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Jurnal Teknologi Informasi dan Multimedia
Published by Puslitbang Sekawan Institute Nusa Tenggara
ISSN : 27152529     EISSN : 26849151     DOI : https://doi.org/10.35746/jtim.v2i1
Core Subject : Science,
Computer Science & IT
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 332 Documents
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Pemanfaatan IoT dalam Sistem Kontrol Lingkungan Tanaman Drosera sessilifolia Menggunakan Fuzzy Type-2 Rhimba Aulia; Chrystia Aji Putra; Henni Endah Wahanani
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 2 (2026): May
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i2.980

Abstract

Drosera sessilifolia is a carnivorous plant that requires optimal environmental conditions, par-ticularly in terms of light intensity, temperature, and water level. This study aims to utilize the In-ternet of Things (IoT) to implement an environmental control system using Type-2 Fuzzy Logic for monitoring and controlling the environmental parameters of Drosera sessilifolia. The system uses an ESP32 microcontroller supported by several sensors, including a DS18B20 temperature sensor, an LDR light intensity sensor, and a water level sensor, to monitor environmental parameters ac-curately. The acquired data are processed using the Type-2 Fuzzy method to generate control deci-sions for actuators such as a heater, peltier, lamp, peristaltic pump, and fan. The Blynk platform is used to display environmental conditions, including temperature, light intensity, water level, and actuator decision status in real time. Based on the results of a 7-day indoor test conducted in the morning and at night, the average morning temperature was 30.04°C and the average nighttime temperature was 27.91°C, while the average light intensity was 1278 ADC in the morning and 2525.43 ADC at night, and the average water level was 1.16 cm in the morning and 0.99 cm at night. Based on 14 observations over 7 days, the system showed appropriate control responses in all observed scenarios, resulting in a 100% response success rate for the detected conditions. The novelty of this study lies in the implementation of an IoT-based Type-2 Fuzzy system specifically designed for the indoor cultivation of Drosera sessilifolia by simultaneously controlling temper-ature, light intensity, and water level. In addition, this study highlights the novelty of integrating Type-2 Fuzzy Logic and IoT for carnivorous plants, which remains very limited, especially for the cultivation of Drosera sessilifolia in a controlled indoor environment. The test results show that the system is capable of controlling temperature, light intensity, and water level effectively and responsively to environmental changes. The Type-2 Fuzzy method also produces stable and adap-tive control decisions. This system offers a solution for real-time indoor monitoring and environ-mental control of Drosera sessilifolia.
Penerapan E-CRM Berbasis Web Menggunakan Metode RAD pada Showroom Wali Sanga Motor Jihan Salsabila Arifin; Bayu Priyatna; Fitria Nurapriani; April Lia Hananto
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 2 (2026): May
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i2.986

Abstract

Customer service at Wali Sanga Motor Showroom is still conducted manually, causing delays in information delivery, unstructured customer data management, and less optimal handling of or-ders and customer complaints. This study aims to develop a web-based Electronic Customer Rela-tionship Management (E-CRM) system using the Rapid Application Development (RAD) method to improve service effectiveness and customer relationship management. The RAD method was applied through stages of requirements planning, prototyping design, system construction, and implementation. The system was developed using the Laravel framework and MySQL database with main features including product information management, online motorcycle ordering, cus-tomer complaint services, and administrative data management. System testing was carried out using User Acceptance Test (UAT) and White Box Testing on all functional requirements that had been designed. The test results show that the system runs 100% in accordance with the UAT sce-narios and all main modules function according to user needs without any significant logical er-rors. The implementation of this E-CRM system is expected to improve service efficiency, acceler-ate responses to customers, and support integrated and sustainable management of customer ser-vice data at Wali Sanga Motor Showroom.
Game Edukatif pada Materi Teks Wawancara untuk Mendukung Literasi Membaca Siswa Sekolah Dasar Ragil Dian Purnama Putri; Wiwik Kusuma; Tri Lestari
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 2 (2026): May
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i2.943

Abstract

This study aims to develop an educational game-based learning media using Smart Apps Creator 3, named “SIMAKA,” to support elementary school students’ reading literacy in interview text materials. The method used is Research and Development (R&D) with the ADDIE model, which includes the stages of analysis, design, development, implementation, and evaluation. Data collection techniques involve validation questionnaires and user responses, which are analyzed quantitatively in descriptive form using percentages. The results show that the media achieved a feasibility level of 92.8% from experts, 95% from teachers, and 93% from students, all categorized as very good. These findings indicate that the developed media is feasible to be used as an alternative learning tool to support students’ reading literacy.
Hyperparameter Tuning Metode Long Short-Term Memory (LSTM) untuk Prediksi Harga Bawang Merah di Pasar Tradisional Jawa Timur M. Latifur Rahman; Mamluatul Hani'ah; Muhammad Afif Hendrawan
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 2 (2026): May
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i2.976

Abstract

Shallots are one of the essential food commodities in East Java, the price of which frequently fluctuates due to seasonal influences and distribution factors. This price uncertainty often weakens the community's purchasing power and makes it difficult for farmers and sellers to make decisions. Therefore, this study proposes a daily shallot price prediction model for nine regions in East Java using the Long Short-Term Memory (LSTM) method with hyperparameter tuning to obtain the best-performing model. This study utilizes daily price data from PIHPS (Pusat Informasi Harga Pangan Strategis / Strategic Food Price Information Center) over four years, from January 1, 2021, to December 31, 2024. The research stages begin with data preprocessing, which includes imputing missing values to ensure continuity of the time sequence, data normalization, and arrangement of data based on temporal order (time series). To obtain the optimal model, the data was split into 80% for training and 20% for testing. Based on the experimental results, the optimal model configuration was found using a Window Size of 7 (the last seven days of data), 114 Epochs, and a Batch Size of 64. Furthermore, the reliability of the model was measured using MAPE, where the average across all regions fell below 10%, which is classified as "Very Good" based on MAPE interpretation standards. Additional testing using 2025 data as an independent dataset further confirmed that the model remains consistent and stable, as evidenced by an average MAPE of 3.10% across the nine regions.
Analisis Pola Pembelian Konsumen Menggunakan Algoritma FP-Growth pada Data Transaksi Restaurant Burger Nindya Alifia Khumaira; Dadang Priyanto; Hairani Hairani; Galih Hendro Martono; Moch. Syahrir; Husain Husain
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 3 (2026): August
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i3.983

Abstract

Fast-food restaurants generate large volumes of transaction data that can be utilized to understand customer purchasing behavior and support business decision-making. However, transaction data are often used only for operational reporting, limiting their potential for identifying product association patterns. This study aims to apply the Frequent Pattern Growth (FP-Growth) algorithm to discover frequent itemsets and association rules from burger restaurant transaction data and implement the results in a web-based application. The dataset used consists of 2,001 burger restaurant transactions collected from Kaggle, covering the period 2021–2023. The research process included data preprocessing, transaction transformation, FP-Tree construction, frequent itemset extraction, and association rule generation using a minimum support threshold of 2 transactions and a minimum confidence threshold of 60%. The results revealed that the most frequent items were Save Point Sundae (191 transactions), Health Potion Smoothie (181 transactions), and Cheat Code Cookies (164 transactions). Several association rules achieved a confidence value of 100%, indicating a strong co-occurrence relationship between products. Furthermore, the rules Avatar Avocado -> Cosmic Rings and Cosmic Rings -> Avatar Avocado obtained a lift ratio of 1.50, demonstrating a positive association between the two items. These findings indicate that FP-Growth is effective in identifying customer purchasing patterns and can support promotional strategies, product bundling, and inventory management through data-driven decision-making.
Perancangan Aplikasi FinTech Locavest sebagai Sistem Pendukung Keputusan Analisis Kelayakan Lokasi Usaha Menggunakan Metode Design Thinking Muhamad Ikhsan Tazudin; Randhu Fulki Ramadhan; Hyuga Ramdhan Noer; Genta Nazwar Tarempa
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 2 (2026): May
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i2.987

Abstract

The development of financial technology (fintech) and artificial intelligence (AI) opens up oppor-tunities to increase efficiency and objectivity in business decision-making, including business loca-tion selection. However, the integration of fintech, property, and AI-based location analysis in a single mobile platform has rarely been comprehensively studied. This study designed a prototype of the Locavest application as an AI-based fintech solution for business location feasibility analy-sis using a Design Thinking approach. The development method included the stages of empathize, define, ideate, prototype, and test to ensure the suitability of the features to the needs of MSMEs and novice investors. Prototype validation was conducted using the System Usability Scale (SUS) with 10 user respondents, resulting in an average score of 85, indicating a very good level of usability (category "excellent"). This application is expected to become an integrated decision support sys-tem that can help users analyze business locations and property investments more quickly, meas-urably, and easily. The contribution of this research lies in the integration of fintech, property, and AI features in a single mobile application and the use of Design Thinking methods to produce in-novative and user-friendly digital solutions.
Game Edukasi Ilmu Pengetahuan Sosial (IPS) Berbasis Android menggunakan Metode R&D 4D di SMP Negeri 2 Rawalo Annas Ridwan Pangestu; Sigit Sugiyanto; Tito Pinandita; Dimara Kusuma Hakim
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 2 (2026): May
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i2.990

Abstract

Technological advancements have had a significant impact on the world of education, particularly in accelerating and simplifying the learning process for Social Studies (IPS) courses. This study aims to design an Android-based educational game for 9th-grade students at SMP Negeri 2 Rawalo using the Research and Development (R&D) method and the 4D model (define, design, develop, disseminate). This game was designed using the Construct 3 application and named “Society in A Game: Game of Social Changes and Digital Economy Growth.” The study involved 20 students, and the research utilized pre-tests and post-tests to measure improvements in learning outcomes as well as an application evaluation test using the System Usability Scale (SUS) based on a 1–4 Likert scale. The average pre-test score of 57.8 increased to 77.6 on the post-test, representing a 34.2% increase. Additionally, the average SUS score of 74.5 falls into the “Acceptable” category. The research results indicate that Android-based educational games can serve as an interactive learning medium while introducing the use of technology in the field of education.
Pemetaan Spasial Jemaat GPPS Betlehem Lombok Menggunakan Algortima K-Means Clustering dan Leaflet.js Ahmat Adil; Bambang Krimono Triwijoyo; Heroe Santoso; Muhammad Azwar; Raymond Putra Suntana
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 2 (2026): May
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i2.992

Abstract

The church as a place for people to gather requires accurate information to store congregational data. With the Geographic Information System (GIS) it will be easier for church officials to map congregations that number more than hundreds of people and share locations of scheduled activities. The purpose of this study is to implement the K-Means algorithm to map the distribution of the GPPS Bethlehem congregation so that it can provide informative and easy-to-understand spatial visualization.  The clustering algorithm method groups multiple data sets by explaining how data within a group has similar characteristics and how they differ from other groups.  The data in the form of geographic coordinates (latitude and longitude) of the congregation's location was then processed using the K-Means algorithm with a predetermined number of clusters. The processing results showed that the data was successfully grouped into several clusters based on location proximity, each cluster having a centroid as the center point of the group, the centroid value changing at each iteration until it reached a convergent condition. Based on the research results, it can be concluded that: The clustering process produces several groups (clusters) that represent the distribution pattern of congregations in a particular area with a clear cluster center (centroid) and visualization using Leaflet.js is able to display the clustering results in the form of an interactive map that is informative and easy for users to understand.
Optimization of Support Vector Machine Using SMOTE and Grid Search for Kidney Health Data Classification Muhammad Maulana; Zulkipli Zulkipli; Tanwir Tanwir; Dading Oktaviadi Resmiranta; Naufal Hanif; Raisul Azhar
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 2 (2026): May
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i2.993

Abstract

Kidney disease is a highly prevalent health problem that can seriously impact the quality of life of those affected. To improve diagnostic accuracy, machine learning methods are widely used to classify patient data. Class imbalance (imbalanced data) is one of the problems that often occurs in the classification process and can affect the performance of machine learning models, especially in detecting minority classes. This study aims to improve the performance of the Support Vector Machine (SVM) algorithm by applying the SMOTE (Synthetic Minority Over-sampling Tech-nique) and Grid Search methods in the data classification process. SMOTE is used to balance the class distribution by adding synthetic data to the minority class, while Grid Search is used to ob-tain optimal model parameters. The results show that the SVM model without handling data im-balance produces relatively low performance with an accuracy value of 51%, precision 17%, re-call 33%, and F1-score 23%. After applying the SMOTE method, the model performance increases significantly to 81% accuracy, 81% precision, 80% recall, and 81% F1-score. Furthermore, the ap-plication of Grid Search to the SVM + SMOTE model provides the best results with an accuracy of 84%, precision 82%, recall 81%, and F1-score 81% with an AUC value of 0,92. The findings of this study indicate that the combination of SMOTE and Grid Search is effective in improving the per-formance of the SVM algorithm in data classification. The novelty of this study demonstrates that data imbalance management and hyperparameter optimization play a crucial role in producing more accurate and optimal classification models.
Perancangan dan Implementasi Sistem Ticketing Support untuk Pengelolaan Pengaduan Pelanggan Affi Himmawan; Nur Wakhidah
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 3 (2026): August
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i3.996

Abstract

CV. Metamorphz Technology Solutions is a company operating in the information technology sector that receives various complaints and service requests from customers in its daily opera-tions. Previously, the customer complaint management process was carried out manually, causing inefficiencies in recording, tracking, and resolving complaint tickets. This condition resulted in slow customer response times and difficulty in monitoring complaint status in realtime. This study aims to implement support ticketing system to manage customer complaints at CV. Meta-morphz Technology Solutions. The research method used is the Agile Development method, which consists of five stages: requirements analysis, system design, implementation, testing, and maintenance. The system was developed using a web-based platform with a SQL Server data-base, equipped with a chatbot feature based on a Natural Language Processing (NLP) algorithm using a Rule-Based and TF-IDF (Term Frequency-Inverse Document Frequency) approach for au-tomatic classification and matching of complaint categories. The chatbot acts as the first line of customer interaction in receiving, classifying, and providing initial responses to complaints before forwarding them to the relevant technical team. The results show that the ticketing sys-tem integrated with the chatbot successfully streamlines the complaint handling process, enabling structured complaint recording, automated ticket assignment to the relevant technical team, and realtime monitoring of complaint status. System testing using the Black-Box Testing method showed that all system features function according to requirements, with a test success rate of 100% from nine testing scenarios conducted. The implementation of this ticketing system im-proves response time and service quality to customers, as well as facilitating performance moni-toring of the technical support team.

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