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All Journal Jurnal Statistika Universitas Muhammadiyah Semarang Jurnal Transformatika JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Pengembangan Rekayasa dan Teknologi Jurnal Ilmiah Pendidikan dan Pembelajaran Community Development Journal: Jurnal Pengabdian Masyarakat Information Science and Library LOSARI: Jurnal Pengabdian Kepada Masyarakat Journal Of Human And Education (JAHE) Journal of Data Insights Journal of Computing Theories and Applications Journal of Islamic Science Community Journal of Learning on History and Social Sciences Journal of Computing and Smart Ecosystems
Amri, Saeful
Universitas Muhammadiyah Semarang
Agriculture, Biological Sciences & Forestry Humanities 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 Energy Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Public Health Social Sciences Transportation Other

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Implementasi Sistem Rekomendasi Mitigasi Layanan Sertifikasi Produk Halal Berbasis Blockchain pada LP UMKM Muhammadiyah Kota Semarang Amri, Saeful; M. Al Haris; Purnomo Putro, Dwi; Mandala Adikara Sencoko
LOSARI: Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 2 (2025): Desember 2025
Publisher : LOSARI DIGITAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53860/losari.v7i2.521

Abstract

The Muhammadiyah Regional Leadership (PDM) of Semarang City has an MSME Development Institute (LP). This institution has a specific mission in developing MSMEs in growing, mobilizing, improving and empowering the potential of MSMEs in the national and global business arena. This community service activity is to implement a distributed system to develop the creative industry and encourage entrepreneurship in the field of digital technology and innovation and can increase responsible consumption and production in terms of halal consumer products for Muhammadiyah MSMEs in Semarang City. This activity includes socialization, training on system operation, implementation, mentoring and monitoring. The results show that the implementation of the system can document the data of MSMEs well by 75%, halal product certification for MSMEs increased by 80%, and skills in operating the system are increasing, based on the satisfaction level reaching 91% after the activity. This program proves that utilizing technology can provide convenience in verifying data for the halal certification process and increase security and reduce the risk of data loss.
ANALYSIS OF THE THINKING PROCESS OF GRADE XI STUDENTS IN SOLVING MATHEMATICS PROBLEMS REVIEWED FROM THE EXTROVERT AND INTROVERTED PERSONALITIES OF STUDENTS OF SMK PGRI 24 JAKARTA Amri, Saeful
Journal of Learning on History and Social Sciences Vol. 2 No. 7 (2025): Journal of Learning on History and Social Sciences
Publisher : PT. Antis International Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61796/ejlhss.v2i7.1359

Abstract

Objective: I conducted research with the aim of training and determining the skills of students at SMK PGRI 24 Jakarta. Students' ability to think and solve math problems is examined from the perspective of introverted and extroverted students. Method: To make my research easier, I used a qualitative approach. Six Class XI students from SMK PGRI 24 in Jakarta were the subjects of the study; The three participants each represented extroverted and introverted personality types. Questionnaire, interview, and documentation approaches were used to collect data for this study. To collect this data, aspects of the student's personality were considered, along with testing the data and the conclusions drawn from the participants. A triangulation approach was used to collect data for the study. Results: The study found that introverted and extroverted students were at a full level of understanding of the difficulties used in their thought processes as well as carrying out planning, evaluation, and monitoring procedures. Planning steps are followed, which are completed by having students double-check the planning procedures. According to the results of the research interviews, extroverted students were at the level of tacit use, and introverted students were at the level of strategic use. Novelty: Students' ability to think and solve math problems is examined from the perspective of introverted and extroverted students.
AI-Enhanced Coastal Ecosystem Monitoring for Abrasion and Mangrove Decline Detection Using NDVI and CNN Models Muhammad Ivan Ardiansyah; Saeful Amri; Basirudin Ansor; Wendy Sarasjati; Anggry Windasari; Gansar Timur Pamungkas
Journal of Computing and Smart Ecosystems Vol. 1 No. 2 (2025): J-CaSE
Publisher : S1 Teknologi Informasi, Universitas Muhammadiyah Semarang

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Abstract

Coastal ecosystems in Indonesia are increasingly threatened by accelerating abrasion and severe mangrove degradation, especially in Mangunharjo, Semarang, where shoreline retreat continues to endanger local communities and ecological stability. This study aims to develop an AI-driven monitoring framework for detecting coastal abrasion and mangrove loss using Normalized Difference Vegetation Index (NDVI) combined with a Convolutional Neural Network (CNN) classifier. Multispectral data from Sentinel-2 imagery were processed to extract NDVI time-series from 2015 to 2025, followed by image preprocessing, normalization, and CNN-based classification. The model identifies abrasion-affected zones and declining mangrove cover, while the geospatial dashboard visualizes risk levels and restoration priority areas. Experimental results show that the CNN–NDVI model achieves high accuracy in distinguishing stable and abrasion-prone regions, with clear detection of vegetation loss patterns along the western coastline of Mangunharjo. The developed dashboard successfully integrates prediction output, interactive mapping, and AI-assisted recommendations for mangrove restoration. In conclusion, this system demonstrates the potential of combining satellite data, CNN-based analysis, and geospatial visualization to support data-driven decision-making for coastal ecosystem management and sustainable environmental planning.
Forecasting Rice Prices in Indonesia Using a Hybrid HWES-MLP Time Series Prediction Model Supriadin, Supriadin; Haris, M. Al; Amri, Saeful; Abas, Hafiza; Fadugba, Sunday Emmanuel
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 2 (2026): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i2.35445

Abstract

Rice is the main staple food for the majority of the Indonesian population. However, the fluctuation in rice prices and future uncertainty emphasize the importance of forecasting rice prices, thus requiring a forecasting model capable of providing accurate predictions. Various previous forecasting methods have been limited in capturing the combination of linear and non-linear patterns in rice price data, spurring the need for a more comprehensive hybrid approach. This research applies a quantitative approach by utilizing secondary data sourced from publications of the Central Statistics Agency (BPS) of Indonesia. This study aims to forecast rice prices in Indonesia using a hybrid approach combining Holt–Winters Exponential Smoothing (HWES) with Multilayer Perceptron (MLP). The hybrid model is designed to overcome the limitations of the Holt-Winters Exponential Smoothing method, which can only capture linear patterns such as trend and seasonality, by adding the Multilayer Perceptron method to capture non-linear patterns that cannot be handled by the linear approach. The dataset comprises monthly rice prices in Indonesia from January 2010 to December 2024, while the period of January–December 2025 is used as the prediction period. The data analysis process was carried out using the software R-Studio and Minitab, which provide a variety of features to support time series modeling. The results indicate that the most effective method for forecasting rice prices in Indonesia is the Hybrid Holt Winters Exponential Smoothing (α = 0.5; β = 0.3; γ = 0.3)-Multilayer Perceptron (12-12-1), which achieved the highest accuracy with a MSE of 9666.12, a RMSE of 310.9117, and a MAPE of 1.9949%. This finding indicates that the Hybrid HWES-MLP approach is highly capable of capturing rice price data patterns. Thus, this model holds significant potential to be utilized as a benchmark supporting government policy in maintaining rice price stability, market intervention, and optimizing the management of national rice reserves stock.
An Explainable Multimodal Framework for Chest X-Ray Alert Classification Using Radiology Reports and Images Edy Winarno; Indah Manfaati Nur; Abdul Karim; Saeful Amri; Ismi Elya Wirdati; Prajanto Wahyu Adi
Journal of Computing Theories and Applications Vol. 3 No. 4 (2026): JCTA 3(4) 2026
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.16023

Abstract

Artificial intelligence has the potential to support radiology workflows by assisting in the identification of cases that may require additional clinical attention. However, alert-oriented medical AI systems should provide not only classification outputs but also interpretable evidence that can be reviewed and audited by clinicians. This study develops and evaluates an explainable multimodal framework for binary chest X-ray alert classification using paired radiology reports and chest X-ray images. The text branch employs TF-IDF n-gram features with a class-balanced Logistic Regression classifier, while the image branch fine-tunes a pretrained ResNet18 model. The two branches are integrated through probability-level late fusion using a validation-selected fusion weight. Explainability is implemented in a modality-specific manner: global coefficient analysis is used to identify influential textual cues, while Grad-CAM heatmaps are used to visualize salient image regions. Experiments were conducted on paired samples from the Open-i/IU X-Ray dataset using text-only, image-only, and fusion-based evaluation settings. Additional analyses include case-level complementarity analysis, bootstrap confidence intervals for ROC-AUC, shortcut-feature inspection, and qualitative Grad-CAM auditing. The results indicate that the text modality provides the dominant predictive signal under the current proxy-label setting. Late fusion produced a small descriptive improvement on the test set, increasing accuracy from 0.8533 to 0.8667, F1-score from 0.8817 to 0.8936, and ROC-AUC from 0.8936 to 0.9025 compared with the text-only baseline. However, the observed ROC-AUC improvement was not statistically conclusive based on bootstrap analysis. These findings suggest that the proposed framework is useful as a reproducible and auditable multimodal prototype, while also highlighting important limitations, including proxy-label ambiguity, potential label leakage from radiology reports, limited image-branch contribution, lack of external validation, and the need for stronger explanation and calibration assessment.
Co-Authors Abas, Hafiza Abdul Karim AHMADI Ali Imron Alwan Fadlurohman Anawai Basman, Aprilla Anggry Windasari April Firman Daru Arafat, Amaliah Sholeha Ariska Fitriyana Ningrum Basirudin Ansor Dannu Purwanto Dhani, Oktaviana Rahma Edy Winarno Eka Suryani, Puput Fadugba, Sunday Emmanuel Fauzi, Fatkhurokhman Fisabilillah, Muh. Irodat fitriani, ine Gansar Timur Pamungkas Hanif, Mohammad Burhan Haris, M. Al Ihsan Fathoni Amri Indah Fitriyani Indah Manfaati Nur Indah Manfaati Nur Ismi Elya Wirdati Khoirudin Khoirudin Khoirudin Khoirudin, Khoirudin M. Al Haris Mandala Adikara Sencoko Manfaati Nur, Indah Masudah, Nurhidayatul Mohammad Ridwan Muhammad Ivan Ardiansyah Musa, Fitri Diana Nur, M. Saifudin Panata, Helmi Prasetio Prajanto Wahyu Adi Prasetyo, Noer Prizka Rismawati Arum Purnomo Putro, Dwi Puspitasari, Listi Putri, Agata Dwi Putri Putro, Dwi Purnomo Rahman , Budiono Ridwanulhaq, Alfina Fauziah Rifa i, Ahmad Rohani, Imam Safira, Rahma Sawiah Adam, Asriyanti Sitti Sahara supriadin supriadin Supriadin Supriadin Supriyadin, Supriyadin Wardani, Amelia Kusuma Wendy Sarasjati