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All Journal Jurnal Algoritma Jurnal Wawasan Ilmiah Jurnal Teknologi Informasi dan Ilmu Komputer JAIS (Journal of Applied Intelligent System) Jurnal Ilmu Sosial dan Ilmu Politik JOIN (Jurnal Online Informatika) Edu Komputika Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Seminar Nasional Teknologi Informasi Komunikasi dan Industri JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal ULTIMATICS Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JURTEKSI Jurnal Sistem Cerdas Aiti: Jurnal Teknologi Informasi Jurnal Teknik Informatika (JUTIF) Teknika Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal PkM MIFTEK Jurnal Algoritma Engineering Science Letter Journal of Novel Engineering Science and Technology IT-Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Integrated : Journal Of Information Technology and Vocational Education JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Journal of Intelligent Systems Technology and Informatics International Journal of Applied Information Systems and Informatics Jurnal Elektronika dan Telekomunikasi
Dede Kurniadi
Institut Teknologi Garut
Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Other

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Perancangan Aplikasi Text To Speech Dalam Bahasa Indonesia Menggunakan Firebase Machine Learning Kit Berbasis Android Kurniadi, Dede; Nuraeni, Fitri; Raharja, Indra Trisna; Mulyani, Asri
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 9 No 6: Desember 2022
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2022965985

Abstract

Aplikasi text to speech dapat merubah teks menjadi keluaran suara menggunakan engine text to speech, namun teks tersebut harus berupa teks digital agar bisa di render. Sehingga, jika teks berada pada suatu objek maka harus diekstrak terlebih dahulu. Firebase Machine Learning Kit menyediakan API text recognition untuk membantu proses ekstrak teks. Firebase Machine Learning Kit (ML-Kit) juga menyediakan API language identifier untuk mendeteksi bahasa pada teks yang dibaca sehingga suara yang dikeluarkan dari teks yang dibaca dapat optimal dengan menggunakan dialek bahasa tertentu. Tujuan dari penelitian ini adalah membangun aplikasi text to speech dalam Bahasa Indonesia dengan penerapan Firebase Machine Learning Kit berbasis android. Dalam membangun aplikasi ini menggunakan metode extreme programming yang tahapannya terdiri dari planning, design, coding, dan testing. Hasil dari penelitian ini, berupa aplikasi yang dapat digunakan sebagai alat bantu pembelajaran bahasa asing dan alat digitaisasi teks serta terjemah ke dalam Bahasa Indonesia dan 34 dialek bahasa untuk keluaran suara text to speech. Selain itu, pada penelitian ini didapatkan nilai akurasi pengenalan teks dari tulisan tangan dan tulisan mesin, dengan rata-rata persentase akurasi untuk tulisan tangan sebesar 85,25%, sedangkan rata-rata persentase akurasi untuk tulisan mesin sebesar 87,35%. Dengan akurasi yang baik tersebut, maka aplikasi siap untuk dipergunakan sebagai alat bantu dalam proses pembelajaran bahasa asing oleh masyarakat Indonesia. AbstractText to speech applications can convert text into voice output using a text to speech engine, but the text must be digital text in order to render. So, if the text is in an object, it must be extracted first. The Firebase Machine Learning Kit provides a text recognition API to help extract text. The Firebase Machine Learning Kit (ML-Kit) also provides a language identifier API to detect the language in the text being read so that the sound emitted from the text read can be optimized by using a specific language dialect. The purpose of this research is to build a text to speech application in Indonesian with the application of an Android-based Firebase Machine Learning Kit. In building this application using the extreme programming method whose stages consist of planning, design, coding, and testing. The results of this study are in the form of applications that can be used as foreign language learning aids and text digitization tools and translations into Indonesian and 34 language dialects for text to speech voice output. In addition, in this study, the accuracy of text recognition from handwriting and machine writing was obtained, with an average percentage of accuracy for handwriting of 85.25%, while the average percentage of accuracy for machine writing was 87,35%. With good accuracy, the application is ready to be used as a tool in the process of learning foreign languages by the Indonesian people.
Sistem Informasi Geografis Pemetaan Data Terpadu Kesejahteraan Sosial di Kabupaten Garut Kurniadi, Dede; Mulyani, Asri; Firmansyah, Marshal; Abania, Nia
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 9 No 6: Desember 2022
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2022956098

Abstract

Dinas Sosial Kabupaten Garut berusaha dalam meningkatkan pelayanannya kepada masyarakat terutama dalam transparansi jumlah Data Terpadu Kesejahteraan Sosial (DTKS) per Kecamatan di Kabupaten Garut. Tetapi Dinas Sosial Kabupaten Garut saat ini belum mempunyai sistem informasi geografis yang menyediakan informasi jumlah DTKS per Kecamatan di Kabupaten Garut kepada masyarakat. Tujuan dari penelitian ini membangun sistem informasi geografis pemetaan data terpadu kesejahteraan sosial untuk memudahkan masyarakat mengetahui informasi jumlah DTKS per Kecamatan di Kabupaten Garut dengan memanfaatkan Teknologi Sistem Informasi Geografis (SIG). Metode yang digunakan adalah Rapid Application Development (RAD), dengan menggunakan tiga tahapan yaitu requirements planning, RAD design workshop, dan implementation. Bahasa pemrograman yang digunakan PHP dengan DBMS MySQL, dan Leaflet JavaScript Library. Penelitian ini menghasilkan Sistem Informasi Geografis Pemetaan Data Terpadu Kesejahteraan Sosial di Kabupaten Garut yang memiliki fitur peta DTKS kecamatan, pencarian data, fitur login super admin dan admin, serta fitur pengelolaan semua data oleh admin dan super admin. Penggunaan Metode RAD telah berhasil mengefektifkan waktu dalam pembangunan SIG ini, disamping hal tersebut hasil penilaian blackbox testing menunjukan hasil pengujian telah memenuhi semua hasil yang diharapkan oleh pengguna pada kebutuhan fungsional, dengan hasil tersebut diharapkan dapat memudahkan masyarakat untuk mengetahui informasi dan memeriksa status terdaftar di DTKS salah satunya melalui fitur pencarian data berdasarkan NIK (Nomor Induk Kewarganegaraan). AbstractThe Garut Regency Dinas Sosial is trying to improve its services to the community, especially in the transparency of the amount of Social Welfare Integrated Data (DTKS) per District in the Garut Regency. However, the Garut Regency Dinas Sosial currently does not have a geographic information system that provides information on the number of DTKS per sub-district in the Garut Regency to the public. This study aims to build a geographic information system for integrated social welfare data mapping to make it easier for the public to find information on the number of DTKS per sub-district in Garut Regency by utilizing Geographic Information System (GIS) technology. The method used is Rapid Application Development (RAD), using three stages, namely requirements planning, RAD design workshop, and implementation. The programming language used is PHP with MySQL DBMS and Leaflet JavaScript Library. This research resulted in a Geographical Mapping Information System for Social Welfare Integrated Data in Garut Regency, which features a sub-district DTKS map, data search, super admin and admin login features, and features for managing all data by admin and super admin. The RAD method has succeeded in streamlining time in the construction of this GIS. In addition to this, the results of the BlackBox testing assessment show that the test results have met all the results expected by users on functional requirements, with these results expected to make it easier for the public to find information and check the registered status in DTKS, one of which is through the data search feature based on NIK (Citizenship Identification Number).
Klasifikasi Masyarakat Penerima Bantuan Langsung Tunai Dana Desa Menggunakan Naïve Bayes dan SMOTE Kurniadi, Dede; Nuraeni, Fitri; Firmansyah, Marshal
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 2: April 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.20236453

Abstract

Pemerintah menyelenggarakan program Bantuan Langsung Tunai Dana Desa (BLT DD), program ini memberikan (subsidi) kepada keluarga miskin yang memenuhi syarat. Program ini dapat membantu mengurangi beban pengeluaran serta meningkatkan pendapatan keluarga miskin. Masyarakat yang berhak menerima BLT DD terkadang melebihi kuota yang tersedia, kemudian proses penentuan penerima dilakukan secara musyawarah. Hasil penetapan tersebut terkadang menimbulkan kecemburuan sosial di masyarakat, sehingga diperlukan klasifikasi yang dapat membantu menentukan keluarga yang layak menerima program bantuan ini. Penelitian ini bertujuan untuk menerapkan metode Naïve Bayes untuk mengklasifikasikan data keluarga layak dan tidak layak menerima BLT DD karena masih banyak keluarga miskin berpenghasilan rendah lainnya yang belum berkesempatan untuk memperoleh program bantuan ini. Metode penelitian yang digunakan yaitu Cross-Industry Standard Process For Data Mining (CRISP-DM). Data yang digunakan merupakan data penerima BLT DD tahun 2021 dan 2022 di Desa Kersamenak dengan jumlah data yang digunakan sebanyak 375, meliputi class layak 205 record dan tidak layak 170 record. Data yang terkumpul menunjukkan adanya ketidakseimbangan kelas pada jumlah masyarakat yang layak dan tidak layak, sehingga diperlukan teknik Synthetic Minority Over-sampling Technique (SMOTE) untuk menangani kelas yang tidak seimbang pada data. Hasil pemodelan Naïve Bayes menggunakan teknik SMOTE menghasilkan model performansi terbaik dengan nilai akurasi 97,80% dan nilai AUC 0,99 yang termasuk dalam kategori Excellent Classification. Berdasarkan hasil model kinerja klasifikasi yang diperoleh, model yang dihasilkan dapat diimplementasikan ke dalam sistem aplikasi pendukung keputusan untuk membantu Desa dalam menentukan penerima BLT DD agar lebih cepat dan mudah. Abstract The government organizes the Bantuan Langsung Tunai Dana Desa (BLT DD) program, which provides (subsidies) to low-income families who meet the requirements. This program can help reduce the burden of spending and increase the income of low-income families. Communities who deserve to receive BLT DD sometimes exceed the available quota, then the process of determining the recipient is carried out utilizing deliberation. The results of these determinations sometimes cause social jealousy in the community, so a classification is needed that can help determine eligible families to receive this assistance program. This study aims to apply the Naïve Bayes method to classify family data as eligible and not eligible to receive BLT DD because there are still many other low-income families who have not had the opportunity to acquire this assistance program. The research method used is Cross-Industry Standard Process for Data Mining (CRISP-DM). The data used is the data of the 2021 and 2022 Village Fund Direct Cash Aid recipients in Kersamenak Village, with the amount of data used as much as 375, including 205 eligible class records and 170 inappropriate records. The data collected shows an imbalanced class in the number of eligible and ineligible people, and it is necessary to use the Synthetic Minority Over-sampling Technique (SMOTE) technique to handle the imbalanced class in the data. The results of modeling the Naïve Bayes using SMOTE technique produce the best performance model with an accuracy value of 97.80% and an AUC value of 0.99, which is included in the Excellent Classification category. Based on the results of the classification performance model obtained, we can implement the resulting model into a decision support application system to assist the Village in determining the recipient of the BLT DD to make it faster and easier.
Analisis Penerimaan Learning Management System Institut Teknologi Garut Menggunakan Technology Acceptance Model Mulyani, Asri; Kurniadi, Dede; Putri, Mita Hidayani
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 4: Agustus 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2024106618

Abstract

Kemajuan teknologi dari masa ke masa terus berkembang secara pesat dalam bermacam bidang salah satunya dalam bidang pendidikan. Pendidikan mempunyai kedudukan yang sangat berarti dalam upaya kenaikan mutu seseorang, tetapi dengan kemunculan wabah penyakit Corona Virus Disease 2019 (Covid-19) menyebabkan lahirnya tatanan gaya hidup baru secara global. Civitas akademika Institut Teknologi Garut selain mematuhi peraturan dari pemerintah juga mengikuti perkembangan pendidikan berbasis teknologi informasi yang bersifat interaktif dengan menggunakan aplikasi Learning Management System sebagai pendukung proses pembelajaran jarak jauh dimasa wabah penyakit Covid-19. Dikarenakan Learning Management System (LMS)  di Institut Teknologi Garut baru digunakan, maka penelitian ini bertujuan menganalisis penerimaan Learning Management System Institut Teknologi Garut menggunakan metode Technology Acceptance Model, untuk mengetahui pengukuran pengaruh antar konstruk sekaligus sebagai barometer adaptasi penerimaan pengguna terhadap sistem LMS yang digunakan. Dalam penelitian ini pengolahan data analisis memakai Structural Equation Modeling melalui tools Statistical Product and Service Solution dan Analysis of Moment Structures. Penelitian ini menghasilkan tingkat penerimaan pengguna terhadap Learning Management System dengan nilai probabilitas dibawah 5% yaitu 0,000 dan pengaruh antar konstruk Technology Acceptance Model dengan 3 hipotesis yang diterima ialah variabel Persepsi kemudahan memengaruhi Persepsi kegunaan, Persepsi kegunaan memengaruhi Niat penggunaan, dan Niat penggunaan memengaruhi Penggunaan nyata. AbstractTechnological advances from time to time continue to develop rapidly in various fields, one of which is in the field of education. Education has a very significant role in efforts to improve one's quality, but the emergence of the Corona Virus Disease 2019 outbreak has led to the birth of a new lifestyle order globally. In addition to complying with government regulations, the Garut Institute of Technology academic community also follows the development of interactive information technology-based education with the use of informative applications through electronic media in order to get efficient results, namely the Learning Management System. Because the Learning Management System at the Garut Institute of Technology has just been used, a study entitled Learning Management System Acceptance Analysis of the Garut Institute of Technology uses the Technology Acceptance Model Method, to determine the measurement of the influence between constructs as well as a benchmark for adapting user acceptance to the system used. In this research, data analysis is processed using Structural Equation Modeling through Statistical Product and Service Solution tools and Analysis of Moment Structures. This study resulted in the level of user acceptance of the Learning Management System with a probability value below 5%, namely 0.000 and the influence between the constructs of the Technology Acceptance Model with 3 accepted hypotheses, namely the variable Perception of convenience affects Perception of usefulness, Perception of usefulness affects Intention of use, and Intention of use affects Real use . It is hoped that the results of this research can be used as a reference for developers to continue to optimize the functionality of the Learning Management System so that it can be used optimally.
Sistem Rekomendasi Pemilihan Pengepul Limbah di PT. Pituku Cordova International Menggunakan Algoritma Haversine Kurniadi, Dede; Sutedi, Ade; Nursyaban, Dzikri; Mulyani, Asri
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 11 No 1: Februari 2024
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.20241117694

Abstract

Seiring dengan semakin banyaknya mitra serta volume pesanan pada platformPituku menjadikan pihak perusahaan kesulitan dalam menentukan pengepul limbah yang cocok untuk menangani suatu pesanan. Idealnya, pengepul yang dipilih merupakan pengepul yang terletak paling dekat secara geografis dengan pemesan limbah sehingga biaya pengiriman dapat di minimalkan dan pemesan dapat segera menerima limbah pesananannya. Oleh karena itu dibutuhkan suatu sistem rekomendasi yang dapat merekomendasikan daftar pengepul limbah yang diurutkan dari yang paling dekat ke pembeli limbah. Penelitian ini bertujuan untuk membuat sistem rekomendasi pemilihan pengepul limbah di PT. Pituku Cordova International yang dapat membantu merekomendasikan daftar pengepul limbah yang diurutkan dari yang paling dekat dengan pembeli limbah sehingga proses pemilihan pengepul limbah menjadi lebih efektif. Penelitian ini menggunakan metode Rapid Throwaway Prototyping Modelyang dimana tahapan yang dilakukan meliputi outline requirements, develop protoype, evaluate prototype, specify system, develop software, dan validate system. Algoritma Haversine formuladigunakan dalam sistem rekomendasi dimana koordinat garis lintang dan garis bujur dihitung untuk mendapatkan jarak antara pembeli dan pengepul limbah dalam satuan km kemudian berdasarkan jarak tersebut daftar pengepul limbah diurutkan dari yang paling dekat ke yang paling jauh. Metrik evaluasi menggunakan NDCG (Normalized Discounted Cumulative Gain) yangmengukur akurasi rangkingsistem rekomendasi. Berdasarkan hasil evaluasidiperoleh informasi bahwasistem rekomendasi memiliki score NDCG rata-rata sebesar 1 yang artinya sistem rekomendasi memberikan item rekomendasi dengan rangkingyang diharapkan
Prediction System for Problem Students using k-Nearest Neighbor and Strength and Difficulties Questionnaire Kurniadi, Dede; Mulyani, Asri; Muliana, Inda
JOIN (Jurnal Online Informatika) Vol 6 No 1 (2021)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v6i1.701

Abstract

The student counseling process is the spearhead of character development proclaimed by the government through education regulation number 20 of 2018 concerning strengthening character education. Counseling at the secondary school level carries out to attend to these problems that might resolve with a decision support system. So that makes research challenging to measure completion on target because it is not doing based on data. The counseling teacher does not know about student's mental and emotional health conditions, so it is often wrong to handle them. Therefore, we need a system that can recognize conditions and provide recommendations for managing problems and predicting students who have potential issues. The Algorithm used to predict problem students is K-Nearest Neighbor with a dataset of 100 students. The stages of predictive calculation are data collection, data cleaning, simulation, and accuracy evaluation. Meanwhile, building the system is done using the rapid application development methodology where the instrument used to map the student's condition is the Strenght and Difficulties Questionaire instrument. This research is a system to predict problem students with an accuracy rate of 83%. The level of user experience based on the User Experience Questionnaire (UEQ) results in the conclusion that the system reaches "Above Average.". This system is expecting to help counseling teachers implement an early warning system, help students know learning modalities, and help parents recognize the child's personality better.
IMPLEMENTATION OF RSA AND AES-128 SUPER ENCRYPTION ON QR-CODE BASED DIGITAL SIGNATURE SCHEMES FOR DOCUMENT LEGALIZATION Nuraeni, Fitri; Kurniadi, Dede; Rahayu, Diva Nuratnika
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 3 (2024): JUTIF Volume 5, Number 3, June 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.3.1426

Abstract

Maintaining the confidentiality and integrity of electronic documents is essential in the modern digital age. In the contemporary digital world, digital signatures are essential for safeguarding and legalizing electronic documents. The current issue, however, goes beyond digital signatures and instead centers on enhancing security and data integrity. Therefore, RSA and AES-128 super-encryption is required in QR-code-based digital signature techniques for document legalization. This research stage entails constructing a super encryption algorithm, testing it experimentally for security and performance, and designing a digital signature system using RSA and AES-128 super encryption. The results of this research show that the use of RSA and AES super encryption has been proven to have better performance in data security, where the encryption and decryption process time is relatively close to the RSA encryption time, and the comparison of entropy values is better than RSA and AES-128. So, the combination of Super RSA and AES-128 encryption can increase the security level of electronic documents and reduce the risk of hacking. Moreover, the proposed QR-code-based digital signature scheme is also very efficient regarding file size and processing time.
ENHANCING SENTIMENT ANALYSIS WITH CHATBOTS: A COMPARATIVE STUDY OF TEXT PRE-PROCESSING Indri Tri Julianto; Kurniadi, Dede; B. Balilo Jr , Benedicto
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 6 (2023): JUTIF Volume 4, Number 6, Desember 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.6.1448

Abstract

Text pre-processing plays a crucial role in the Sentiment Analysis process. Machine Learning models like Chat GPT-3.5 by OpenAI and Google Bard serve as alternative methods for text pre-processing. This study aims to evaluate the capabilities of both Chatbots in the text pre-processing stage while assessing their performance using a dataset obtained by crawling from source X. The study involves a comparison of Chat GPT-3.5 and Google Bard using Decision Tree and Naïve Bayes algorithms. The validation process employs K-Fold Cross Validation with a K value of 10. Additionally, three sampling methods, namely Linear, Shuffled, and Stratified Sampling, are utilized. The findings reveal that Chat GPT-3.5 performs best when using the Decision Tree algorithm with a K-Fold Cross value of 10, and employing Stratified Sampling, achieving an Accuracy of 90.68%, Precision of 90.63%, and Recall of 100%. On the other hand, Google Bard's optimal performance is achieved with the Decision Tree algorithm, a K-Fold Cross value of 10, and Shuffled Sampling, resulting in an Accuracy of 74.00%, Precision of 72.73%, and Recall of 98.77%. The study concludes that Chat GPT-3.5 and Google Bard are viable alternatives for text pre-processing in Sentiment Analysis. Performance measurements indicate that Chat GPT-3.5 outperforms Google Bard, achieving an Accuracy of 90.68%, Precision of 90.63%, and Recall of 100%. These results were validated by comparing them to human annotations, which achieved an accuracy score of 85.20%, Precision of 85.71%, and Recall of 99.03% when using the Decision Tree algorithm with a K-Fold Cross value of 10 and employing Stratified Sampling. This suggests that Chat GPT-3.5's text pre-processing performance is on par with human annotations.
IMPLEMENTATION OF PATHFINDING ALGORITHM IN SCOUT EXPLORING GAME WITH DIGITAL GAME-BASED LEARNING-INSTRUCTIONAL DESIGN METHOD Kurniadi, Dede; Tresnawati, Dewi; Sopiah, Dede
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.1931

Abstract

Scouting, or Praja Muda Karana, which means young people who like to work, has become an extracurricular activity that must be held in schools and is regulated by the Law of the Republic of Indonesia. Tri Satya and Dasa Dharma are scouting principles applied through scouting teaching methods, including interactive learning in the open air. One form of implementation is through exploration activities. Along with the rapid development of science and technology, scouting material is now easier to convey through educational games. Educational games are specifically designed to teach specific concepts and understanding, as well as to guide, train skills, and motivate players. Therefore, the aim of making this game is to describe and simulate exploration activities, which is one of the essential aspects of scouting activities. Applying the A* pathfinding algorithm in a 3D game with a scout exploration theme is critical in helping players determine the fastest path to the destination post. This game is expected to improve the player's learning experience with realistic challenges and interactive learning. This game was developed using the Digital Game-Based Learning-Instructional Design (DGBL-ID) method and tested using black box testing. The implementation results show that the scout exploration game application provides positive benefits, as proven by the results of a questionnaire using the Guttman scale with the title "Very Good," indicating that this game is a learning medium that is easy to understand and fun.
Bacteria Recognition Application Model Using Marker-Based Augmented Reality for Android Mobile Devices Mulyani, Asri; Kurniadi, Dede; Fadillah, Hadi Bagus
ULTIMATICS Vol 15 No 2 (2023): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v15i2.3278

Abstract

This article aims to develop a multimedia application model for bacterial recognition using Marker-Based Augmented Reality (Marker-Based AR) technology for Android mobile devices. Marker-based tracking creates mobile augmented reality markers to increase user interaction in Marker-Based Augmented Reality systems. The software development method uses the Multimedia Development Life Cycle, which consists of 6 phases: concept, design, material collecting, assembly, testing, and distribution. The results of this study are a model of a multimedia application for bacterial recognition using Marker-Based AR, which has a marker-based tracking feature and displays bacterial objects in 3 dimensions along with their explanations and exercise questions. Based on user tests, it shows that the application model developed helps and makes it easier to learn about bacteria independently using Android mobile devices more easily and interestingly. This is proven based on beta testing towards users who got a score of 73.68% is obtained which agrees.
Co-Authors A. Abdul Latif Abania, Nia Abdulah, Farhan Naufal Abdurrahman, Fauzan Abdussalam, Iqbal Abdussalam Abdusy Syakur Amin Ade Sutedi Ade Sutedi Ade Sutedi, Ade Adiwangsa, Alfian Akmal Agil Rahmat Agus Hermawan Agus Nugraha Agustiansyah, Yoga Ahmad Habib Lutfi Aisyah Fitri Islami Ajif, Arvin Muhammad Ajiz, Rafi Nurkholiq Alamsyah, Renaldy Aldy Rialdy Atmadja Ali Djamhuri Alisha Fauzia, Fathia Alkamal, Chaerulsyah Alvin Zainal Musthafa Alwan Nul Hakim Amrulloh, Muhammad Fawaz Andri Saepuloh Aneu Suci Nurjanah Asri Indah Pertiwi Asri Mulyani Asri Rahayu Ningsih Ayu Latifah Ayu Suryani B. Balilo Jr , Benedicto B. Balilo Jr, Benedicto Balilo Jr, Benedicto B. Barlinti Maryam Benedicto B. Balilo Jr Budik Burhanuddin, Ridwan Cahya Mutiara Dede Sopiah Della Adelia Anugrah Detila Rostilawati Dewi Tresnawati Dhea Arynie Noor Annisa Diar Nur Rizky Diaz Radhian Salam Diazki, Moch Haiqal Diki Jaelani Dini Destiani Siti Fatimah Diva Nuratnika Rahayu Dudy Mohammad Arifin Dyka Afan Afthori Dzikri Nursyaban Efi Sofiah Elsen, Rickard Endang Prayoga Hidayatulloh Eri Satria Erick Fernando B311087192 Erwan Yani Erwan Yani, Erwan Erwin Gunadhi Rahayu, Raden Erwin Widianto Fadillah, Hadi Bagus Faisal, Ridwan Nur Fajar Rahman Faturrohman, Nadhif Fauziah, Fathia Alisha Fauziyah, Asyifa Fikri Zakaria Rahman Firmansyah, Marshal Fitri Nuraeni Fitriani, Ranti Fitriyani Gelar Panca Ginanjar Ghilman Hasbi Basith Gina Suciyana Gisna Fauzian Dermawan Gugun Geusan Akbar H. Bunyamin Hadi Wijaya, Tryana Haekal, Mohamad Fikri Hamzah Nurrifqi Fakhri Fikrillah Hari Ilham Nur Akbar Hasfi Syahrul Ramadhan Hazar, Aura Fitria Helmalia P, Nabilla Febriani Hendri Aji Pangestu Heri Johari Heri Suhendar Heri Suhendar Hilmi Aulawi Ida Farida Ikbal Lukmanul Hakim Ikhrom, Taufik Darul Ikmal Muhammad Fadhil Ilham Muhamad Ramdan Ilham Syahidatul Rajab Imas Dewi Ariyanti Inda Muliana Indra Trisna Raharja Indri Tri Julianto Indri Tri Julianto Intan Sri Fatmalasari Irawan, Muhammad Randy Irfan Qusaeri Irfanov, Muhammad Irsyad Ahmad Iskandar, Joko Jajang Jaenudin Jajang Romansyah Jembar, Tegar Hanafi Khaerunisa, Nisrina Khoerunisa, Sarah Kusmayadi, Kusmayadi Latifah, Ayu Leni Fitriani Leni Fitriani Leni Fitriani, Leni Lia Amelia Lindayani, Lindayani M. Mesa Fauzi Mahendra Akbar Musadad Maulana , Muhammad Arief Maulana, Ahmad Rakha Maulana, Ilham Ahmad Maulana, Yusep Maulina, Wina Senja Meta Regita Mochamad Deni Ramdani Muhamad Solihin Muhammad Abdul Yusup Hanifah Muhammad Affan Al Sidqi Muhammad Rikza Nashrulloh Muhammad Saleh Muhammad Sanusi Muhammad Sanusi Muhammad Wildan Muliana, Inda Murni Lestari Rahmi Muttaqin, Moch Riefky Chaerul Nabila Putri Nurhaliza Nita Nurliawati Nugraha, M Aldi Nugraha, Nikolas Pranata Nuraisah Nuraisah Nurfadillah, Rifa Sri Nurhaliza, Nabila Putri Nurlisina, Elisa Nurpatmah, Lisna Nursa'diah, Rifania Sapta Nursyaban, Dzikri Nurul Fauziah Nurul Khumaida Nurzaman, Muhammad Zein Omar Komarudin Pratama, Reifalga Gais Prayoga, Moch. Gumelar Putri, Mita Hidayani Raharja, Indra Trisna Rahayu, Diva Nuratnika Rahayu, Raden Erwin Gunadhi Rajab, Ilham Syahidatul Ramdhan, Dekha Ramdhani Hidayat Randy Wardan Ridwan Setiawan Ridwan Setiawan Ridwan Setiawan Ridwan Setiawan Rifky Muhammad Shidiq Rinda Cahyana Rinda Cahyana Risfiyanisa Fasha Rizki Esa Saputra Rizki Fauziah Roeri Fajri Firdaus Rohman, Fauza Rohmanto, Ricky Rostina Sundayana Rubi Setiawan Rudi Sutrio Safei P, M Iqbal Ismail Sarah Khoerunisa Sermana, Elsa Maharani Sheny Puspita Indriyani Siti Rima Fauziyah Sofwan Hamdan Fikri Sopiah, Dede Sri Intan Multajam Sri Mulyani Lestari Sri Rahayu SRI RAHAYU Sri Rahayu Syahrul Sidiq Syaiffani, Moch Assami Tina Maryana Undang Indrajaya W, Faksi Ahmad Wahidah, Tania Agusviani Wiwit Septiani Yanti Sofiyanti Yayat Supriatna Yoga Handoko Agustin Yosep Septiana Yosep Septiana Yuni Yuliani Yusfar Ilhaqul Choer Yusuf Mauluddin Zaqiah, Neng Nufus Zulkarnaen, Ade Iskandar