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All Journal JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI Jurnal Pemberdayaan Masyarakat Universitas Al Azhar Indonesia Prosiding Seminar Nasional Pemberdayaan Masyarakat (SENDAMAS)
Arniaty, Andi
Universitas Al-Azhar Indonesia
Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Education Electrical & Electronics Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences

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Pemberdayaan Kemitraan Masyarakat Petani: Penerapan Multi Cropping dan Smart Farming di Dusun Cihieum, Desa Sukanagalih Cianjur, Jawa Barat Noriko, Nita; Effendi, Yunus; Pambudi, Arief; Arniaty, Andi; Armelia, Adela; Mandjusri, Alma
Jurnal Pemberdayaan Masyarakat Universitas Al Azhar Indonesia Vol 7, No 1 (2024): Desember 2024
Publisher : Universitas Al Azhar Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36722/jpm.v7i1.3211

Abstract

Biaya  produksi yang tinggi dibandingkan dengan penjualan merupakan masalah yang dihadapi petani dusun Cihieum Kampung Cibeureum, desa Sukanagalih. Penyebabnya adalah biaya sewa lahan, kebutuhan pupuk, pestisida, ketersediaan air dan upah tenaga kerja untuk pengolahan lahan. Solusi dalam menghadapi permasalahan ini adalah menerapkan, multi cropping, smart farming, konservasi tanah dan air serta penggunaan traktor tangan. Tujuan yang akan dicapai adalah mengurangi biaya produksi dan meningkatkan hasil pertanian. Metode yang dilakukan untuk menjalankan solusi tersebut adalah mengadakan Pemberdayaan Kemitraan Masyarakat(PKM) untuk petani mitra melalui sosialisasi dan workshop. Hasil PKM menunjukkan adanya peningkatkan pengetahuan dan kemampuan petani untuk melaksanakan multi cropping dan smart farming, konservasi tanah dan air serta penggunaan traktor tangan. Penerapkan multi cropping dan smart farming, konservasi tanah dan air serta traktor tangan dapat menekan biaya produksi hingga 30% dan hasil pertanian pada satu areal terdiri atas 2 komoditi seperti Capsicum annuum (cabai merah) dan Phaseolus vulgaris (buncis). Hasil produksi C. annuum dapat meningkat 30% dan P. vulgaris 100%. Peningkatan keuntungan bududaya cabai merah  dapat mencapai 91%.
Pemodelan Emosi Pengguna Berbasis Ulasan Digital Melalui Integrasi Natural Language Processing dan Ilmu Sosial Komputasional Adinda Riska Safitri; Andi Arniaty Arsyad
JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI Vol 11, No 2 (2026): Mei 2026
Publisher : Universitas Al Azhar Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36722/sst.v11i2.5425

Abstract

Internal company apps such as PT Astra Honda Motor’s AHM Mobile receive a wide range of reviews on the Google Play Store that contain users’ emotional expressions. However, the emotional dimension of these reviews has rarely been systematically analyzed, as most previous studies have focused only on positive, negative, and neutral sentiments. This study aims to analyze the emotions of AHM Mobile users through the integration of Natural Language Processing (NLP) and Computational Social Science perspectives. The dataset consists of 2.117 reviews obtained via web scraping and classified into six emotional categories: angry, sad, afraid, neutral, surprised, and happy. The annotation process was conducted by two annotators in the fields of clinical psychology and linguistics using a Seniority-Based Tie-Breaking mechanism with a Cohen’s Kappa value of 0.636. Emotion classification was performed using a combination of TF-IDF and Logistic Regression as classical models, as well as IndoBERT as the main model. Evaluation results show that the classical model achieved an accuracy of 0.43 and a macro-F1 score of 0.183, while IndoBERT reached an accuracy of 0.7831 and a macro-F1 score of 0.5582. Collective emotion analysis indicates that anger dominates user reviews and is strongly correlated with user ratings, as evidenced by a Spearman correlation coefficient of 0.7141. These results indicate that sentiment analysis using the IndoBERT model can provide more effective insights for evaluating the quality of usage of internal corporate applications in Indonesia.Keywords - Computational Social Science (CSS), Emotion Classification, IndoBERT, Natural Language Processing (NLP), User Reviews of the AHM Mobile Application.
EduCrypt: A Secure File Data Sharing Platform using Hybrid Encryption for Cloud-Based E-Learning Andi Arniaty Arsyad; Riri Safitri; Lambda Sangkala Murbawisesa
JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI Vol 11, No 1 (2026): Januari 2026
Publisher : Universitas Al Azhar Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36722/sst.v11i1.5086

Abstract

The rise of cloud-based learning environments has transformed education but has also exposed vulnerabilities in data security. Learning Management Systems (LMSs) often handle sensitive academic data without adequate protection, leaving it vulnerable to unauthorized access and data breaches. This study introduces EduCrypt, a secure file-sharing platform that uses hybrid encryption, combining AES for fast data encryption and RSA for secure key exchange. In this research, a Hybrid Waterfall–Iterative method was used as the overarching research methodology to guide requirements analysis, architectural design, system implementation, and evaluation. EduCrypt integrates seamlessly with Moodle LMS via token- and credential-based authentication. Its architecture includes asynchronous RabbitMQ workers for efficient synchronization and a user-friendly web interface for secure file operations. Benchmark tests demonstrate stable encryption and decryption times under 300 ms for files up to 30 MB, showcasing both scalability and efficiency. Security evaluations confirm that EduCrypt effectively mitigates brute-force attacks, SQL injection, and man-in-the-middle attacks. This research resulted in a validated enhancement in file security practices for LMS through the implementation of a hybrid cryptographic model. Furthermore, the outcome includes a fully functional EduCrypt prototype integrated with Moodle, along with performance and security evaluation results.Keywords - Data Security, Hybrid encryption, File sharing, E-learning, Cloud computing.
A Knowledge-Based Stress Diagnosis System Using the Certainty Factor Approach and DASS-42 Psychological Indicators Winangsari Pradani; Syarifah Hani; Siti Rahmawati; Ade Jamal; Andi Arniaty Arsyad
Prosiding Seminar Nasional Pemberdayaan Masyarakat (SENDAMAS) Vol 5, No 1 (2025): Desember 2025
Publisher : UniversitasAl Azhar Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36722/psn.v5i1.5018

Abstract

Stress is a natural physiological and psychological response to everyday demands, yet chronic stress can impair cognitive functioning, emotional regulation, sleep quality, social interaction, and academic or occupational performance. Access to mental health professionals remains limited and early detection is crucial. To address this issue, this study developed a Depression, Anxiety, and Stress Scale-42 (DASS-42)–based expert system for stress diagnosis using the Certainty Factor (CF) method. A key contribution of this work is the active involvement of licensed psychologists in knowledge elicitation, rule construction, symptom weighting, and iterative validation, ensuring clinical accuracy, reliability, and interpretability. The system underwent functional, usability, and diagnostic testing. Black Box Testing confirmed full feature performance (100%), indicating strong system stability. Usability evaluation using the System Usability Scale (SUS) produced a score of 78.375 (Grade B+, “Good”), with the highest acceptance among students and employees, and lower ratings from users with limited digital literacy. Diagnostic validation using 20 test cases assessed by two certified psychologists yielded an average accuracy of 87.5%, showing strong agreement between system results and expert judgment. These findings demonstrate that CF-based reasoning effectively models clinical evaluation of 13 stress indicators from DASS-42, indicating the system’s feasibility a reliable early stress-screening tool.Keywords— Certainty Factor, DASS-42, Expert System, Mental Health Screening, Stress Diagnosis
Design and Implementation of a Blockchain-based Shipment Tracking Proof-of-Concept for Academic Application Andi Arniaty Arsyad; Riri Safitri; Winangsari Pradani; Nurbojatmiko Nurbojatmiko; Abdullah Abdullah
Prosiding Seminar Nasional Pemberdayaan Masyarakat (SENDAMAS) Vol 5, No 1 (2025): Desember 2025
Publisher : UniversitasAl Azhar Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36722/psn.v5i1.5053

Abstract

The demand for secure, transparent shipment tracking is rising as digital logistics advances. Traditional centralized tracking systems face issues such as data delays and manipulation, which reduce trust and accuracy. This research aims to create a blockchain-based shipment-tracking system that serves as both a prototype and an educational tool for students. The system features a user interface built with Vue.js and utilizes a middleware layer with Node.js and Express.js. A smart contract in Solidity is deployed on a local Ethereum network using the Hardhat framework. This prototype allows students to engage with decentralized application development and explore interactions among front-end components, middleware, and smart contracts. Each transaction is recorded immutably, with an average gas consumption of about 175,000 units and execution times under 2 seconds, while preventing duplicate shipments. This research offers a functional shipment-tracking model that provides transparent data recording and serves as an effective framework for blockchain education, bridging theoretical concepts with practical applications in higher education.Keywords – Academic Application, Blockchain, Shipment Tracking, Smart Contract, Solidity.
Co-Authors Abdullah Abdullah Ade Jamal Adinda Riska Safitri Alma Mandjusri Arief Pambudi Armelia, Adela Hani Syarifah Lambda Sangkala Murbawisesa Nita Noriko Nurbojatmiko Nurbojatmiko Pradani, Winangsari Riri Safitri Riri Safitri Siti Rahmawati Yunus Effendi