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All Journal Scientific Journal of Informatics JITK (Jurnal Ilmu Pengetahuan dan Komputer) International Journal of Engineering, Technology and Natural Sciences (IJETS) BERNAS: Jurnal Pengabdian Kepada Masyarakat Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Jurnal Ilmu Komputer dan Informatika J-ESA (Jurnal Ekonomi Syariah) Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Taroa : Jurnal Pengabdian Masyarakat SEWAGATI: Jurnal Pengabdian Kepada Masyarakat Abdi Masyarakat UIKA Journal of Excellence Humanities and Religiosity Jurnal Pengabdian Nusantara Jurnal Pengabdian kepada Masyarakat (PEMAS) Scientific: Journal of Computer Science and Informatics Journix: Journal of Informatics and Computing Indonesian Applied Research Computing and Informatics
Sutriawan
Department Of Computer Science, Universitas Muhammadiyah Bima, Indonesia
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Pelatihan Aplikasi Pencatatan Keuangan Berbasis Mobile untuk Pelaku UMKM di Rabanggodu Selatan Zumhur Alamin; Sutriawan; Fathir; Muhammad Amirul Mu'min
Jurnal Pengabdian kepada Masyarakat (PEMAS) Vol. 1 No. 2 (2024): Mei 2024
Publisher : Yayasan Ran Edu Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63866/pemas.v1i2.52

Abstract

Pelaku UMKM sering menghadapi kendala dalam pencatatan keuangan yang sistematis, yang berdampak pada pengelolaan arus kas dan pengambilan keputusan bisnis. Untuk mengatasi masalah ini, kegiatan pengabdian ini bertujuan meningkatkan literasi keuangan digital melalui pelatihan penggunaan aplikasi pencatatan keuangan berbasis mobile bagi pelaku UMKM di Kelurahan Rabanggodu Selatan, Kota Bima. Pendekatan yang digunakan adalah Mixed-Methods, menggabungkan metode kuantitatif dan kualitatif dengan teknik pelatihan dan pendampingan partisipatif. Sebanyak 30 pelaku UMKM dipilih dengan metode purposive sampling berdasarkan keterbatasan dalam pencatatan keuangan manual serta kepemilikan perangkat mobile yang mendukung aplikasi digital. Pelatihan ini terdiri dari sosialisasi, praktik langsung menggunakan aplikasi BukuWarung, Money Lover, dan Catatan Keuangan Harian, serta evaluasi efektivitas melalui pre-test dan post-test, wawancara, serta observasi. Hasil analisis kuantitatif menunjukkan adanya peningkatan signifikan dalam pemahaman dan keterampilan peserta setelah pelatihan, sebagaimana dibuktikan oleh perbedaan skor pre-test dan post-test. Sementara itu, analisis kualitatif mengungkapkan bahwa mayoritas peserta memilih BukuWarung sebagai aplikasi yang paling mudah digunakan. Tantangan utama yang dihadapi peserta mencakup keterbatasan perangkat, akses internet, serta kebiasaan pencatatan manual yang sulit diubah. Kesimpulannya, pelatihan ini efektif dalam meningkatkan kemampuan pencatatan keuangan digital UMKM. Model pelatihan serupa dapat diterapkan lebih luas dengan dukungan pemerintah dan lembaga terkait guna mempercepat adopsi teknologi keuangan digital di sektor UMKM.
Pelatihan Literasi Digital dan Pengelolaan Data Pribadi untuk Remaja di Era Big Data Siti Mutmainah; Teguh Ansor Lorosae; Alamin, Zumhur; Sutriawan
Jurnal Pengabdian kepada Masyarakat (PEMAS) Vol. 2 No. 2 (2025): Mei 2025
Publisher : Yayasan Ran Edu Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63866/pemas.v2i2.74

Abstract

Era big data telah membawa perubahan yang signifikan dalam cara remaja berinteraksi dan mengelola informasi. Meskipun demikian, aktivitas digital yang tinggi juga disertai dengan risiko terkait privasi dan keamanan data pribadi. Kegiatan pengabdian ini bertujuan untuk meningkatkan literasi digital dan kesadaran akan pentingnya pengelolaan data pribadi di kalangan remaja di Kota Bima. Metode kegiatan yang digunakan antara lain penyuluhan interaktif, studi kasus insiden kebocoran data, dan simulasi pengaturan privasi di platform media sosial. Evaluasi dilakukan melalui pre-test dan post-test yang bertujuan untuk mengukur peningkatan pemahaman peserta. Berdasarkan evaluasi pre-test dan post-test menunjukkan adanya peningkatan yang signifikan pada pemahaman remaja mengenai konsep big data, jejak digital, potensi risiko siber (seperti phishing dan malware), serta tindakan praktis untuk melindungi data pribadinya. Peserta juga menunjukkan antusiasme yang tinggi dan partisipasi aktif selama kegiatan berlangsung. Pelatihan yang diselenggarakan efektif membekali remaja dengan pengetahuan dan keterampilan dasar untuk menavigasi dunia digital dengan lebih aman dan bertanggung jawab, sekaligus meningkatkan kesadaran remaja akan pentingnya menjaga privasi data di tengah masifnya arus informasi.
DEEP LEARNING JARINGAN SARAF TIRUAN UNTUK PEMECAHAN MASALAH DETEKSI PENYAKIT DAUN APEL Sutriawan, Sutriawan; Fanani, Ahmad Zainul; Alzami, Farrikh; Basuki, Ruri Suko
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 11, No 1 (2023): Jurnal TIKomSiN, Vol. 11, No. 1, April 2023
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v11i1.729

Abstract

Diseases on apple leaves are becoming a major issue for apple growers since they can cause the crop to fail. Due to the diversity of diseases that can affect apple leaves, it can be challenging for farmers to determine the cause of leaf damage. The purpose of this research is to evaluate a convolutional neural network (CNN) method for its potential use in solving the problem of apple leaf disease identification. Four types of illness are dealt with: normal, multi-illness, rusty, and scabby. Many methods, such as data preparation and a preset VGG-16 artificial neural network (CNN) architecture, are recommended for use in the deep artificial neural network processing method. The most precise outcomes occurred when the beta parameter value was set to 2 = 0.999 at Ephoch to 85/100 with an accuracy of 0.7582, and when the epsilon parameter value was set to 1e-07 at Ephoch to 32/100 with an accuracy of 0.7582 with the best accuracy.
Kolaborasi Bersama Menuju Pendidikan Berkualitas: Pengalaman Penerapan Service Learning di Sekolah Menengah Atas Missouri, Randitha; Alamin, Zumhur; Sutriawan, Sutriawan; Annafi, Nurfidianty; Lukman, Lukman
Taroa: Jurnal Pengabdian Masyarakat Vol 1 No 1 (2022): Januari
Publisher : LPPM IAI Muhammadiyah Bima

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52266/taroa.v1i1.969

Abstract

Artikel ini menyajikan hasil dari implementasi Service Learning di Sekolah Menengah Atas (SMA) Muhammadiyah Kota Bima dengan tujuan untuk meningkatkan kualitas pendidikan. Metode pengabdian ini melibatkan kolaborasi antara perguruan tinggi dan SMA dalam memperkuat pembelajaran melalui pelayanan masyarakat. Data kuantitatif yang terkumpul menunjukkan dampak positif yang signifikan dari program ini. Terjadi peningkatan yang signifikan dalam tingkat kehadiran siswa, dengan peningkatan sebesar 15% setelah implementasi program. Selain itu, survei kepuasan siswa dan guru menunjukkan tingkat kepuasan yang tinggi terhadap program Service Learning, dengan 95% siswa dan 90% guru merasa puas. Hasil akademis siswa juga meningkat, ditunjukkan oleh peningkatan nilai rata-rata sebesar 10 poin. Selain itu, terjadi peningkatan partisipasi siswa dalam kegiatan ekstrakurikuler sebesar 20%. Hasil ini menunjukkan bahwa Service Learning merupakan pendekatan yang efektif dalam memperkuat kualitas pendidikan di SMA, dengan memberikan manfaat yang signifikan bagi siswa, guru, dan komunitas sekolah secara keseluruhan. Dengan demikian, kolaborasi antara perguruan tinggi dan masyarakat melalui Service Learning menjadi salah satu strategi yang potensial dalam meningkatkan pendidikan yang berkualitas.
PENGUATAN DAYA SAING UMKM MELALUI PELATIHAN KETERAMPILAN TEKNOLOGI DI ERA SOCIETY 5.0 Alamin, Zumhur; Lukman, Lukman; Missouri, Randitha; Annafi, Nurfidianty; Sutriawan, Sutriawan; Khairunnas, Khairunnas
Taroa: Jurnal Pengabdian Masyarakat Vol 1 No 2 (2022): Juli
Publisher : LPPM IAI Muhammadiyah Bima

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52266/taroa.v1i2.1235

Abstract

Artikel ini menggambarkan dampak positif dari program pelatihan keterampilan teknologi terhadap UMKM, fokus utama dalam menghadapi transformasi digital. Melalui survei yang melibatkan berbagai sektor UMKM, hasil menunjukkan peningkatan efisiensi operasional sebesar 85%, terutama dalam manajemen inventaris dan operasional. Ekspansi akses pasar melalui platform digital mencapai 70%, menandakan keberhasilan UMKM dalam mencapai pelanggan lebih luas melalui toko online dan e-commerce. Adaptasi strategi bisnis menuju layanan daring, dengan pertumbuhan pendapatan sebesar 60%, menjadi merespons perubahan perilaku konsumen yang memilih kenyamanan dalam layanan pesan antar dan pemesanan online. Integrasi sistem pembayaran digital, mencapai persentase positif sebesar 75%, membuktikan bahwa UMKM yang memfasilitasi pembayaran digital dapat meningkatkan efisiensi dan kepercayaan pelanggan. Dampak positif pada brand dan reputasi, mencapai 90%, menandakan bahwa aktivitas di media sosial memberikan kontribusi dalam membangun hubungan dengan pelanggan. Ulasan positif dan keterlibatan di media sosial meningkatkan citra brand UMKM secara signifikan. Hasil ini mencerminkan bahwa literasi teknologi menjadi kunci sukses UMKM dalam menghadapi dinamika bisnis di era Society 5.0.
Indonesian News Text Summarization Using MBART Algorithm Astuti, Rahma Hayuning; Muljono, Muljono; Sutriawan, Sutriawan
Scientific Journal of Informatics Vol 11, No 1 (2024): February 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i1.49224

Abstract

Purpose: Technology advancements have led to the production of a large amount of textual data. There are numerous locations where one can find textual information sources, including blogs, news portals, and websites. Kompas, BBC, Liputan 6, CNN, and other news portals are a few websites that offer news in Indonesian. The purpose of this study was to explore the effectiveness of using mBART in text summarization for Bahasa Indonesia.Methods: This study uses mBART, a transformer architecture, to perform fine-tuning to generate news article summaries in Bahasa Indonesia. Evaluation was conducted using the ROUGE method to assess the quality of the summaries produced.Results: Evaluation using the ROUGE metric showed better results, with ROUGE-1 of 35.94, ROUGE-2 of 16.43, and ROUGE-L of 29.91. However, the performance of the model is still not optimal compared to existing models in text summarization for another language.Novelty: The novelty of this research lies in the use of mBART for text summarization, specifically adapted for Bahasa Indonesia. In addition, the findings also contribute to understanding the challenges and opportunities of improving text summarization techniques in the Indonesian context.
FCM-Guided CNN with Fuzzy Membership Maps for Robust Brain MRI Tumor Classification Firnanda Al-Islama Achyunda Putra; Kukuh Yudhistiro; Sutriawan; Zumhur Alamin
Journix: Journal of Informatics and Computing Vol. 1 No. 3 (2025): December
Publisher : Ran Edu Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63866/journix.v1i3.9

Abstract

Accurate brain MRI classification is critical for early tumor diagnosis and computer-aided clinical decision support. Conventional convolutional neural networks (CNNs) are effective in learning deep hierarchical features but often struggle with intensity heterogeneity and partial volume effects inherent to MRI data. To address these limitations, this study proposes a hybrid Fuzzy C-Means–CNN (FCM–CNN) framework that integrates unsupervised soft clustering with deep feature learning. The fuzzy segmentation stage preserves boundary uncertainty by generating multi-channel membership maps, which are then fed into a CNN for robust classification. Evaluations conducted on the Kaggle brain MRI dataset (3,264 slices across four diagnostic categories) under Stratified 5-Fold Cross-Validation show consistent improvements over baseline models. The proposed FCM–CNN achieves a mean accuracy of 96.26% and Macro-F1 of 0.9622, surpassing both CNN-only and K-Means+CNN by +4.84% and +2.74% respectively. Ablation analysis confirms that soft memberships enhance discrimination between visually similar tumors, while statistical testing verifies that the gains are systematic and reproducible. Furthermore, the fuzzy membership maps provide interpretable visual cues, aligning with recent trends in explainable AI (XAI) for medical imaging. Overall, the FCM–CNN framework demonstrates that combining fuzzy logic with deep learning yields a balanced trade-off between performance, interpretability, and computational efficiency, making it promising for clinical-grade brain MRI analysis.
Implementation of Post-Quantum Cryptography Algorithms for Financial Applications in Indonesia Sutriawan; Enggar Novianto
Journix: Journal of Informatics and Computing Vol. 1 No. 2 (2025): August
Publisher : Ran Edu Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63866/journix.v1i2.13

Abstract

The development of quantum computing poses a serious threat to classical cryptographic algorithms that have been used to protect digital data and financial transactions. Algorithms such as RSA and Elliptic Curve Cryptography (ECC) are vulnerable to quantum computer attacks capable of running Shor's algorithm to efficiently solve large number factorization problems. This study aims to explore and analyze the implementation of Post-Quantum Cryptography (PQC) algorithms, specifically Falcon and Dilithium, in the context of digital financial systems in Indonesia. The research approach was conducted through literature studies and case study analysis on the Algorand platform, which has adopted the Falcon algorithm to strengthen digital signature security. The results of the study show that the integration of PQC algorithms can be done without sacrificing system efficiency, while providing a significant increase in security resilience against quantum threats. This research is expected to serve as a reference for financial institutions and national regulators in formulating transition strategies towards a secure digital security infrastructure in the quantum era.
A HYBRID BERT–GNN FOR DETECTING HOAXES AND NEGATIVE CONTENT IN INDONESIAN SOCIAL MEDIA Khairunnisa; Khairunnas; Sutriawan
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 3 (2026): JITK Issue February 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i3.7330

Abstract

The rapid spread of hoaxes on social media threatens public trust and information integrity, especially within the Indonesian digital landscape. This study proposes a hybrid deep learning model that integrates transformer-based semantic representation from IndoBERT with Graph Neural Networks (GNNs) to enhance hoax detection performance. A heterogeneous social graph is constructed to model relationships among posts, users, and news sources, where post node features are extracted from the [CLS] embeddings of a fine-tuned IndoBERT. The GNN component consists of two graph convolutional layers with ReLU activation and dropout, followed by a multilayer perceptron classifier for binary classification. Experiments conducted on the Indonesia False News dataset (Kaggle) employ SMOTE resampling to handle class imbalance and 5-fold stratified cross-validation for robust evaluation across three configurations: BERT-only, GNN-only, and the proposed BERT–GNN hybrid model. The hybrid model achieves an average F1-score of 0.89 ± 0.01 and ROC-AUC of 0.92 ± 0.01, outperforming both single-model baselines while maintaining a balanced precision–recall trade-off. These results confirm that combining contextual semantic understanding with relational graph topology substantially enhances accuracy, robustness, and generalization in detecting hoaxes within Indonesian-language social media content
Development of a Dashboard-Based Information System to Improve Prospective Customer Engagement at PLN UP3 Bima Aldillah; Zumhur Alamin; Lailia Rahmawati; Sutriawan; Teguh Ansyor Lorosae; Fitriani Ramadhani
Indonesian Applied Research Computing and Informatics Vol. 1 No. 1: July (2025)
Publisher : PT. Teras Digital Nusantara

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

Abstract

PT PLN (Persero) UP3 Bima faces challenges in effectively managing and analyzing prospective customer data, resulting in delays in decision-making and suboptimal utilization of potential connected power. This study aims to develop an interactive dashboard system using Looker Studio and Google Sheets to improve operational efficiency and support digital transformation within PLN. The methodology includes user needs analysis, real-time data integration from Google Sheets, and the design of data visualizations in Looker Studio based on key parameters such as customer growth trends, sector classification, and potential connected power. The implementation results show that the system effectively delivers accurate and timely information, assisting management in identifying opportunities to increase new customer connections. The impact of this system includes enhanced effectiveness in managing prospective customer data, faster decision-making processes, and stronger support for data-driven strategies to increase customer acquisition in a measurable way.
Co-Authors Ade Kurniawan Afril Efan Pajri Ahmad Zainul Fanani Ahmad Zaniul Fanani Aldillah Alkhair Alzami, Farrikh Astuti, Rahma Hayuning Budiman Budiman Enggar Novianto Erham Erham Erviana, Irma Fathir Fathir Fathir Fathurrahman Fathurrahman Fitriani Ramadhani Gufran Gufran, Gufran Hamiah, Nurul Husnul Khatimah, Nur Khairunnas Khairunnas, Khairunnas Khairunnisa Khairunnisa Khairunnisa Khatimah, Nur Husnul Kukuh Yudhistiro, Kukuh Lailia Rahmawati LUKMAN, LUKMAN M. Fikram Muammar Iksan Muh. Alimin Muhammad Akbar Muhammad Amirul Mu'min Muhammad Hayun Muljono Muljono Mursalim Mursalim Nimas Ratna Sari Nur Hunul Khatimah Nur Husnul Khatimah Nur Wahyu Hidayat Nurfidianty Annafi, Nurfidianty Putra, Firnanda Al Islama Achyunda Rahmawati, Lailia Randitha Missouri Rosyid, Romadhoni Ruri Suko Basuki Sahrul Ramadhan Sanusi, Gufran Siti Mutmainah Taufik Azhary Teguh Ansyor Lorosae Teguh Ansyor Lorosae Ummu Rofikah Widayati, Ulfa Zumhur Alamin Zumhur Alamin Zuraini, Irma