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All Journal Proceeding of the Electrical Engineering Computer Science and Informatics JURNAL MEDIA INFORMATIKA BUDIDARMA Information Management For Educators And Professionals (IMBI) Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Ilmiah Matrik Sebatik Jurnal Nasional Komputasi dan Teknologi Informasi METIK JURNAL Building of Informatics, Technology and Science Just TI (Jurnal Sains Terapan Teknologi Informasi) Brahmana : Jurnal Penerapan Kecerdasan Buatan Tematik : Jurnal Teknologi Informasi Komunikasi TEPIAN Buletin Poltanesa Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Informatika Wicida Jurnal Riset Inossa : Media Hasil Riset Pemerintahan, Ekonomi dan Sumber Daya Alam eProceedings of Engineering J-Icon : Jurnal Komputer dan Informatika Journal of Informatics, Electrical and Electronics Engineering Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Sasambo: Jurnal Abdimas (Journal of Community Service)
Pitrasacha Adytia
Sistem Informasi, STMIK Widya Cipta Dharma
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Neuroscience Social Sciences Transportation Other

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Integration of Field Data and Citizen Science in Spatial-Based Tropical Biodiversity Information Systems Bustomi , Tommy; Adytia, Pitrasacha
Sebatik Vol. 29 No. 2 (2025): December 2025
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/sebatik.v29i2.2725

Abstract

Biodiversity monitoring in tropical regions is often constrained by limited field survey coverage and fragmented data. This study develops a spatial information system that integrates field data collected through an Android application, citizen science contributions from iNaturalist, and environmental indicators such as the Normalized Difference Vegetation Index (NDVI) and land cover. The integration process employs a spatial database and ETL mechanisms for data normalization, quality validation, and spatial joins with raster data. The implementation results demonstrate that the system is capable of displaying biodiversity distribution in an integrated interactive map. Although citizen science data provide significant contributions, challenges remain in terms of data quality, participation bias, and the protection of sensitive species. With appropriate methodological approaches, this system has the potential to serve as a supporting tool for biodiversity monitoring and data-driven conservation planning.
Rancang Bangun Sistem Layanan Pengaduan Pusat Komputer Berbasis Website Pratama, Jerio Putra; Adytia, Pitrasacha; Harianto, Kusno
Journal of Informatics, Electrical and Electronics Engineering Vol. 5 No. 2 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jieee.v5i2.2823

Abstract

This study aims to design and develop a web-based Puskom Complaint Service System that facilitates integrated and transparent complaint reporting, handling, and monitoring processes. The system development method used is the Software Development Life Cycle (SDLC) Waterfall model, which consists of the stages of requirements analysis, system design, implementation, testing, and maintenance. The system is developed using the PHP programming language with the Laravel framework, MySQL as the database, and Vue.js as the front-end technology to provide a modern user interface. The result of this study is a web-based system that has been successfully implemented with key features, including registration and login for students and staff, an online complaint submission form, online complaint status updates (open, progress, resolved, rejected), and a monitoring dashboard. Functional testing using the Black Box Testing method shows that 10 test scenarios were successfully executed with a 100% success rate, indicating that the system functions as designed. It is expected that this web-based Puskom complaint service system can provide a more structured, efficient, and transparent solution, thereby improving the quality of information technology services at STMIK Widya Cipta Dharma.
Pengembangan Platform LMS Asli Cerdas dalam Upaya Meningkatkan Literasi Digital Anak Usia Sekolah di Kota Samarinda sebagai Mitra Ibu Kota Nusantara (IKN): Innovation of the Asli Cerdas LMS Platform in Enhancing Digital Literacy Among School-Age Children in Samarinda Sa'ad, Muhammad Ibnu; Nursobah; Pajar Pahrudin; Pitrasacha Adytia; Hanifah Ekawati; Salmon
Jurnal Riset Inossa : Media Hasil Riset Pemerintahan, Ekonomi dan Sumber Daya Alam Vol. 7 No. 1 (2025): Juni
Publisher : Badan Perencanaan Pembangunan Daerah, Penelitian dan Pengembangan Kota Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54902/jri.v7i1.171

Abstract

Digital literacy is a fundamental competency in preparing the younger generation to face the challenges of the digital transformation era. Samarinda City, as a strategic partner of the National Capital (IKN), plays an important role in preparing adaptive and tech-literate human resources. This study aims to develop a Learning Management System (LMS) platform called Asli Cerdas to enhance digital literacy among elementary and middle school students. The method used is descriptive-exploratory, involving 675 respondents from 10 districts in Samarinda. Instruments such as digital literacy questionnaires and field observations were used to collect both quantitative and qualitative data. The results showed that students had an average digital literacy index of 3.60, with the lowest score in the aspect of digital safety. Teachers showed better scores but still require technical training to maximize technology use. The Asli Cerdas platform was developed with features including local content, self-assessment tools, and offline access. Pilot testing of the platform showed a 24% improvement in students' understanding of digital literacy. This study recommends the adoption of locally based LMS platforms supported by regional policies to strengthen the digital learning ecosystem in areas that serve as partners to IKN
Classification of Diabetes Diseases Based on Medical Features Using Optimized Support Vector Machine Arfyanti, Ita; Yusnita, Amelia; Adytia, Pitrasacha
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.v7i3.8880

Abstract

Diabetes mellitus is a chronic disease caused by impaired glucose metabolism and has become a global health threat with a steadily increasing prevalence each year. According to WHO and IDF, the number of people living with diabetes is projected to reach 783 million by 2045. This condition demands the development of an accurate and efficient early detection system to support medical decision-making. This study aims to develop an optimized Support Vector Machine (SVM)-based classification model to enhance the accuracy and interpretability of diabetes prediction. The dataset used is the Pima Indians Diabetes Dataset, which consists of eight medical features such as glucose level, blood pressure, and body mass index (BMI). The research stages include data preprocessing, class balancing using the Synthetic Minority Over-sampling Technique (SMOTE), parameter optimization with GridSearchCV, and interpretability analysis through SHapley Additive exPlanations (SHAP). The results show that the optimized SVM model with the Radial Basis Function (RBF) kernel achieved an accuracy of 82%, with a significant improvement in the diabetes class recall value from 0.564 to 0.83 after optimization. The Area Under Curve (AUC) value of 0.871 indicates the model’s effectiveness in distinguishing between positive and negative classes. The SHAP analysis reveals that Glucose, Age, BMI, and Diabetes Pedigree Function are the most influential features in prediction. These findings emphasize that the combination of normalization, balancing, hyperparameter optimization, and interpretability produces a reliable and transparent SVM model. This model has strong potential for implementation in Clinical Decision Support Systems (CDSS) for accurate and explainable early diabetes detection.
Co-Authors Adha Trisna Lidya Alvin Hernanda Ekaputra Amelia Yusnita Andriawan Arriyanti, Eka Asmaramany, Dimas Astin, Siti Namira Rizqi Aulia Abdul Rahman Bustomi , Tommy Didi Kuswandi Ekawati Yulsilviana Ekawati, Hanifah Fariz Mirza Ahmad Hanifah Ekawati Hanifah Ekawati Harianto, Kusno Heny Pratiwi Heny Pratiwi I Nengah Riandika Ika Nurmila Avinda Ita Arfyanti Kasim, Fadly Kelik Sussolaikah Lisda Aulia Rahmi Maulana Umar Muhammad Ahsanu Qaulan Muhammad Fachri Sanjaya Muhammad Fahmi Muhammad Ibnu Saad Saad Muhammad Ibnu Sa’ad Niansyah, Sugih Nurhuda, Asep Nursobah Nursobah, Nursobah Pahrudin, Pajar Pratama, Jerio Putra Rahmat Hidayat Reza Andrea Rizky Zakariyya Rasyad SA'AD, MUHAMMAD IBNU Salmon Salmon Salmon Salmon Salmon, Salmon Solly Aryza Supriady Supriady Sussolaikah, Kelik Tommy Bustomi Ujang Sumarwan Wahyuni - Wahyuni wahyuni wahyuni Yudha Satria Yuli Adam Prasetyo Yunita Yunita Yunita Yunita