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Applying Local Interpretable Model-agnostic Explanations (LIME) for Interpretable Deep Learning in Lung Disease Detection Ananda, Sherly; Negara, Benny Sukma; Irsyad, Muhammad; Jasril, Jasril; Iskandar, Iwan
Journal of Artificial Intelligence and Software Engineering Vol 5, No 2 (2025): Juni On-Progress
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i2.7042

Abstract

Artificial Intelligence (AI) semakin banyak diterapkan dalam bidang kesehatan melalui model Machine Learning (ML) dan Deep Learning (DL). Namun, kompleksitas model modern yang bersifat black-box menimbulkan kebutuhan akan metode interpretasi yang transparan. Explainable AI (XAI) hadir untuk menjembatani hal tersebut, dengan memberikan pemahaman yang lebih baik terhadap kinerja model. Penelitian ini mengimplementasikan metode Local Interpretable Model-agnostic Explanations (LIME) untuk memvisualisasikan hasil klasifikasi model DL berbasis arsitektur ResNet18 terhadap citra Chest X-ray (CXR) pada tiga kelas: normal, COVID-19, dan pneumonia. Model mencapai precision, recall, dan F1-score rata-rata sebesar 97%, serta Accuracy sebesar 98%. Visualisasi LIME menunjukkan area citra yang berkontribusi signifikan terhadap klasifikasi, serta mampu membedakan ketiga kelas dengan baik. Hasil ini mendukung penggunaan XAI untuk meningkatkan interpretabilitas model DL dalam diagnosis medis.
Interpreting Lung Disease Detection from Chest X-rays Using Layer-wise Relevance Propagation (LRP) Fauziyyah, Laila Nurul; Negara, Benny Sukma; Irsyad, Muhammad; Iskandar, Iwan; Yanto, Febi
Journal of Artificial Intelligence and Software Engineering Vol 5, No 2 (2025): June
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i2.7043

Abstract

Penelitian ini mengusulkan pendekatan klasifikasi penyakit paru berbasis citra X-ray menggunakan arsitektur VGG16 yang dilengkapi metode interpretabilitas Layer-wise Relevance Propagation (LRP). Dataset terdiri dari tiga kelas: COVID-19, pneumonia, dan normal, yang diproses melalui augmentasi dan normalisasi. Model dilatih dengan rasio data 70:30, learning rate 0.001, batch size 32, dan optimizer Adam. Hasil pelatihan menunjukkan akurasi tinggi sebesar 96,78% dengan nilai precision, recall, dan F1-score yang seimbang. Metode LRP digunakan untuk menyoroti area penting pada citra yang berkontribusi terhadap prediksi model, sehingga meningkatkan transparansi keputusan. Kontribusi utama penelitian ini adalah integrasi VGG16 dengan LRP dalam klasifikasi multi-kelas citra X-ray, yang memberikan hasil akurat sekaligus interpretasi visual yang mendukung kepercayaan dalam aplikasi medis.
Application of Shapley Additive Explanations (SHAP) in Deep Learning for Lung Disease Detection Using X-ray Images Muliani, Sarifah; Negara, Benny Sukma; Irsyad, Muhammad; Jasril, Jasril; Iskandar, Iwan
Journal of Artificial Intelligence and Software Engineering Vol 5, No 2 (2025): June
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i2.7044

Abstract

Pemeriksaan menggunakan citra x-ray merupakan metode yang efektif dalam membantu deteksi penyakit paru-paru, seperti COVID-19, dan pneumonia. Seiring dengan perkembangan teknologi yang meningkat, proses diagnosis kini dapat dilakukan secara lebih akurat dengan memanfaatkan sistem berbasis kecerdasan buatan. Salah satu metode yang banyak digunakan adalah deep learning namun metode ini bersifat black-box, sehingga hasil prediksi sulit dipahami dengan alasan dibalik keputusan model. Tujuan penelitian ini adalah untuk membangun sistem klasifikasi citra x-ray menggunakan model deep learning berbasis Convolutional Neural Network (CNN) dengan arsitektur VGG-16, serta menerapkan metode Shapley Additive Explanations (SHAP) untuk memberikan penjelasan mengenai visual terkait area citra yang mempengaruhi hasil prediksi. Model dilatih menggunakan beberapa konfigurasi, dan hasil terbaik diperoleh pada rasio data 80% : 20%, learning rate 0.001, batch size 32, dan 50 epoch. Hasil penelitian menunjukkan bahwa model mampu mencapai akurasi sebesar 95,75% pada data training dan 96,00% pada data validasi. Metode SHAP digunakan untuk meningkatkan pemahaman terhadap hasil prediksi. Hasil menunjukkan bahwa kombinasi deep learning dan SHAP mampu memberikan penjelasan visual terhadap hasil prediksi model.
Lung Disease Detection Using Gradient-Weighted Class Activation Mapping (Grad-CAM) Sofiyah, Wan; Negara, Benny Sukma; Irsyad, Muhammad; Iskandar, Iwan; Yanto, Febi
Journal of Artificial Intelligence and Software Engineering Vol 5, No 2 (2025): June
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i2.7041

Abstract

Early detection of respiratory diseases such as Coronavirus Disease-19 (Covid-19) and Pneumonia is crucial for accelerating treatment and preventing more serious complications. This study proposes a method for classifying Chest X-ray (CXR) images using a Convolutional Neural Network (CNN) to distinguish between Covid-19, Pneumonia, and normal lungs. Model training involved exploring various hyperparameter combinations to find the optimal configuration. The best results were achieved with a learning rate of 0.001, 50 epochs, and a batch size of 32, yielding an accuracy of 96.33%. Evaluation was conducted using accuracy, precision, recall, F1-score, and confusion matrix metrics. This study uses Gradient-Weighted Class Activation Mapping (Grad-CAM) as a transparent interpretation tool for model decisions. The main contribution of this study is the application of Grad-CAM in multi-class CXR classification to enhance model interpretability in lung disease diagnosis.
Perancangan UI/UX Aplikasi Zaafer Mobile Menggunakan Metode Design Thinking Ardelia, Adinda Abidah; Irsyad, Muhammad; Chandra, Reski Mai; Affandes, Muhammad
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 2 (June 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i2.1197

Abstract

Zaafer is a company specializing in slim-fit men’s Muslim attire, operating an official e-commerce site at www.zaaferindonesia.id. After interviewing ten users who had previously shopped on the Zaafer website, we found that they did not receive real-time notifications and felt more comfortable shopping via an Android app rather than through the website. This insight motivated the design of a mobile-based Zaafer application to enhance the user experience. The relationship between user interface interactions and UX is a critical factor in application design. This study aims to design the UI/UX of the Zaafer mobile application using the Design Thinking methodology, which comprises five stages: empathize, define, ideate, prototype, and testing. Prototype testing of the Zaafer mobile app using the Single Ease Question method yielded a score of 6.33 out of 7, indicating a good rating. Based on these results, we conclude that the UI/UX design of the Zaafer mobile application is well accepted by users.
Manifesting community language learning activities in Islamic boarding school speaking program Bukhori, Bukhori; Irsyad, Muhammad
Englisia Journal Vol 12 No 2 (2025)
Publisher : Universitas Islam Negeri Ar-Raniry Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/ej.v12i2.28491

Abstract

Community Language Learning (CLL) is an educational approach designed to foster speaking proficiency. This study explores the application of CLL activities within an English-speaking program at an Islamic boarding school in Indragiri Hilir Regency, Riau. Employing a qualitative case study methodology, data were gathered through observations, interviews, and document analysis, involving four teachers and two students. Findings reveal that the CLL approach was implemented through four key activities: repetition, free conversation, listening practice, and daily speaking exercises, supported by media such as vocabulary boards (Richards & Rodgers, 2001). These activities significantly enhanced students’ speaking skills, fostering an interactive and collaborative learning environment. In conclusion, specific CLL activities proved effective for developing speaking proficiency in this Islamic boarding school context. Recommendations include addressing identified challenges to further optimize program effectiveness.
Do ESG Performance Improve Bank Stability: Comparative Analysis Islamic vs Conventional Bank Irsyad, Muhammad; Chairiyati, Fauziah; Rachmadi, Erfan
Jurnal Magister Ekonomi Syariah Vol. 3 No. 2 Desember (2024): J-MES: Jurnal Magister Ekonomi Syariah
Publisher : Program Studi Magister Ekonomi Syariah, Fakultas Ekonomi dan Bisnis Islam, Universitas Islam Negeri Sunan Kalijaga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jmes.2024.032-06

Abstract

This research examines the impact of ESG on the stability of conventional banks and Islamic banks in Indonesia and Malaysia. Using panel data from 140 conventional banks and 27 Islamic banks from 2014-2023, we found that ESG performance has a significantly positive impact on bank stability. The research results indicate that ESG significantly affects the stability of both Islamic and conventional banks. Furthermore, the research results also indicate that the environmental pillar has a more significant impact on the stability of conventional banks and the social pillar has a more significant impact on the stability of Islamic banks. The results of this research can be utilized by stakeholders to pay more attention to ESG performance as an effort to maintain the long-term stability of both conventional and Islamic banks.
Advancing precision in air quality forecasting through machine learning integration Komarudin, Muhamad; Ratna Sulistiyanti, Sri; Suharso, Suharso; Irsyad, Muhammad; Dian Septama, Hery; Yulianti, Titin; Sophian, Ali; Michel, Michel
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i3.pp2113-2122

Abstract

In an era where environmental concerns are escalating, air quality forecasting emerges. Forecasting is a crucial tool for addressing the adverse impacts of pollution on public health and ecosystems. In urban centers like Bandar Lampung, economic activities intensify pollution levels. This condition leveraging advanced machine learning forecasting methods can significantly mitigate these effects. This study evaluates the precision of long short-term memory (LSTM) and Prophet methods in predicting air quality. This study utilizes data from January 12, 2022 to November 9, 2023. The results reveal a distinct advantage of the LSTM method over the Prophet. The LSTM method showcases superior accuracy across all evaluation metrics. Specifically, the LSTM method achieved an average root mean squared error (RMSE) of 5.38, mean absolute error (MAE) of 3.94, and mean absolute percentage error (MAPE) of 0.07. In contrast, the Prophet method recorded higher error rates, with an average RMSE of 18.48, MAE of 15.61, and MAPE of 0.25. These numbers underscore the LSTM method's robustness and reliability in forecasting air quality. The result highlights its potential as a pivotal resource for environmental monitoring and policymaking to safeguard public health and promote sustainable urban development.
Sosialisasi Pemanfaatan Mesin Pencacah dalam Pengelolaan Sampah Mendukung SDGs Desa Peswaran Indah Prayitno, Hadi; Amrul; Irsyad, Muhammad; Nafrizal; Supono
Yumary: Jurnal Pengabdian kepada Masyarakat Vol. 5 No. 4 (2025): Juni
Publisher : Penerbit Goodwood

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/yumary.v5i4.3801

Abstract

Purpose: The purpose of this community service program in Desa Pesawaran Indah is to enhance public understanding and participation in sustainable waste management by introducing the 7R principles: Rethink, Refuse, Reduce, Repurpose, Reuse, Recycle, and Rot. Methodology: The program utilized a structured socialization approach, which included developing educational materials and conducting interactive discussions with village officials and members of the Women’s Farmers Group (KWT). Each 7R principle was introduced, practical applications were explored, and local waste management challenges were addressed. Results: The program resulted in a substantial increase in participants' understanding, with comprehension levels rising from an initial 2-4 participants to 18-21 participants who fully understood key principles like "Rethink" and "Recycle" by the program's conclusion. Conclusions: The program successfully enhanced community knowledge and engagement in sustainable waste management. Future initiatives could benefit from practical training to reinforce knowledge and empower participants to implement waste management strategies, contributing to the development of environmentally conscious communities aligned with broader sustainability goals. Limitations: The limitations of the study include the absence of practical demonstrations and the limited sample size, which may affect the generalizability of the findings. Contribution: This program contributes to the field of environmental education by promoting sustainable waste management practices within rural communities and aligning local actions with global sustainability goals.
Systematic Review of Valuation of State Property at the Indonesian State Property and Auction Service Office: Challenges and Successes Jayadi, Yusma Indah; Irsyad, Muhammad
Asian Journal of Management Analytics Vol. 3 No. 1 (2024): January 2024
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ajma.v3i1.7568

Abstract

This research focuses on the assessment of State Property (BMN) at the State Property and Auction Service Office (KPKNL). The Systematic Literature Review method was used using identified research questions consisting of PICO (Population, Intervention, Comparator, and Outcome). Case studies in several KPKNLs reveal that the role of work units has not been fully evaluated, the rental value calculation process has not been optimal, and BMN revaluation improvements have been successful despite facing obstacles. Although the assessment was carried out according to regulations, a need was found to address the lack of understanding of work units, optimize rental value calculations, and better time management. The BMN assessment at KPKNL is in accordance with regulations, but improvements are needed, including better understanding of work units, optimization of the rental value calculation process, and more efficient time management in BMN revaluation.
Co-Authors A.Yudi Eka Risano Aditya Gunawan, Aditya Admiral, Randa Agus Saputro, Mohammad Alif Agus Solikhin, Agus Agus Sugiri, Agus Agus Sutarjo Ahmad Farhan, Ahmad Ahmad Yonanda Akhmad Qashlim, Akhmad Alifa, Alifia Zuhriatul Alviona Marsya Alwis Alwis Amrizal Amrizal Amrul Amrul Amrul Ananda, Sherly Andysah Putera Utama Siahaan Aniswita Anshari, Muhammad Isa Anwar, Hasrul Ardelia, Adinda Abidah Asbanu, Govira Christiadora Assyarify, Hanif Aulia, Weko Indira Romanti Aziz, Qithfirul Azmi, Khairil Baehaqi Bukhori, Bukhori Chairiyati, Fauziah Chandra, Reski Mai Dafid Slamet Setiana Denik Agustito Desmaiani, Herda Dian Fadli, Dian Dwi, Nurdin Edi Tarigan, Tri Juli Elisabet Tambunan Elliyana, Dessy Em Yunir, Em Eriyadi, Riko erman Balo, Asri Andrias H Fachry Abda El Rahman Fadhilah Syafria Fajri, Zidan Fakhira, Adzra Fauziyyah, Laila Nurul Febi Yanto Febriansyah, Wahyu Fitri Insani Fitria Sulistyowati Fitriaty, Fitriaty Gusti, Siska Kurnia Hadi Prayitno Hadi Prayitno, Hadi Haida Fitri Hakim, Naufal Harmen, Harmen Haryanto Haryanto Hasan Basri Helmy Fitriawan Helviansyah, Try Hendrawan, Rezki Naufan HERU WAHYUDI Hery Dian Septama Iffa, Marwika Rifattul Iis Afrianty Irza Sukmana, Irza istiqomah istiqomah Iswati, Eni Jaelani, Alan Jasril Jasril Jasril Jasril Jayawarsa, A.A. Ketut Jumriah Syam, Jumriah Syam Junaidi Junaidi Khairudin, Rizal Khairul Khirfatul Jannah Krismadinata Krismadinata, Krismadinata kurnia, fitra Leni Marlina Lubis, Anggun Tri Utami BR. M, Musnaini M. Dyan Susila M. Haviz M. Ridho Ulya Martinus, Martinus Michel, Michel Misfa Susanto Muhamad Komarudin Muhammad Affandes Muhammad Arsan Jamili Muhammad Fikry Muliani, Sarifah Musafira Musafira Nadhif, Muhammad Hanif Nafrizal Najmi, Risna Lailatun Najmuddin Abd Shafa Nalis, Amrizal Nasution, Rodiah Nazir, Alwis Nazruddin Safaat Nazruddin Safaat H Negara, Benny Sukma Niky Fetra, Niky Nugraha, Yulian Nurdin, Bernediv Nurlaila, Endang Pizaini Pizaini Pratiwi, Trya Ayu Putri Ayuni, Desy R.S, Salsa Faradilla Rachmadi, Erfan Rafaelandri, Billy Rahmad Kurniawan Rahmad Kurniawan Raka Indra Lukmana Ramadhan, Muhammad Ilham Ramadhan, Syabani Ratna Sulistiyanti, Sri Retno Putri Lestari Rijal Febriyantono, Muhammad Riszal, Akhmad Riszal, Akmad Rizal Adi Saputra Rudi Susanto Safitri, Jehan Salsabillah, Angelia E. Sardi, Hajra Sarumpaet, Angela Satira, Husna Setiawan, Ahmad Adi Sibawaihi Sibawaihi Silfia Hanani Silvy Amelia Sinaga, Jorfri Boike Sinaga, Jorfri Boyke Siti Mujiatun Siti Nurul Rofiqo Irwan Sofia Edriati Sofiyah, Wan Sophian, Ali Sri Rahayu Budiani Sri Sukaesih Sry Rosita Subhi, Yazid Abdullah Subuh Tugiono, Subuh Sugiman Sugiman Suharso Suharso Suharto Linuwih Sujadi, A.A. Sukma Noor Akbar Sumarni Sumarni Supono Surya Agustian SUTRIONO SUTRIONO Suwanto Sanjaya Syarli, Syarli Tasnim Rahmat, Tasnim Titin Yulianti Triyadi, M Dico Tyasha Ayu Melynda Sari Uma, Yuli Choirul Vitriani, Yelfi Wahid Munawar Widiatama, Angga Jati Wiyanto - Yahya Mara Ardi Yani, Susmi Syahfrida Yogi, Muallim Supra Yosefa, Yessa Okta Yudianto Yudianto Yulian, Aji Muhammad Yuliani, Rika Yusma Indah Jayadi Yusra, Yusra Zainuddin, Ahmad Dennil Zakir, Supratman Zalwana, Hilya Zuhriyah, Indah Aminatus