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All Journal Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Finger : Jurnal Ilmiah Teknologi Pendidikan Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Muhamad Azrino Gustalika
Universitas Telkom
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Public Health Social Sciences Other

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The Role Of Website In Improving Digital Marketing In E-Commerce MSME Macaroni Cheese: Peran Website Dalam Meningkatkan Digital Marketing Pada E-Commerce UMKM Makaroni Keju Muhamad Azrino Gustalika; Dimas Fanny Hebrasianto; Annisaa Utami; Adithana Dharma Putra; Ervan Hapiz; Haposan Felix Marcel Siregar
JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Vol. 9 No. 4 (2025): Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Publisher : DPD Jatim Perkumpulan Dosen Indonesia Semesta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Icip-Icip Cheese Makaroni UMKM located in Wirasana Village, Purbalingga Regency. This UMKM focuses on making snacks, especially cheese makaroni with various flavors. Currently, Icip-Icip Cheese Makaroni products are only sold in Purbalingga Regency. One of the problems faced by Icip-Icip Cheese Makaroni UMKM is that marketing is not optimal, so many people do not know this product. Competition in the cheese makaroni industry is very fierce with other brands, so Icip-Icip Cheese Makaroni UMKM must develop a marketing strategy through digital marketing in order to compete and increase sales. This service resulted in 91.67% of UMKM satisfaction and the e-commerce application was successfully 100% run.
Dota 2 Hero Buff And Nerf Predictions Based On Professional Match Data Using Random Forest Muhammad Raditya Azanata; Muhamad Azrino Gustalika; Dimas Fanny Hebrasianto Permadi
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 11, No. 3, August 2026 (Article in Progress)
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v11i3.2698

Abstract

Balancing updates (buffs and nerfs) are critical in Multiplayer Online Battle Arena games because small parameter changes can shift the competitive metagame and reduce hero diversity. This study proposed a data-driven pipeline to classify each Dota 2 hero as overpowered, underpowered, or balanced from professional match telemetry and to translate these classes into balance recommendations (nerf, buff, or balance). Most prior Dota 2 studies focus on match outcome or micro-event prediction and do not evaluate hero-centric balance recommendations against official patch actions across patch transitions. To address this gap, this work contributes a patch-to-patch external validation protocol that compares recommendations from patch t with developer actions in patch t+1 using patch notes. Professional match records were collected from public sources and aggregated per hero and per patch into combat, economy, and impact features (e.g., kills, deaths, assists, gold per minute, experience per minute, damage dealt, tower damage, and healing). Labels were derived from win-rate and pick-rate distributions using statistical control limits (μ ± kσ, k = 0.3) to ensure transparent and repeatable labeling. A Random Forest classifier was trained using grid-searched hyperparameters and evaluated using stratified 6-fold cross-validation with macro-averaged F1 to address class imbalance. Internal evaluation achieved 0.94 accuracy and 0.84 macro-F1. For external validation, recommendations from patch t were compared with official balance actions in patch t+1 across six consecutive transitions; accuracy ranged from 0.436 to 0.672 (mean 0.559), with the best result on 7.39b to 7.39c (84/125). These results indicated that professional telemetry could support interpretable balance monitoring and provide early signals for buff/nerf candidate review
Improving Cattle Farmers Knowledge of Animal Weight Monitoring Using IoT: Peningkatan Pengetahuan Peternak Sapi dalam Monitoring Berat Badan Hewan Ternak Berbasis IOT Wahyu Andi Saputra; Muhamad Azrino Gustalika; Faizah Faizah; Silvia Van Marsally; Dedy Agung Prabowo; Fahrudin Mukti Wibowo
JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Vol. 10 No. 3 (2026): Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Publisher : DPD Jatim Perkumpulan Dosen Indonesia Semesta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36339/je.v10i3.536

Abstract

The Mukti Mandiri Livestock Group is located in Karanggitung Village, Banyumas Regency. This group focuses on beef cattle farming. Currently, the group faces various obstacles, including the lack of ability to accurately calculate cattle weight. This causes the group to often rent scales or entrust their cattle to other cattle groups to determine their weight. Furthermore, the Mukti Mandiri Group often chooses to estimate the weight of cattle due to the high rental price of scales. This impacts the selling price of cattle to collectors, resulting in farmers only earning a small profit. Therefore, a weighing device is needed to assist the Mukti Mandiri Livestock Group. This community service activity was carried out in order to provide IoT (Internet of Things)-based weighing devices to facilitate the cattle weighing process. The activity consisted of 5 stages: socialization, technology implementation, training, mentoring and evaluation, and the sustainability of the community service program. The results of this community service showed that 51% of respondents answered strongly agree, 46% agreed, and 3% quite agreed, in terms of increasing the knowledge of livestock farmers regarding the community service activity and the use of IoT-based weighing devices. It is hoped that this community service activity can continue in the management aspect for RPH (Animal Slaughterhouse) and Juleha (Halal Slaughterhouse) so that it can encourage participation from other livestock breeders in the use of technology in the livestock sector.
Design and Development of a Machine Learning-Based Mobile Application for Stress Detection Using Facial Expression Analysis Musyafa Al Adn; Muhamad Azrino Gustalika; Nicolaus Euclides Wahyu Nugroho
FINGER : Jurnal Ilmiah Teknologi Pendidikan Vol. 5 No. 2 (2026): Finger : Jurnal Ilmiah Teknologi Pendidikan
Publisher : CV. Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/finger.v5i2.685

Abstract

Background: Stress is a common mental health issue that requires early detection to prevent severe consequences.Aims: This study aims to develop an Android-based mobile application capable of detecting stress levels using facial expression analysis.Methods: The application was developed using the Rapid Application Development (RAD) approach. A Convolutional Neural Network (CNN) based on EfficientNetB0 was used and trained on the FER2013 dataset. The trained model was then converted into TensorFlow Lite format for efficient deployment on mobile devices.Results: The model achieved an accuracy of 80.23%, precision of 80.60%, recall of 73.84%, and F1-score of 77.07%. Furthermore, real-world performance testing on mobile devices demonstrated high efficiency. The optimized TensorFlow Lite model achieved a rapid inference time of 6.00 ms and a compact footprint of 2.85 MB. The developed application successfully performs real-time and offline stress detection using images captured from the camera or selected from the gallery. Functional testing using the black-box method showed that all application features operated correctly, while usability evaluation using the System Usability Scale (SUS) produced an average score of 79, indicating that the application is easy to use. Conclusion: This study demonstrates that integrating machine learning into mobile applications can provide a practical and accessible solution for early stress detection. However, dataset imbalance remains a limitation that affects model performance and should be addressed in future work.
Co-Authors Adithana Dharma Putra Annisaa Utami Dedy Agung Prabowo Dimas Fanny Hebrasianto Dimas Fanny Hebrasianto Permadi Ervan Hapiz Fahrudin Mukti Wibowo Faizah Faizah Haposan Felix Marcel Siregar Muhammad Raditya Azanata Musyafa Al Adn Nicolaus Euclides Wahyu Nugroho Silvia Van Marsally Wahyu Andi Saputra