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INDONESIA
JURNAL ILMIAH INFORMATIKA
Published by Universitas Putera Batam
ISSN : 23378379     EISSN : 26151049     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal Teknologi Informatika dan Sistem Informasi Fakultas Teknik dan Komputer UPB, telah menerbitkan publikasi ilmiah dengan topik yang mencakup tentang Information System, Geographical Information System, Remote Sensing, Cryptography,artificial intelligence, Computer Network, Security dan Database.
Arjuna Subject : -
Articles 190 Documents
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PERANCANGAN UI/UX APLIKASI MOBILE PANGAUBAN KARINDING DENGAN MENGGUNAKAN FIGMA Lubis, Novitasari Ramadhani; Anggraini, Novita; Senubekti, Mamok Andri
JURNAL ILMIAH INFORMATIKA Vol 13 No 02 (2025): Jurnal Ilmiah Informatika (JIF)
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v13i02.10147

Abstract

This study aims to design the User Interface (UI) and User Experience (UX) of the Pangauban Karinding mobile application as a medium for preserving the art and education of traditional Sundanese musical instruments. Pangauban Karinding functions as a digital space that documents, archives, and shares the dynamics of perkarinding strategically and sustainably. Although this platform is already available in the form of a website, the development of a mobile version was carried out to increase accessibility and user engagement, especially among the younger generation who are more familiar with mobile devices. The method used is a prototyping approach with the help of the Figma application, which supports the process of making wireframes, interface design, and testing interactive prototypes. The application design is carried out through the stages of analyzing user needs, creating navigation and display structures, and evaluating functionality through user feedback. The final results show that the proposed UI/UX design is able to provide a more structured, informative, and attractive user experience than the previous platform. With this application, the preservation of the Karinding culture is not only packaged in an educational way, but also adaptive to the development of technology and the digital behavior of today's society.
PEMBUATAN WEBSITE INVENTARIS BARANG DI KOBER AULIA Muhammad, Thomas Lazuardi; Darsiti, Darsiti
JURNAL ILMIAH INFORMATIKA Vol 13 No 02 (2025): Jurnal Ilmiah Informatika (JIF)
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v13i02.10152

Abstract

The Goods Inventory Website is a website-based application used to manage and track stock of goods or assets in an agency in Kober Aulia, an important means to provide convenience for teachers to record goods in Kober Aulia. Managing goods data is often a challenge for Kober.Kober today, which still uses the manual method of recording one by one through books. This study aims to design a website-based application that can do bookkeeping or recording of goods neatly and make it easy to see stock or new goods to be submitted to the center for reporting learning facilities and infrastructure. To overcome this problem, it can be overcome by CMS (Content Management System). CMS is a system that can change data content dynamically. This inventory website is made using Laravel which is easy to use and also uses Visual Studio Code as a supporting application and uses MySQL as a database to store data. This application will certainly be very easy to use by users with clear information and is not difficult to operate. This application is adjusted to the needs of users who currently still find it difficult to record goods in Kober Aulia and still use manual books to record existing stock of goods.
OPTIMASI SISTEM INFORMASI PENGELOLAAN DATA KESEHATAN PEGAWAI PADA UNIT P3K PT KEBON AGUNG PG TRANGKIL MENGGUNAKAN METODE AGILE DENGAN PENDEKATAN SCRUM Rahmawati, Yulinda; Setiawan, R. Rhoedy; Irawan, Yudie; Setiaji, Pratomo
JURNAL ILMIAH INFORMATIKA Vol 13 No 02 (2025): Jurnal Ilmiah Informatika (JIF)
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v13i02.10194

Abstract

This study is entitled “Optimization of Employee Health Data Management Information System at P3K Unit PT Keon Agung PG Trangkil Using Agile Method with Scrum Approach”. This study aims todevelop an integrated and flexible informastions system to manage employee healrt data. With agile method with Scrum approach, the system is developed in stages through Sprint, adjusted ased on user feedback. The system is designed to record examination data, classify results into mild and severe diseases, and process referrals for severe disease cases. The development results show increased efficiency, accuracy of recording, and support management in making decisions related to employee welfare
ANALISIS KEPUASAN PENGGUNA APLIKASI GOPAY MENGGUNAKAN ALGORITMA NAÏVE BAYES DAN K-FOLD CROSS VALIDATION Usnah, Asmaul; Hasan , Fuad Nur; Kuntoro, Antonius Yadi
JURNAL ILMIAH INFORMATIKA Vol 13 No 02 (2025): Jurnal Ilmiah Informatika (JIF)
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v13i02.10276

Abstract

The rapid advancement of digital technology has significantly increased the adoption of digital wallet services in Indonesia, one of which is the GoPay application. This study aims to analyze user satisfaction with GoPay based on user reviews from the Google Play Store. The classification method used is the Naïve Bayes algorithm, with model validation performed using the K-Fold Cross Validation technique. A total of 3,000 reviews were collected through web scraping and then preprocessed using several text preprocessing steps including cleansing, case folding, tokenizing, stopword removal, and stemming. The data was automatically labeled using the IndoBERT model and classified into two satisfaction categories. The classification results show that the Naïve Bayes algorithm achieved an accuracy of 92.46%, with a precision of 92.25%, recall of 94.70%, and an f1-score of 93.46%. Validation using 10-fold cross-validation resulted in an average accuracy of 92.23%. These results indicate that the model demonstrates strong classification performance and stable generalization on unseen data. This research is expected to contribute to improving GoPay's service quality and serve as a reference for the implementation of machine learning techniques in user satisfaction analysis.
PREDIKSI MAHASISWA INSTITUT SOSIAL DAN TEKNOLOGI WIDURI JAKARTA BERPOTENSI DROP OUT MENGGUNAKAN ALGORITMA NAÏVE BAYES Sultan, Sultan; Pusparini, Nur Nawaningtyas; Kharisma, Nanda; Samuel, Samuel
JURNAL ILMIAH INFORMATIKA Vol 13 No 02 (2025): Jurnal Ilmiah Informatika (JIF)
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v13i02.10310

Abstract

Universities are responsible for producing quality graduates and reducing dropout rates (DO), a serious challenge for the Widuri Institute of Social and Technology (ISTEK). This phenomenon has a negative impact on the quality of education and accreditation, making early identification of students who have the potential to drop out (DO) very crucial. This study aims to apply the Naïve Bayes algorithm to predict the potential for dropout (DO) of ISTEK Widuri students based on data on the activities of the 2021, 2022, and 2023 intakes. Naïve Bayes has proven effective in classifying students at risk of dropping out (DO). The Semester Credit Unit (SKS) attribute is the most dominant indicator, students with low SKS have a high potential for dropping out (DO). Model performance varies for each batch, in the 2021 batch it reached 90% accuracy (100% DO precision, 40% recall), the 2022 batch showed 93.75% accuracy (100% DO precision, 60% DO recall), and the 2023 batch had 86.67% accuracy (100% DO precision, 33.33% DO recall). This model is very good at validating students who are safe from DO (100% recall of Not DO in all batches). Even so, the model still needs to be improved so that it can find all students who are at risk of dropping out (DO) as a whole. The prediction results for students with the potential for DO at ISTEK Widuri Jakarta are expected to support more optimal prevention efforts and contribute to improving the quality of education.
KLASIFIKASI CITRA WADAH MINUMAN REUSABLE DAN NON-REUSABLE MENGGUNAKAN MOBILENETV2 Ramanda, Dea; Hasan, Fuad Nur; Kuntoro, Antonius Yadi
JURNAL ILMIAH INFORMATIKA Vol 13 No 02 (2025): Jurnal Ilmiah Informatika (JIF)
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v13i02.10349

Abstract

Single-use plastic waste, particularly from beverage bottles, remains a significant contributor to the increasing volume of waste in Indonesia. The limited use of reusable beverage containers underscores the urgent need for technological innovations that can support efficient waste segregation. Addressing this issue, the present study proposes a computer vision-based image classification system designed to automatically distinguish between reusable and non-reusable drinking containers. This research adopts a quantitative experimental approach, employing the MobileNetV2 architecture through transfer learning techniques. The model was trained with augmented and normalized datasets to enhance its generalization across diverse image inputs. Evaluation results demonstrate strong classification performance, achieving 96% accuracy, 99% precision (for tumblers), 95% recall, and a 97% F1-score. These outcomes indicate the effectiveness of MobileNetV2 in identifying visual patterns between container types and its potential for deployment in image-driven waste management systems.
ANALISIS SENTIMEN PENGGUNA APLIKASI MYPERTAMINA MENGGUNAKAN METODE NAÏVE BAYES BERBASIS DATA ULASAN DI PLAY STORE Rifkiansyah, Rifkiansyah; Setiawan, Santoso; Sariasih , Findi Ayu
JURNAL ILMIAH INFORMATIKA Vol 13 No 02 (2025): Jurnal Ilmiah Informatika (JIF)
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v13i02.10351

Abstract

MyPertamina is PT Pertamina's digital application designed to support cashless and targeted distribution of subsidized fuel. Although it has been downloaded by millions of users, the app has received a variety of responses recorded in the form of reviews on the Google Play Store. This research was conducted to determine the tendency of user opinions through an automated sentiment analysis approach. Review data is collected by utilizing the Google Play Scraper library, then processed through preprocessing stages such as text normalization, character cleaning, tokenization, common word removal, and stemming. Positive and negative sentiment labels are assigned with the help of the IndoBERT pre-trained model. The next process includes conversion of text to numerical form with TF-IDF method and application of Multinomial Naïve Bayes algorithm for classification. The model is tested using confusion matrix and 10-Fold Cross Validation. The results showed that the majority of user reviews were negative (63.65%), and the classification model achieved 89.25% accuracy, 87.5% precision, 82% recall, and 84.69% F1-score. This shows that the approach used is effective in identifying public perceptions of MyPertamina application services.
IMPLEMENTASI WEB LAUNDRY DENGAN METODE AGILE UNTUK MENINGKATKAN EFISIENSI Illahi, Rendy Rahmad; Hutabri, Ellbert
JURNAL ILMIAH INFORMATIKA Vol 13 No 02 (2025): Jurnal Ilmiah Informatika (JIF)
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v13i02.10356

Abstract

Rapid developments in industry and information technology have created increasingly fierce competition to create new innovations and maintain competitiveness in the global marketplace. The development of information systems is currently rapid and dynamic, with many people relying on them to simplify their work activities. One of the easiest forms of information systems to develop is a web-based information system. This research aims to develop a web-based information system for Khendy Laundry. Currently, Khendy Laundry still uses a traditional system, namely manual recording and transactions using paper receipts. With this method, customer and order data are sometimes lost due to damaged or lost receipts, so the main goal is to record transactions digitally. The research method used is the Agile method. The results show that this new system successfully reduces the risk of errors and data loss, speeds up, and simplifies report generation. This system improves operational efficiency at the laundry.
PENERAPAN DATA MINING DALAM PENILAIAN KINERJA AKADEMIK SISWA/I SMP YPI PULOGADUNG DENGAN METODE K-MEANS CLUSTERING Nabilatul Adzra, Salsa; Hasan, Fuad Nur; Kuntoro, Antonius Yadi
JURNAL ILMIAH INFORMATIKA Vol 13 No 02 (2025): Jurnal Ilmiah Informatika (JIF)
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v13i02.10396

Abstract

Improving the quality of education requires an objective, systematic, and data-driven academic performance assessment system. One technological approach that can be used to support this is data mining, specifically the K-Means Clustering method. This studyaims to cluster student academic data based on report card grades for the odd semester of the 2024/2025 academic year using the K-Means algorithm. Data processing was performed using RapidMiner software, with the optimal number of clusters selected at three (K=3) based on the Davies Bouldin Index (DBI) of 0.077. The clustering results form three main categories: Cluster 0 contains 174 students with average academic performance, Cluster 1 contains only one student with the lowest performance, and Cluster 2 contains 107 students with high academic performance. This grouping provides more structured and useful information for schools in designing targeted academic development strategies. This study demonstrates the effectiveness of the K-Means Clustering method in identifying student academic patterns and classifications.
ANALISIS SENTIMEN PROGRAM MAKAN GRATIS PADA PLATFORM X MENGGUNAKAN AGORITMA NAÏVE BAYES Laia , Metodius Modianus; Hasan, Fuad Nur; Kuntoro, Antonius Yadi
JURNAL ILMIAH INFORMATIKA Vol 13 No 02 (2025): Jurnal Ilmiah Informatika (JIF)
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v13i02.10427

Abstract

The Free Meal Program is one of the government’s strategic policies that has received various public responses, especially on social media Platform X (formerly Twitter). This study aims to analyze the level of public sentiment toward the Free Meal Program on Platform X. The classification method used is the Naïve Bayes algorithm, with model validation performed using the K-Fold Cross Validation technique. A total of 3,600 Indonesian-language tweets relevant to the Free Meal Program were collected through a web scraping process, followed by text preprocessing steps such as case folding, cleaning, tokenizing, stopword removal, and stemming. Data labeling was carried out semi-automatically using the IndoBERT model, and the tweets were then classified into two sentiment categories: positive and negative. The Naïve Bayes model was trained using the TF-IDF representation and tested on a test set comprising 20% of the total dataset. The evaluation results showed that the Naïve Bayes algorithm achieved an accuracy of 86.46%, precision of 86.55%, recall of 95.25%, and an F1-score of 90.77% on 458 test tweets. Validation using 10-fold cross-validation yielded an average accuracy of 86.74%. These results indicate that the Naïve Bayes algorithm demonstrates good classification performance and stable generalization in classifying public sentiment regarding the Free Meal Program. This research is expected to serve as a supporting tool in mapping public opinion based on social media

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