithm. The evaluation is conducted using K-Fold Cross Validation. Research findings indicate an improvement in the accuracy of the best model, which is ChatGPT, when using the Naïve Bayes algorithm and Shuffled Sampling technique. The initial accuracy of 79.09% increased to 87.18% after Feature Selection was applied. This demonstrates the effectiveness of Feature Selection, particularly Forward Selection, in enhancing the accuracy performance of the model.            Keywords: ai; assistant; chat gpt; feature selection; gemini.  Abstrak: Pekembangan Asisten AI seperti Gemini dan Chat GPT dapat membantu pekerjaan manusia sehari-hari. Dalam bidang Analisis Sentimen, Asisten AI dapat digunakan sebagai alternatif pelabelan otomatis untuk memberikan sentimen positif, negatif atau netral dalam suatu dataset. Penlitian ini bertujuan untuk meningkatkan performa yang dihasilkan oleh Asisten AI dalam proses pelabelan otomatis menggunakan Algortima Feature Selection yaitu Forward Selection. Metode yang digunakan adalah dengan menggunakan Algoritma Naïve Bayes dan K-NN kemudian hasil akurasi akan ditingkatkan menggunkan Algoritma Feature Selection. Evaluasi yang digunakan adalah K-Fold Cross Validation. Hasil penelitian menunjukkan peningkatan akurasi model terbaik berada pada Chat GPT dengan menggunakan Algoritma Naïve Bayes dan Teknik Shuffled Sampling, dari nilai akurasi awal sebesar 79.09%, setelah ditingkatkan menggunakan Feature Selection, maka nilai akurasinya meningkat menjadi 87.18%. Hal ini membuktikan peran Feature Selection, dimana yang digunakan adalah Forward Selection dalam meningkatkan akurasi ternyata memang efektif dalam meningkatkan performa akurasi model. Kata kunci: ai; assisten; chat gpt; feature selection; gemini 
Automatic Sentiment Annotation Using Grok AI for Opinion Mining in a University Learning Management System Julianto, Indri Tri; Sidqi, Muhammad Affan Al
Journal of Intelligent Systems Technology and Informatics Vol 1 No 3 (2025): JISTICS, November 2025
Publisher : Aliansi Peneliti Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64878/jistics.v1i3.42

Abstract

Sentiment analysis has become an essential tool in evaluating user feedback on digital learning platforms. Understanding student sentiments toward Learning Management Systems (LMS) in higher education can offer critical insights for system development and service improvement. This study aims to evaluate the effectiveness of AI-assisted sentiment labeling using Grok AI and ChatGPT compared to manual labeling for sentiment classification of student opinions on LMS at Institut Teknologi Garut. The research involved distributing an online questionnaire to 96 students across four academic levels, collecting open-ended responses regarding their LMS usage experiences. These responses were preprocessed through case folding, cleaning, tokenization, stopword removal, and stemming. The sentiment labels were assigned using Grok AI, ChatGPT, and manual annotation, and the resulting datasets were used to build classification models using the Naïve Bayes algorithm in Altair RapidMiner with 10-Fold Cross Validation. The performance evaluation shows that manual labeling yielded the highest accuracy (52.22%) and Cohen's Kappa (0.137), followed by ChatGPT (50.11%, 0.119) and Grok AI (48.00%, 0.087). Word cloud visualizations further revealed the dominant themes within each sentiment class, indicating that positive opinions emphasized helpfulness and ease of use, while negative ones focused on access issues and system lags. This research suggests that AI-assisted labeling methods can be viable alternatives, although manual labeling still offers slightly better accuracy.
User Sentiment Analysis X Towards Makan Bergizi Gratis Program Using Automatic Labeling Technique with Deepseek AI Julianto, Indri Tri; Nurpajar, Dini Siti
Journal of Intelligent Systems Technology and Informatics Vol 1 No 2 (2025): JISTICS, July 2025
Publisher : Aliansi Peneliti Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64878/jistics.v1i2.43

Abstract

Public perception of national nutrition initiatives is instrumental in shaping inclusive and data-driven policy development. In Indonesia, the "Makan Bergizi Gratis" (MBG) program introduced by President Prabowo has drawn significant attention, particularly on the X platform (formerly Twitter). This research topic was selected due to its national urgency and political significance, as the MBG program emerged as a key agenda during the 2024–2025 political transition. Therefore, examining public sentiment is essential to assess policy acceptance and identify areas for improvement. This study analyzes user sentiment toward the MBG policy using an automatic labeling approach supported by DeepSeek AI and the VADER Lexicon, followed by sentiment classification through the K-Nearest Neighbor (KNN) algorithm. The research involved five main stages: collecting 1,704 tweets from X between January 2024 and March 2025, preprocessing the text, conducting automatic sentiment labeling, applying TF-IDF for vectorization, handling class imbalance using the Synthetic Minority Over-sampling Technique (SMOTE), and classifying sentiments using KNN. The results indicate that without SMOTE, the VADER model achieved higher accuracy (93.49%) but lower Cohen's Kappa (0.16), while DeepSeek AI yielded lower accuracy (73.67%) but slightly higher Kappa (0.17). After SMOTE was applied, accuracy declined (VADER to 77.25%, DeepSeek AI to 64.72%), but Kappa scores improved significantly (VADER to 0.65, DeepSeek AI to 0.47), indicating more balanced and consistent sentiment predictions across classes. In conclusion, integrating automatic labeling, SMOTE, and KNN provides a reliable and scalable framework for analyzing large-scale sentiment on social media platforms, particularly in contexts with imbalanced opinion distributions.
Rancang Bangun Virtual Reality Tour Untuk Menunjang Wisata Ziarah Berbasis Website Julianto, Indri Tri; Nursalapiah, Sopa
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.1702

Abstract

Garut is a region known for its many pilgrimage sites that are considered sacred and revered. One of the pilgrimage destinations in Garut is the Sacred Tomb of Godog (Makam Keramat Godog). This pilgrimage tourism emphasizes religious values and is visited with the purpose of seeking blessings and prayers from those believed to hold a special status in the eyes of God. Information about this pilgrimage site is still obtained from personal stories and digital platforms such as blogs. However, this information is only presented in the form of text and images. In addition, the information provided about the Sacred Tomb of Godog is still limited due to the lack of specific sources of information. With the development of technology, Virtual Reality can be utilized as a medium to introduce the Sacred Tomb of Godog and assist people who have limited accessibility to visit the pilgrimage site. This research aims to design and develop a Virtual Reality Tour for pilgrimage tourism that can help tourists or potential visitors who face distance limitations, have accessibility constraints, and increase tourist interest in visiting pilgrimage sites. The method used in this research is the Multimedia Development Life Cycle (MDLC), which consists of six stages: concept, design, material collecting, assembly, testing, and distribution. The testing technique used in this research is alpha testing using the black box method. The result of this research is a website-based Virtual Reality Tour to support pilgrimage tourism, which features pilgrimage information, Google Maps, directional guide features (hotspots), audio, and a chatbot.
Rancang Bangun Virtual reality Tour Pusat Perbelanjaan Modern Berbasis Web Julianto, Indri Tri; Rustandy, Sandy
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.1777

Abstract

Garut has nine modern shopping centers that are the main destinations for local residents and visiting tourists. The modern shopping center industry has a significant role in improving the economy and welfare, especially in Garut Regency. Where now virtual reality can complement social media as a source of information. With the development of virtual reality (VR) technology to support modern shopping centers. The purpose of this study is to design, build and implement a web-based virtual reality tour of modern shopping centers using the MDLC method for information media for visitors. The methodology used in this research is the Multimedia Development Life Cycle method consisting of six stages: concept, design, material collecting, assembly, testing, and distribution. The results of this study are the Design of a Web-Based Virtual Reality Tour of Modern Shopping Centers. displays 3600 panoramic images, hotspot features, sound features, videos, and there are google map and chatbot features. The testing method used in this study is using Beta testing obtained a score of 3.98 percent stating that the Ciplaz VR Tour web is feasible to use.
Analysis of the Usability Level of the JKN Mobile Application Using the User Experience Questionnaire (UEQ) and Importance–Performance Analysis (IPA) Methods Haris, Gendhi; Tri Julianto, Indri; Ridwan Ibrahim, Maulana
Journal of Applied Information System and Informatic (JAISI) Vol 3, No 2 (2025): November 2025
Publisher : Deparment Information System, Siliwangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/jaisi.v3i2.17008

Abstract

The JKN Mobile application developed by BPJS Kesehatan is a digital service for National Health Insurance (JKN) participants to access features for checking membership, online queues, and complaint services. JKN Mobile contributes significantly to the digitalization of healthcare services, but various negative reviews still emerge, especially regarding the interface aspect. This study analyzes the usability level of the application using the User Experience Questionnaire (UEQ) and Importance Performance Analysis (IPA) methods. The UEQ assesses six aspects of user experience, while IPA maps attributes based on importance and performance. The analysis results show a gap between expectations and experience. Clarity (1.1056, 0.4021), efficiency (1.0181, 0.0026), and appeal (1.0946, -0.019) fall into the "maintain performance" quadrant. Novelty (0.0965, 0.4113) is in the "top priority" quadrant, stimulation (0.8763, -0.1192) is a low priority, while accuracy (0.9514, -0.1224) is excessive. These findings provide a comprehensive overview of aspects that need to be maintained or improved. User feedback-driven strategies and agile approaches are recommended to make application development more innovative, optimal, and responsive to the needs of digital healthcare services.
Co-Authors Abdullah, Angga Abdulrohman, Muhammad Haviz Ade Sutedi Ade Sutedi, Ade Aditriyana, Muhammad Rizky Agisni Nurlela, Agni Agreindra Helmiawan, Muhammad Akhdan Hidayat, Fairuz Alamsyah, Restu Alisha Fauzia, Fathia Apriliani, Insani Ardana, Alwan Arif Rahman, Rifal Arif Syamsudin, Muhammad Asri Mulyani B. Balilo Jr , Benedicto B. Balilo Jr, Benedicto Balilo Jr, Benedicto B. Baswardono, Wiyoga Burhanudin, Asep Chaerunisa, Adinda Citra Indahsari, Ajeng Dede Kurniadi Deni Heryanto, Deni Dewi Tresnawati Dikdik, Dikdik Dinata, Messy Suryani Jaya Dwi Anggara, Krisna Dzulkhomzah, Moh Rival Fajar, Sigit Sihab Fauzi Pratama, Andhika Fauziah, Fathia Alisha Fikri Fahru Roji Fiqriansyah, Agung Firdaus, Ardy Reza Ginanjar, Ahmad Gotama, Dwi Haris, Gendhi Hartono, Ali Hidayat, Ramdan Rahmat Hidayat, Rangga Huwaidah, Alya Ilham Maulana Ilyasin, Yasa Tiyas Kurnia, Ahmad Hopan Leni Fitriani, Leni Lindawati Lindawati Mahesa, Restu Gusti Malik Ibrahim, Maulana Meta Regita Muhammad Ajif, Arvin Muhammad Rikza Nashrulloh Muhammad Sambas, Phadil Mulyani, Neng Cici Munparik, Riyan Hakim Mutiara, Sani Muzaky, Rifky Khoerul N, Firza Much Asrizal Nawawi, Irfan Ahmad Nurandhini, Rosa Eliza Nurdiansyah, Farhan Nurdin, Kaila Fashla Nurfauziah, Hanifah Nurhalimah, Seli Nurhaqiqi, Lisda Nurpajar, Dini Siti Nursalapiah, Sopa Nurul Muttaqin, Epwan Octaviansyah, Rizqi Moch Pardiansyah, Irgi Pratama, Rizky Muhammad Rahayu, Raden Erwin Gunadhi Rahman, Jaohari Rahmawati, Deby Ricky Rohmanto Ricky Rohmanto Ridwan Ridwan Ibrahim, Maulana Ridwan Setiawan Rinda Cahyana Rinda Cahyana Rohman, Fauza Rohmanto, Ricky Rusdiawan, Mohamad Mihradi Rustandy, Sandy Sadikin, M. Fitroh Saepul Jamil, Alwis Sanusi, Aini Fauziah Putu Septian Rheno Widianto Sermana, Elsa Maharani Setiawan Putra, Achmad Dhani Sidqi, Muhammad Affan Al Sirojudin, Naufal Suryadi, Khaila Thsabita Suryani, Isma Taupik Hidayat, Taupik Tizani, Sofyan Tria Afini Ujang Sarifudin Yoga Handoko Agustin Yosep Septiana