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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Teknologi dan Manajemen Informatika CommIT (Communication & Information Technology) ComTech: Computer, Mathematics and Engineering Applications Journal of Information Systems and Informatics Jurnal Informatika Ekonomi Bisnis G-Tech : Jurnal Teknologi Terapan Computer Science and Information Technologies Journal of Applied Data Sciences Indonesian Community Journal Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Informatika Ekonomi Bisnis IJISCS (International Journal of Information System and Computer Science) Jurnal Ilmu Komputer dan Sistem Informasi (JIKSI)
Santo Fernandi Wijaya
Faculty Of Engineering And Informatics, Information System, Universitas Multimedia Nusantara
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Mathematics Public Health Social Sciences Other

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Studi Awal Pemanfaatan Teknologi Digital oleh UMKM UP2K Kenanga di Desa Curug Sangereng: Analisis Kesiapterapan Digitalisasi Pemasaran Jansen Wiratama; Santo Fernandi Wijaya; Hendro Budiyanto; Robben Setiadi; Axel Lionel Raphael
I-Com: Indonesian Community Journal Vol 5 No 3 (2025): I-Com: Indonesian Community Journal (September 2025)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/i-com.v5i3.8005

Abstract

Rendahnya literasi digital dan terbatasnya pemanfaatan media daring membatasi akses pasar UMKM perdesaan. Program pengabdian ini bertujuan mengidentifikasi kesiapan dan kebutuhan UMKM UP2K Kenanga di Desa Curug Sangereng dalam mengadopsi teknologi pemasaran digital. Desain program menggunakan pendekatan partisipatif berbasis komunitas (community-based participatory approach). Metode meliputi observasi lapangan, FGD dengan pemangku kepentingan, pelatihan digital marketing, serta perancangan dan pengujian prototipe e-marketplace berbasis web responsif. Sebanyak 11 UMKM terlibat pada proses pemetaan, uji coba, dan pelatihan. Hasil menunjukkan sebagian besar UMKM belum memiliki legalitas usaha dan belum memanfaatkan platform digital secara optimal, namun menunjukkan kemauan belajar yang tinggi. Prototipe e-marketplace diterima dan disempurnakan berdasarkan umpan balik pengguna. Temuan ini menegaskan bahwa pelatihan dan pendampingan berbasis teknologi merupakan strategi yang layak dan relevan untuk memperkuat transformasi pemasaran serta daya saing UMKM secara berkelanjutan.
Intelligent LSTM-based deforestation prediction model and dashboard for Kalimantan using global forest change and night-time light data Jansen Wiratama; Samuel Ady Sanjaya; Thomas Januardy; Reyhan Arya Hermawan; Santo Fernandi Wijaya
Jurnal Ilmu Komputer dan Sistem Informasi |JIKSI| Vol. 7 No. 2 (2026): Jurnal Ilmu Komputer dan Sistem Informasi (JIKSI) [in Progress]
Publisher : Institute of Information Technology and Social Science (IITSS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61346/jiksi.v7i2.333

Abstract

Forest assessment based on predictions and evidence is an appropriate step toward environmental conservation. This study developed a Long Short-Term Memory (LSTM) based prediction model to monitor and predict forest cover and light intensity in Kalimantan. Using Global Forest Change (GFC) and Night-Time Light data, the prediction results are applied to a web-based dashboard. The data were available for the period from 2001 to 2023 and has been processed and aggregated to the provincial level. The LSTM model was trained using five optimizers, namely Adam, RMSprop, Stochastic Gradient Descent (SGD), Adadelta, and Adamax. Model performance was evaluated using Root Mean Squared Error (RMSE). The results showed that the Adam and RMSprop optimizers produced lower RMSE values compared to the other optimizers on the GFC dataset, making them more effective at learning patterns and forest cover change. On the NTL dataset, Adam, RMSprop, and Adamax demonstrated relatively similar performance due to the data’s more stable characteristics. Overall, Adam provided the most accurate and consistent predictions. The prediction results are presented via a web-based dashboard that allows for the visualization of historical trends as well as predictions of change in forest cover and nighttime light intensity. These findings suggest that the combination of the LSTM model and an interactive dashboard can support more effective deforestation monitoring.
Fuzzy Expert System for Melamine Moulding Compound Dye Feasibility Identification: A Case study on Plastic Industry Jansen Wiratama; Santo Fernandi Wijaya; Samuel Ady Sanjaya; Florentina Kurniasari; Hendro Budiyanto; Ala Al Kafri; Nuttaphat Sukchitt
Journal of Applied Data Sciences Vol 7, No 3: September 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i3.1498

Abstract

This study addresses a practical decision problem within the melamine industry. Production managers are tasked with determining whether a new Melamine Moulding Compound (MMC) dye is suitable for use, based on testing parameters such as boiling point, processing time, and pressure. Given that these values frequently fall between established expert categories, manual decision-making can be challenging to justify and replicate. Accordingly, this research develops a web-based Fuzzy Sugeno expert system to assess the feasibility of MMC dye. The model incorporates three input variables, each characterized by low, medium, and high fuzzy sets. Expert knowledge is formalized into 27 rules employing zero-order Sugeno consequents for three classes: not feasible, conditionally feasible, and feasible. The system has been implemented as a PHP and MySQL application and is accessible via a publicly available login page. An illustrative example involving MMC103—boiling point of 165 °C, processing time of 65 seconds, and pressure of 55 bar—indicated medium and high membership values across all three parameters, activating eight rules. The aggregate firing strength was calculated as 3.00, the weighted consequent sum amounted to 80.00, and the final Sugeno score was 26.67. This score categorizes MMC103 as feasible. The results demonstrate that the model not only provides a classification label but also displays memberships, active rules, rule consequents, and the final computation, thereby enabling verification by the production manager. Furthermore, the study includes an English version of the application interface with privacy masking features for user data.
Co-Authors Abda Abda Ala Al Kafri Angelina Ervina Jeanette Egeten Angga Aditya Permana Antonius Sony Eko Nugroho Axel Lionel Raphael Budiyanto, Hendro Damayanti, Felicia Maria Cynthia Fanny Johan Felicia Maria Cynthia Damayanti Fikri Arlan Fikri Arlan, Fikri Handoyono, Yustina Hari Santoso Hendra Alianto Hendra Alianto I Gusti Ngurah Antaryama Jansen Wiratama Jansen Wiratama Jansen Wiratama Jonathan Jonathan Kurniasari, Florentina Noveriyanti, Dea Nugroho, Antonius Sony Eko Nuttaphat Sukchitt Raymond Sunardi Oetama Raymond Sunardi Oetama Reyhan Arya Hermawan Robben Setiadi Rudi Sutomo Samuel Ady Sanjaya Samuel Ady Sanjaya Tandika, Idris Thomas Januardy Verri Kuswanto Willsen Wijaya Wiratama, Jansen Yang, Angelina Yustina Handoyono