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INDONESIA
Jurnal Teknologi Informasi dan Multimedia
ISSN : 27152529     EISSN : 26849151     DOI : https://doi.org/10.35746/jtim.v2i1
Core Subject : Science,
Cakupan dan ruang lingkup JTIM terdiri dari Databases System, Data Mining/Web Mining, Datawarehouse, Artificial Integelence, Business Integelence, Cloud & Grid Computing, Decision Support System, Human Computer & Interaction, Mobile Computing & Application, E-System, Machine Learning, Deep Learning, Information Retrievel (IR), Computer Network & Security, Multimedia System, Sistem Informasi, Sistem Informasi Geografis (GIS), Sistem Informasi Akuntansi, Database Security, Network Security, Fuzzy Logic, Expert System, Image Processing, Computer Graphic, Computer Vision, Semantic Web, Animation dan lainnya yang serumpun dengan Teknologi Informasi dan Multimedia.
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Articles 17 Documents
Search results for , issue "Vol. 8 No. 1 (2026): February" : 17 Documents clear
Perancangan Dan Implementasi Game Interaktif untuk Pembelajaran Digital pada Pelajaran TIK di MTsN 2 Banda Aceh Menggunakan Scracth Ramadhana, Zahwanul; Dewi, Sarini Vita
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 1 (2026): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i1.944

Abstract

ICT learning currently demands the use of innovative learning media, to increase students' moti-vation and understanding of the material being studied, but at MTsN 2 Banda Aceh, convention-al methods such as lectures still dominate, which reduce students' motivation towards storage device and output device materials. This study aims to design, develop, and implement learning media in the form of scratch-based interactive games as a means of ICT (information and com-munication technology) learning to increase interactivity, learning motivation, and understand-ing of grade VIII students towards storage device and output device materials. Development re-search with a 4D model (Define, Design, Develop, Disseminate) and a mixed methods approach integrates quantitative data from questionnaires and qualitative data from observations and in-terviews. The results of media expert validation reached an average of 91% (strongly agree), while the assessment of 36 students showed an average score of 91% (very good) in the aspects of design, navigation, material understanding, and learning motivation. The Maze Tech game has been proven to be feasible, effective, and fun as an ICT digital learning media that supports inde-pendent and active learning. Furthermore, the Maze Tech game was developed with attention to the characteristics of junior high school students who tend to prefer visual and challenge-based learning. The integration of game elements, such as maze navigation, audio-visual feedback, and evaluative quizzes, provides a contextual and meaningful learning experience. This media also encourages active student involvement in the learning process, so it serves not only as a means of entertainment but also as an effective pedagogical tool. Therefore, the results of this study are ex-pected to contribute to the development of game-based digital learning media and serve as a ref-erence for educators in implementing ICT learning innovations in the madrasah environment.
Rancang Bangun Aplikasi Laporan Keuangan Berbasis Web Dengan Metode Prototype (Studi Kasus: Praktik Mandiri Bidan Nining) Putrie, Dewi Sonia; Putro, Aditya Dwi; Wibisono, Gunawan
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 1 (2026): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i1.810

Abstract

Technological advances in the digital era have had a significant impact on various aspects of life, including the financial reporting system. One form of this transformation is the use of web-based applications to facilitate the process of managing and presenting financial data. PMB Nining, an Independent Midwife Practice in Sukatenang Village, Bekasi Regency, still carries out manual financial reporting using books, which risks causing recording errors, physical data damage, and delays in reporting. This study aims to design and build a web-based financial reporting system using the prototype method with the Laravel framework. This approach involves users in every stage of the design so that the system developed is in accordance with their needs. In addition, system testing is carried out using the black box testing method to ensure that each function runs according to specifications. The test results show that all main features, such as user authentication, transaction recording, data validation, printing reports in PDF and Excel formats, and staff data management, function properly and achieve a 100% success rate. The system is also able to handle various types of input, both valid and invalid. The presence of dashboard and report filter features also supports a more efficient financial monitoring process. Thus, this system can be a solution to improve the accuracy and effectiveness of financial reporting at PMB Nining, while also contributing to the development of information technology in the health services sector.
Game Virtual Tour Pengenalan Sistem Tata Surya Berbasis VR Google Cardboard dan Voice Command Alkhaq, Muh Ulil; Asmiatun, Siti
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 1 (2026): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i1.854

Abstract

The solar system is an essential topic in elementary school science education, playing a role in developing students' critical thinking skills and scientific understanding. However, conventional teaching methods often make students passive recipients of information, discouraging interaction and independent exploration. This can decrease interest and engagement in learning. Therefore, a more interactive and engaging approach is necessary to teach students about the solar system ef-fectively. This game uses VR technology and voice commands to provide an immersive experience exploring the solar system. Players can interact with objects in the solar system. It also features voice control, which allows students to interact with objects in the solar system and access addi-tional information. The average score on the questionnaire survey of the application was 86.30%. Integrating VR and voice commands has proven effective in increasing students' interest in learn-ing and facilitating navigation in immersive learning environments.
Smart Admissions: Meningkatkan Efesiensi Proses Penerimaan Mahasiswa Baru dengan Chatbot Interaktif RS, Asmaul Husna; Khalil, Adawiyah Asti; Putri, Mindi Richia; Rifqi, Muhammad Ari; Kurniawati, Ari
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 1 (2026): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i1.888

Abstract

The new student admission (PMB) process at the Baru Universitas Bima Internasional MFH often faces challenges related to time efficiency and administrative burdens due to repetitive inquiries from prospective students. This research aims to design and build an interactive chatbot system named "Sipenmaru MFH" to enhance the efficiency and effectiveness of the PMB process. The de-velopment method used is Extreme Programming (XP), which allows for an adaptive and flexible process. Data was collected through interviews and questionnaires to build the chatbot's knowledge base. The application was developed using the Flutter framework with a NoSQL da-tabase, and its functionality was tested using the Black Box testing method. The result of this re-search is a functional chatbot application with a user-friendly interface, capable of providing fast and accurate responses to common questions regarding new student admissions. The implemen-tation of this chatbot has successfully provided easier access to information for prospective stu-dents and reduced the committee's workload, thus making the admission process more efficient.
Sistem Informasi Re-Actions pada Fitur Sentimen Data Aduan Publik dan Reporting Bagaskara, Muhammad Fatih; Renanti, Medhanita Dewi
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 1 (2026): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i1.897

Abstract

An effective public complaint management system plays an essential role in enhancing governmental transparency, accountability, and responsiveness to public needs. This study aims to develop Re-Actions, a web-based information system designed to facilitate the structured collection, processing, and monitoring of public complaints. The system integrates an automatic sentiment analysis feature to identify emotional tendencies or public opinions from complaint texts using a machine learning model. The software was developed using the Scrum methodology, enabling an iterative and adaptive development process aligned with user requirements. The sentiment analysis model was built using the Support Vector Machine (SVM) algorithm and trained on 2,756 public complaint records obtained from the archival data of the Layanan Aspirasi Kotak Saran Anda (LAKSA) system of Tangerang City. Experimental results show that the sentiment analysis model achieved an accuracy of 79%, indicating a reliable capability in classifying public complaints into positive, negative, and neutral categories. This level of accuracy is consistent with previous studies on machine learning-based sentiment analysis in public service domains, which generally report performance within the 70%–80% range, depending on data characteristics and applied methods [3], [12], [13]. Furthermore, the system was evaluated using Black-box Testing to verify functional correctness and User Acceptance Testing (UAT) to assess usability and user satisfaction. All core system features operated as expected, and the UAT results indicated a user satisfaction rate of 92%, reflecting a high level of system acceptance and consistency with similar information system evaluations in the public sector [16]. These findings demonstrate that integrating machine learning techniques into public complaint information systems can enhance information management effectiveness, accelerate data-driven decision-making, and support improvements in public service quality in Tangerang City.
Implementasi Algoritma FP-Growth untuk Sistem Rekomendasi Produk Kebutuhan Pokok pada E-Commerce Herlambang, Mahjid; Susanto, Susanto
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 1 (2026): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i1.900

Abstract

The rapid development of e-commerce in Indonesia necessitates recommendation systems that can capture user purchasing patterns accurately, adaptively, and in a data-driven manner. This study implements the FP-Growth algorithm to analyze transaction data from a self-developed essential-goods e-commerce platform. The research dataset consists of 60 user accounts with a total of 600 completed transactions, processed using a Python-based analytical module and au-tomatically integrated into a Laravel backend through a dedicated execution script. The FP-Growth algorithm is applied to generate frequent itemsets and association rules using a min-imum support of 0.01, a minimum confidence of 0.1, and a minimum lift of 1.0. The results indi-cate that the most dominant associative patterns occur among kitchen staple products such as in-stant noodles, chicken eggs, and wheat flour, as well as household cleaning products such as de-tergents and fabric softeners. Several rules exhibit confidence values as high as 0.9615 and lift values up to 4.451, indicating strong and statistically significant relationships between products. System performance evaluation using a Top-4 recommendation scheme shows a Hit Rate of 54.35% and a Recall of 54.35%, demonstrating that the system is able to provide relevant recom-mendations for the majority of transactions. This implementation is shown to improve recom-mendation accuracy while strengthening personalization and cross-selling strategies on essen-tial-goods e-commerce platforms. These findings confirm that FP-Growth is an effective and effi-cient method for identifying empirical purchasing patterns and supporting the development of recommendation systems in small- to medium-scale e-commerce environments.
Utilizing Natural Language Processing for the Analysis of BMKG Decadal Atmospheric Dynamics Reports in 2025 Ramadhan, Ardiansyah; Azis, Aaz Muhmmad Hafidz
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 1 (2026): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i1.946

Abstract

The Meteorology, Climatology, and Geophysics Agency (BMKG) publish decennial reports that provide valuable insights into Indonesia's meteorological conditions and their temporal fluctuations. However, due to their narrative structure, conducting direct quantitative analysis is problematic. This study seeks to address this issue by using a transparent, repeatable natural language processing (NLP) method to identify temporal trends in climatic conditions favourable to the formation of acid rain. The collection contains 36 BMKG decadal atmospheric dynamics studies for 2025. The proposed approach entails gathering textual input, performing basic preprocessing (case normalization, character sanitization, space-based tokenization, and stop-word removal), and subsequently employing predefined keyword dictionaries for analysis. These dictionaries delineate weather conditions that either facilitate or inhibit the formation of acid rain. The scores for acid rain conditions are determined by the frequency of specific keywords, adjusted for the document's length. Subsequently, they are categorized into groups utilizing statistical thresholds derived from the mean and standard deviation of the adjusted scores. Non-parametric statistical tests are employed to examine temporal patterns with greater specificity. The findings indicate that normalized acid rain scores are elevated in the initial years of the decade, specifically 2025, before gradually declining until year-end. The Spearman rank correlation test reveals a statistically significant negative correlation between normalized scores and time (\rho = -0.494, p = 0.0022). The Mann–Kendall test indicates a significant downward trend (Z = -2.902). These results demonstrate that the climatic conditions responsible for acid rain occurred only temporarily, rather than year-round. The core element of this work is a straightforward, lexicon-based NLP approach that is easily understood, replicable, and applicable, and can transform narrative atmospheric reports into structured quantitative metrics. This is beneficial for research on atmospheric dynamics and environmental analysis with official written data.

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