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All Journal Sistemasi: Jurnal Sistem Informasi Building of Informatics, Technology and Science Mitra Mahajana: Jurnal Pengabdian Masyarakat Journal Of Artificial Intelligence And Software Engineering Prosiding Seminar Nasional CORISINDO
Sujaka, Tomi Tri
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Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Public Health Social Sciences

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Development of an Android-Based Educational Game to Introduce Sumbawa's Art and Culture to Elementary School Students Attaqwa, M.Aswin Syarif; Hammad, Rifqi; Sujaka, Tomi Tri
Journal of Artificial Intelligence and Software Engineering Vol 5, No 2 (2025): June
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i2.6937

Abstract

Technology is increasingly being used to facilitate work in various fields, including education. One of the uses of technology in education is as a learning medium. However, the use of learning media, especially technology-based media, is still very limited. This affects the learning process, where children often become easily bored due to a lack of interest in studying. Therefore, based on this issue, the researcher developed an Android-based educational game to help children learn about the art and culture of Sumbawa, specifically Satera Jontal (Sumbawa script) and traditional ceremonies of the Sumbawa region. This study uses the Multimedia Development Life Cycle (MDLC) method, which consists of six stages: concept, design, material collecting, assembly, testing, and distribution. Based on the results of media expert validation, a score of 92% was obtained; material expert validation scored 95%; and user testing produced a result of 82%. These results indicate that the developed Android-based educational game is suitable for use. Based on pretest results from users, the average score was 56.36, while the posttest results showed an average score of 74.24. These results demonstrate that the developed educational game can improve student learning outcomes
Smart Farming System on Red Onion Plants Based on the Internet of Things Hadi, Sirojul; Cahyati, Anzali Ika; Latif, Kurniadin Abd; Sujaka, Tomi Tri; Zulfikri, Muhammad
Sistemasi: Jurnal Sistem Informasi Vol 12, No 3 (2023): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v12i3.2860

Abstract

Red Onions are agricultural commodities that are a source of income for farmers and can make a major contribution to Indonesia's economic development. The characteristic of the onion plant is that it requires a lot of sunlight. The sunlight needed for photosynthesis is 70% with an ambient temperature range of 25oC-32oC and soil moisture in the range of 50%-70%. Although red onions require a lot of water, these plants are sensitive to high-intensity rainfall. The critical period of the red onion plants is in the tuber formation phase so it is necessary to control it to get maximum production results. The method of making the smart farming system uses the Research and Development (R&D) method while sending data online to the web uses the Internet of Things (IoT) method. The result of this research is that a monitoring and control system for temperature and humidity has been successfully built on red onion plants. The system built is capable of measuring temperature with an accuracy rate of 95.33% and environmental humidity in plants reaching 92.07% while the accuracy of testing the entire system reaches 93.33%. The smart farming system has been able to automatically irrigate and apply fertilizer. Control of irrigation and application of fertilizers by the system has implications for better shallot growth and creates modern agriculture.
Introducing Children of Environmental Issue in Sekotong Timur Through Project Based Learning Dewi, Puspita; Yuliatin, Riyana Rizki; Hadi, Sirojul; Syarifaturrahman, Wahyu Kamil; Latif, Kurniadin Abd; Sujaka, Tomi Tri; Ramandha, Muhammad Eka Putra; Fatimatuzzahra, Fatimatuzzahra
Mitra Mahajana: Jurnal Pengabdian Masyarakat Vol. 3 No. 2 (2022): Volume 3 Nomor 2 Tahun 2022
Publisher : LPPM Universitas Flores

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37478/mahajana.v3i2.1834

Abstract

Nowadays, the environmental issue is one of the biggest problems worldwide. It is because the climate change deteriorates from time to time; the earth becomes warmer, and pollution polluted the environment. Humans have a pivotal role in changing the earth because they damage the ecosystem by using numerous plastics, throw many of rubbish, and cutting plenty of trees. As a result, climate change and global warming become worse. Consequently, all stakeholders need to take the responsibility to protect the earth. Some groups blame the government; however; environmental issues are the government’s responsibility and all society’s matters, including academicians. This community service activity was conducted in one of the remote areas in Bunbeleng village, East Sekotong district, East Lombok. The Project was held by Relawan Saling Jaga Indonesia (Relasi) funded by Direct Aid Program (DAP) Australian Consulate-General, Bali Indonesia coordinated by Isyatul Mardiah. This project was conducted based on Project-based Learning (PBL). There are five stages in implementing this project: planning the project, monitoring the project, presenting the project, and evaluating the project. The environment topics were elaborated in this community through the PBL. After the program, the students have more knowledge in reducing, recycling, and reusing plastics and green programs with planting trees. The students were very enthusiastic and motivated. The collection of the project was exhibited isn the classroom.
Penetration Testing untuk Menguji Sistem Keamanan Website Menggunakan OWASP ZAP Maulana, Hifzul Wathoni; Sujaka, Tomi Tri; Azwar, Muhamad; Husain, Husain; Hariyadi, I Putu
CORISINDO 2025 Vol. 1 (2025): Prosiding Seminar Nasional CORISINDO 2025
Publisher : CORISINDO 2025

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/corisindo.v1.5227

Abstract

Di era digital yang semakin berkembang  maka keamanan website merupakan aspek krusial dalam melindungi data dan menjaga integritas sistem. Penelitian ini bertujuan untuk menguji keamanan website terhadap serangan parameter injection menggunakan metode penetration testing. Pengujian dilakukan dengan mengacu pada standar OWASP Top 10 denan menggunakan alat OWASP Zed Attack Proxy. Proses pengujian dilakukan dalam empat tahap, yaitu perencanaan, pemindaian, eksploitasi, dan pelaporan. Eksploitasi dilakukan terhadap dua jenis serangan utama, yaitu SQL Injection dan Cross Site Scripting, menggunakan alat SQLMap dan Burp Suite. Hasil pengujian menunjukkan bahwa terdapat dua jenis kerentanan pada sistem, masing-masing memiliki tingkat risiko tingg dan medium. Langkah mitigasi dilakukan dengan mengimplementasikan teknik prepared statement, validasi dan sanitasi input, serta enkripsi data menggunakan algoritma Advanced Encryption Standard serta melakukan konfigurasi tambahan untuk mencegah akses yang tidak sah. Penelitian ini menghasilkan rekomendasi teknis yang dapat digunakan oleh pengembang untuk meningkatkan keamanan website dari ancaman cracker.
Penerapan Sistem Cerdas dan Sistem Informasi Geografis pada Aplikasi Layanan Jaminan Bongkar Reklame Aprisandi, Lalu Wirman; Azwar, Muhamad; Sujaka, Tomi Tri
CORISINDO 2025 Vol. 1 (2025): Prosiding Seminar Nasional CORISINDO 2025
Publisher : CORISINDO 2025

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/corisindo.v1.5262

Abstract

This study aims to design and develop a web-based billboard permit application system that integrates intelligent system technology and Geographic Information Systems (GIS). The system utilizes the Forward Chaining and Certainty Factor algorithms to provide recommendations on the suitability of billboard placement zones based on expert-defined rules, while Google Maps is used for interactive visualization of billboard locations. Alpha testing results indicate that all system features—ranging from application submission and processing to reporting—function as intended according to the initial design. Meanwhile, beta testing shows a user satisfaction rate of 86.33%, indicating that the system is considered user-friendly, functional, and suitable for implementation within regulatory agencies. In addition to supporting the digitization of public services, the system also enhances the efficiency of monitoring and decision-making regarding non-compliant or expired billboards. This study contributes to the application of information technology to accelerate, simplify, and improve the effectiveness of public services related to billboard permitting.
Klasterisasi Pemain PUBG Mobile dengan Algoritma K-Modes Clustering pada Mayoung Universe Harisandi, Lalu Ilham; Sujaka, Tomi Tri; Hammad, Rifqi
CORISINDO 2025 Vol. 1 (2025): Prosiding Seminar Nasional CORISINDO 2025
Publisher : CORISINDO 2025

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/corisindo.v1.5520

Abstract

Mayoung Universe merupakan penyelenggara turnamen Esport dan Leader komunitas yang aktif mengadakan turnamen PUBG Mobile di wilayah Nusa Tenggara Barat. Dari sekian banyak turnamen yang telah di selenggarakan akan tetapi Mayoung Universe mengalami kesulitan dalam menentukan pola penyelenggaraan turnamen PUBG Mobile untuk kedepannya, Selain itu, Terdapat data pendaftaran pemain berjumlah 401 data, serta didominasi oleh atribut yang bertipe kategorik Oleh sebab itu, menerapkan algoritma K-Modes Clustering sangatlah cocok di terapkan untuk mengatasi permasalahan serta untuk menangani data kategorik. Algoritma K-Modes merupakan pengembangan dari K-Means yang dirancang untuk mengelompokkan data kategorikal Hasil evaluasi dari Elbow Method terdapat jumlah k optimal yakni 4,6 dan 8, Hasil evaluasi dari Silhouette Coefficient jumlah k terbaik sebanyak k=6, dengan skor=0,249. Sedangkan evaluasi dari Dunn index dan DBI, k terbaik terdapat pada k=3, skor dari Dunn index yaitu 0,643, dan skor DBI yakni skor 2,395. Hasil dari visualisasi jumlah k=6 dan 3, terdapat jumlah objek terbanyak pada cluster 1 sebanyak 197 untuk k=6, dan 231 untuk k=3. Untuk mengatasi permasalahan bagaimana menentukan pola turnamen PUBG Mobile di Nusa Tenggara Barat, pihak Mayoung Universe hendaknya memperhatikan cluster 1 dari 3 dan 6 jumlah k terbaik dengan segala bentuk karakteristiknya. Sebagai gambaran, dalam menyelenggarakan turnamen PUBG Mobile kedepannya. 
Pengaplikasian Convolutional Neural Network (MobileNetV3) Memanfaatkan Transfer Learning Untuk Membedakan Tanaman Cabai Berasal Dari Genus Capsicum Annuum Sujaka, Tomi Tri; Switrayana, I Nyoman; Haepa Fillah, Ibnu Mumtaz
Building of Informatics, Technology and Science (BITS) Vol 7 No 3 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i3.8740

Abstract

Accurate classification of Capsicum annuum varieties is crucial for food industry applications and agricultural research. Traditional manual classification methods are time-consuming, subjective, lack detail, and are prone to human error, requiring computer vision to automate them. This study presents learning in the form of automatic classification of nine diverse Capsicum annuum varieties using transfer learning with the MobileNetV3 architecture, which is designed to achieve high accuracy and be computationally energy efficient. The dataset consists of 4,500 images (training, testing, and validation) of 9 chili varieties: bell pepper, curly chili, cherry pepper, chiltepin, Hungarian wax, jalapeno, marconi, pequin, and Thai chili. This dataset goes through quality control, one of which is dataset balancing. The model in this study has also been optimized with Adam (Adaptive Moment Estimation). Model interpretation is also improved through Grad-CAM visualization, and model robustness has also been validated using cross-validation 5 times. This model achieved performance with a training accuracy of 97.2%, a testing accuracy of 95.1%, and a validation test of 94.8%, where 5-fold cross-validation showed consistent results (94.23% ± 1.45%). Grad-CAM analysis showed that this model focuses on structural features such as shape, surface texture, and color patterns. With the successful development of an AI system that can automatically identify chili varieties with an accuracy of 95.1%. This system works well in real conditions (90.6% accuracy) and is practical for use in agriculture and food processing. This technology can help farmers and food companies or lay people to sort chilies automatically, reduce costs, and improve quality control.
A Multimodal Deep Learning Framework for Amyotrophic Lateral Sclerosis Diagnosis using Clinical and Audio Morphology Features Switrayana, I Nyoman; Sujaka, Tomi Tri; Silpiana Putri, Imelda
Sistemasi: Jurnal Sistem Informasi Vol 15, No 1 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i1.5763

Abstract

Amyotrophic Lateral Sclerosis (ALS) is a highly progressive neurodegenerative disease that impairs motor and speech function. Conventional diagnostic methods, both invasive and non-invasive, are often time-consuming and produce limited sensitivity. This leads to delays in treatment and worsening disease progression. This study proposes a multimodal deep learning framework that utilizes and integrates invasive medical records with non-invasive morphological features of patient speech audio extracted into Mel-Spectrograms. Unlike previous studies that focused solely on speech or clinical features, this study introduces an integrated multimodal diagnostic framework that effectively combines both data sources to achieve reliable diagnostic accuracy. The study included two experimental scenarios. In the first scenario, the audio-trained model used a Convolutional Neural Network (CNN) and was systematically optimized by testing variations in network depth, feature fusion techniques, and layer dropout probabilities to improve model generalization and stability. From the experimental results of the first scenario, the CNN achieved the best performance, achieving 80.33% accuracy in classification using audio data alone from all the tested model variations. In the second experimental scenario, when the best model was trained by incorporating clinical data, the model demonstrated improved diagnostic performance, achieving 100% accuracy. This finding highlights the importance of combining data modalities or sources from various domains, both invasive and non-invasive, to achieve optimal model performance for early ALS detection.
Co-Authors Aprisandi, Lalu Wirman Attaqwa, M.Aswin Syarif Cahyati, Anzali Ika Fatimatuzzahra Fatimatuzzahra Haepa Fillah, Ibnu Mumtaz Hammad, Rifqi Harisandi, Lalu Ilham Hariyadi, I Putu Husain Husain I Nyoman Switrayana Kurniadin Abd Latif Maulana, Hifzul Wathoni Muhamad Azwar, Muhamad Muhammad Eka Putra Ramandha Puspita Dewi, Puspita Riyana Rizki Yuliatin Silpiana Putri, Imelda Sirojul Hadi Wahyu Kamil Syarifaturrahman, Wahyu Kamil Zulfikri, Muhammad