Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika

PREDIKSI EMOSI DALAM TEKS BAHASA INDONESIA MENGGUNAKAN MODEL INDOBERT

2025-01-30T06:15:12+00:00

This study aims to predict emotions in Indonesian text using the IndoBERT model. Emotions play an essential role in human communication and have a significant impact on sentiment analysis and natural language processing. In Indonesia, the lack of optimized datasets and models for emotion analysis in the Indonesian language poses a major challenge. This research utilizes IndoBERT, a BERT-based model specifically trained for Indonesian, to predict six categories of emotions: anger, sadness, happiness, love, fear, and disgust. The research methodology includes data collection from social media X, data preprocessing, emotion labeling, model training, and performance evaluation using metrics such as accuracy, precision, recall, and F1-score. Results show an overall model accuracy of 73%, with strong performance in recognizing emotions like "disgust" and "fear," although there are misclassifications in distinguishing similar emotions like "happiness" and "love." These findings indicate that IndoBERT has significant potential for emotion prediction in the Indonesian language and provides a foundation for developing more culturally relevant NLP technologies for Indonesia.

PENERAPAN TEKNOLOGI AUGMENTED REALITY (AR) DALAM PEMBELAJARAN KOSA KATA BAHASA INGGRIS

2025-01-30T06:28:17+00:00

Teknologi dalam dunia pendidikan sangat mempengaruhi minat belajar dibandingkan dengan belajar hanya dengan buku teks. Teknologi dapat meningkatkan pemahaman masyarakat terhadap kosakata bahasa Inggris, salah satunya adalah teknologi yang dikenal dengan Augmented Reality yang menghubungkan dunia digital dengan lingkungan pengguna secara real-time. Aplikasi pembelajaran ini diciptakan untuk mengatasi dampak negatif penggunaan smartphone dan mengajarkan kosakata bahasa Inggris sebagai pengenalan awal dalam pembelajaran. Media pembelajaran interaktif ini ditujukan untuk meningkatkan daya ingat pengguna dan meningkatkan fokus mereka terhadap layanan pembelajaran. Tidak hanya dapat memberikan informasi dan pengetahuan, tetapi juga dapat menghibur pengguna. Tujuan dari penelitian ini adalah untuk membuat aplikasi “Augmented Reality English Vocabulary Learning”, dengan menggunakan metode Multimedia Development Life Cycle (MDLC). Augmented Reality (AR) dapat menawarkan solusi yang inovatif, informatif, dan menarik untuk pembelajaran. Selain itu, teknologi ini memiliki kemampuan untuk menyajikan objek virtual dalam bentuk 3D secara real time.

OPTIMASI HASIL PERAMALAN BROWN’S WEIGHTED EXPONENTIAL MOVING AVERAGE MENGGUNAKAN METODE LEVENBERG-MARQUARDT (STUDI KASUS: HARGA BERAS DI KALIMANTAN TIMUR)

2025-01-30T06:32:22+00:00

Rice is a staple food for Indonesian people whose price often fluctuates. Throughout the period from January 2021 to September 2024, the price of rice in East Kalimantan continued to increase, forming a trend pattern. Data forecasting with a trend pattern can be done using the Brown's Weighted Exponential Moving Average (B-WEMA) method which uses smoothing, weighting, and order parameters in its calculations. In this method, a larger weighting is given to the latest data and the order used is a high order. In addition, determining the smoothing parameters that provide the best accuracy value is usually done by the trial-and-error method. To increase the accuracy value of the B-WEMA method, smoothing parameter optimization can be carried out using the Levenberg-Marquardt method. The purpose of this study was to apply the B-WEMA method with Levenberg-Marquardt optimization to rice price forecasting in East Kalimantan. The results showed that the smoothing parameters obtained by the B-WEMA method before optimization were 0,7 with an accurate value of MAPE is 0,820%. After optimization, the optimal smoothing parameter obtained was 0,652 which resulted in an accurate value of MAPE is 0,818%. This indicates an increase in the accuracy value. Based on the optimization results, the forecast results for the next 3 periods were obtained, namely Rp16.070 for October; Rp16.027 for November; and Rp15.985 for December.

SKEMA JARINGAN TROUBLESHOOT MENGGUNAKAN CISCO PACKET TRACER

2025-01-30T06:44:15+00:00

Penelitian ini bertujuan untuk mengidentifikasi dan mengatasi berbagai permasalahan jaringan komputer melalui pendekatan simulasi menggunakan Cisco Packet Tracer. Metode troubleshooting berbasis model OSI diterapkan untuk memecahkan skenario permasalahan seperti koneksi fisik yang terputus, kesalahan konfigurasi IP, kegagalan DHCP, konflik VLAN, dan masalah routing. Simulasi ini menunjukkan efektivitas Cisco Packet Tracer dalam memberikan solusi praktis dan interaktif terhadap tantangan jaringan modern. Penelitian ini juga memberikan panduan langkah-langkah troubleshooting yang sistematis, meningkatkan pemahaman pengguna tentang manajemen jaringan, dan mendukung proses pembelajaran interaktif di bidang teknologi informasi. Hasil penelitian memperlihatkan bahwa penggunaan Cisco Packet Tracer dapat meningkatkan efisiensi troubleshooting hingga 30% dan pemahaman konseptual hingga 45%. Dengan demikian, penelitian ini berkontribusi pada pengembangan keterampilan analitis dan teknis yang relevan dalam dunia pendidikan dan profesional.

IMPLEMENTASI SISTEM INFORMASI DESA BERBASIS SMART VILLAGE DALAM MENDUKUNG TRANSFORMASI DIGITAL DI PEDESAAN STUDI KASUS: DESA SUKADAMAI

2025-01-30T06:48:16+00:00

Sukadamai Village is located in Manggelewa Sub-district, Dompu Regency, West Nusa Tenggara Province. Sukadamai Village is a remote area situated far from the city center, making administrative services an essential aspect for the community. However, several issues are associated with the management of population data, particularly in administrative processes. The data management is entirely conducted manually, utilizing physical record books and printed office media. Moreover, villagers must visit the village office in person to request information and complete administrative tasks. To address these challenges, the authors developed a web-based village information system that supports the concept of a smart village. This system aims to assist the local government and surrounding community in streamlining administrative tasks and ensuring consistent information dissemination. Based on testing, the system received an 89% approval index, with 30 respondents stating they "STRONGLY AGREE" on the implementation of an Android-based village information system. The objective of this study is to leverage technological advancements to improve administrative efficiency. The trial results indicate that the system is effective and applicable in real-world scenarios.

SISTEM KEAMANAN JARINGAN KOMPUTER BERDASARKAN AHLI FORENSIK

2025-01-30T06:54:18+00:00

Perkembangan teknologi yang semakin pesat dalam jaringan komputer membuat meningkatnya kebutuhan akses jaringan untuk memudahkan pekerjaan seperti kualitas jaringan yang stabil, cepat, dan efisien serta keamanan jaringan yang terkendal, Forensik Jaringan seperti detektif komputer. Forensik membantu mencari tahu siapa yang mencoba merusak jaringan komputer dengan melihat petunjuk dan informasi dari rekaman komputer. Salah satu cara seseorang menyerang komputer disebut serangan Distributed Denial of Service (DDoS). Hal ini terjadi ketika banyak komputer mengirim terlalu banyak permintaan ke satu komputer, sehingga komputer tersebut sangat sibuk sehingga tidak dapat membantu orang lain. Di Universitas Ahmad Dahlan di Yogyakarta, para peneliti mempelajari cara menemukan serangan ini. Mereka menggunakan perangkat lunak khusus yang disebut Winbox RouterOS untuk melihat hal-hal seperti siapa yang menyerang, berapa banyak permintaan data yang dikirim, dan kapan serangan terjadi. Mereka juga menguji sistem keamanan komputer mereka dengan program lain yang disebut LOIC untuk melihat seberapa baik sistem tersebut dapat melindungi dari serangan DDoS.[1]

PERBANDINGAN ALGORITMA LOGISTIC REGRESSION DAN ADAPTIVE BOOSTING (ADABOOST) DALAM KLASIFIKASI PENYAKIT GAGAL JANTUNG

2025-01-30T07:06:23+00:00

The heart is a vital organ in the human body, responsible for pumping blood throughout the body via the circulatory system. The heart is responsible for the delivery of oxygen and nutrients to tissues, as well as the removal of carbon dioxide and other waste products. Any disruption to the heart's functioning has the potential to be fatal to human survival. One such disruption is heart failure disease, also known as congestive heart failure (CHF). It is of the utmost importance to detect heart failure at an early stage. The early detection of heart failure disease can be achieved through the utilisation of machine learning, which can mitigate the low probability of this disease. This research employs a machine learning system based on artificial intelligence, utilising logistic regression and adaptive boosting (adaboost) algorithms. The research findings indicate that the classification of heart failure can be accurately determined using a range of parameters. The highest accuracy results, derived from this study, are 90% accuracy, 84% precision, 88% recall, and 88% F1-score. These results are exclusively attributable to the adaboost algorithm. In comparison to the logistic regression algorithm, the resulting accuracy is still below that of the adaboost algorithm, with the results being 86% accuracy, 76% precision, 79% recall, and 88% F1-score. It can therefore be concluded that the adaboost algorithm is more effective than the logistic regression algorithm in classifying heart failure disease. This is particularly the case when the selected data set exhibits an unbalanced number of labels.

INFRASTRUKTUR JARINGAN KOMPUTER BERBASIS CISCO PACKET TRACER DI LABKOM UNIVERSITAS MUHAMMADIYAH SUKABUMI

2025-01-30T07:12:19+00:00

Computer network technology plays a crucial role in supporting
teaching and learning activities. A Local Area Network (LAN) is a type
of computer network that connects devices within a specific area. The
application of network technology supports the learning process,
including in the Computer Laboratory of the Information Technology
Education Program. This research aims to design and configure the
computer network infrastructure in the laboratory using wired media.
The method used is the Network Development Life Cycle (NDLC),
which relies on previous development processes. The research
methodology involves simulation with Cisco Packet Tracer to design
network topology and configure devices. The research results include
the design of computer network infrastructure using wired media and
optimal IP configuration. Findings indicate that the devices within the
designed network topology are interconnected and can access the
internet effectively.

IMPLEMENTASI ALGORITMA FIFO DAN DESCENDING PRIORITY QUEUE PADA SISTEM ANTRIAN PELAYANAN KESEHATAN PUSKESMAS BUNTOK

2025-01-31T02:44:19+00:00

Healthcare services at Puskesmas Buntok often face challenges in managing patient queues, leading to long waiting times and decreased patient satisfaction. This study aims to design and implement an intelligent queue management system based on a website using FIFO (First In First Out) and Descending Priority Queue algorithms, as well as integrate wait time prediction using the Least Squares method in PHP Machine Learning. The software development methodology employed is the Waterfall model, encompassing requirement definition through flowchart creation, system and software design using UML (Use Case Diagram, Activity Diagram, and Class Diagram), implementation with PHP and MySQL, and system testing using black box testing and accuracy testing for the wait time prediction feature. The research results indicate that the developed intelligent queue system efficiently and effectively manages the order of patient services. The integration of wait time prediction provides accurate estimates, assists patients in planning their visits, and enhances the operational efficiency of the health center. System testing confirms that all functions operate as expected, making the website suitable for use as the official platform of Puskesmas Buntok. This implementation successfully improves the quality of healthcare services by reducing patient waiting times, increasing registration efficiency, and optimizing medical service processes through an innovative intelligent queue system