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All Journal International Journal of Artificial Intelligence Research Indonesian Journal on Software Engineering (IJSE) JURNAL MEDIA INFORMATIKA BUDIDARMA JURNAL REKAYASA TEKNOLOGI INFORMASI Jurnal Kridatama Sains dan Teknologi JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Taroa : Jurnal Pengabdian Masyarakat Jurnal Sains, Nalar, dan Aplikasi Teknologi Informasi SEWAGATI: Jurnal Pengabdian Kepada Masyarakat RESLAJ: Religion Education Social Laa Roiba Journal Journal of Excellence Humanities and Religiosity Jurnal Penelitian, Pengabdian dan Pemberdayaan Masyarakat Jurnal Pengabdian kepada Masyarakat (PEMAS) Scientific: Journal of Computer Science and Informatics Journix: Journal of Informatics and Computing Indonesian Applied Research Computing and Informatics
Siti Mutmainah
Universitas Muhammadiyah Bima
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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PENINGKATAN KESADARAN DAN PARTISIPASI MASYARAKAT MELALUI PELATIHAN PENGELOLAAN SAMPAH Missouri, Randitha; Annafi, Nurfidianty; Lukman, Lukman; Khairunnas, Khairunnas; Mutmainah, Siti; Fathir, Fathir; Alamin, Zumhur
Taroa: Jurnal Pengabdian Masyarakat Vol 2 No 2 (2023): Juli
Publisher : LPPM IAI Muhammadiyah Bima

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52266/taroa.v2i2.2617

Abstract

Krisis pengelolaan sampah global membutuhkan solusi berkelanjutan yang melibatkan partisipasi masyarakat. Penelitian ini mengevaluasi dampak positif metode pelatihan berbasis masyarakat terhadap peningkatan kesadaran dan partisipasi dalam pengelolaan sampah. Kegiatan ini dilakukan di Kelurahan Mande, Kecamatan Mpunda, Kota Bima. Survei awal menunjukkan pemahaman dan partisipasi yang rendah, dengan hanya 40% responden memiliki pemahaman memadai. Setelah pelatihan, pemahaman meningkat signifikan menjadi 85%, menunjukkan efektivitas pelatihan dalam meningkatkan kesadaran masyarakat terkait pengelolaan sampah. Meskipun partisipasi di tingkat rumah tangga menunjukkan penurunan yang tidak signifikan, perubahan positif dalam praktik pengelolaan sampah dapat diukur dari hasil survei. Analisis kualitatif menyoroti perubahan sikap mendalam pada masyarakat, yang merespons pelatihan dengan menerapkan konsep-konsep pengelolaan sampah secara aktif. Evaluasi juga menegaskan pelatihan berhasil menciptakan keterlibatan masyarakat yang lebih luas di tingkat komunitas. Hasil survei menunjukkan peningkatan pesat dalam pemahaman dampak lingkungan pengelolaan sampah berkelanjutan (90%). Partisipasi dalam kegiatan komunitas terkait sampah melonjak dari 30% menjadi 80%, menunjukkan dampak pelatihan dalam merangsang keterlibatan masyarakat.
Persepsi Mahasiswa Jurusan Pendidikan Bahasa Arab Terhadap Tantangan dalam Memahami Pembelajaran Bahasa Arab di Universitas Muhammadiyah Bima Siti Mutmainah; Sri Wahyuningsih; Nurdiniawati
Reslaj: Religion Education Social Laa Roiba Journal Vol. 7 No. 5 (2025): RESLAJ: Religion Education Social Laa Roiba Journal
Publisher : Intitut Agama Islam Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/reslaj.v7i5.7724

Abstract

At Muhammadiyah Bima University, Arabic language learning faces various challenges, ranging from students' diverse levels of understanding, the availability of learning resources, to the teaching methods applied by lecturers. In this context, the diversity of students' level of understanding can be caused by differences in educational background before entering college, previous experience in learning Arabic, and how often they are exposed to Arabic-speaking environments. So this research aims to find out the perceptions of students majoring in Arabic Language Education towards the challenges in understanding Arabic language learning at Muhammadiyah Bima University. This research will be conducted at the University of Muhammadiyah Bima which is located on Jln. Anggrek No. 16 Nae Village, West Rasanae Sub-District, Bima City, West Nusa Tenggara. This research uses Qualitative Research with a Case Study Approach. Data collection techniques are observation, interview and documentation. Data Analysis Techniques are Data Reduction, Data Presentation and Conclusion Drawing. Based on the results of the study, it can be concluded that students of the Arabic Language Education Department at Muhammadiyah Bima University have various perceptions of the challenges they face in understanding Arabic language learning. Most students realize that learning Arabic has its own level of difficulty, especially in grammatical aspects (qawaid), vocabulary mastery (mufradat), and listening and speaking skills (istima' and kalam). This perception shapes students' attitudes in responding to the learning process, both in terms of learning motivation and the strategies used.
STRATEGI PENGEMBANGAN KARIER MAHASISWA ILMU KOMPUTER: MENENTUKAN PILIHAN KANTORAN, KERJA LEPAS, DAN WIRAUSAHA Mutmainah, Siti; Dahlan, Dahlan; Syarifuddin, Syarifuddin; Taufiqurahman, Taufiqurahman
Taroa: Jurnal Pengabdian Masyarakat Vol 5 No 1 (2026): Januari
Publisher : LPPM IAI Muhammadiyah Bima

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52266/taroa.v5i1.4545

Abstract

Kegiatan kuliah umum ini bertema “Kenali Potensi IT Anda: Temukan Jalur yang Tepat antara Kantoran, Freelance, atau Wirausaha” merupakan salah satu bagian dari pengabdian kepada masyarakat yang bertujuan untuk memberikan pemahaman kepada mahasiswa Ilmu Komputer mengenai berbagai jalur karier di bidang teknologi informasi. Kegiatan yang diselenggarakan oleh Program Studi Ilmu Komputer Universitas Muhammadiyah Bima dan diikuti oleh 110 mahasiswa ini menghadirkan dua pembicara dari kalangan akademisi dan praktisi IT. Beberapa materi yang disampaikan antara lain pengenalan profesi karier bidang IT, serta jalur pilihan kerja sebagai karyawan, freelancer, dan entrepreneur digital, berikut kelebihan dan tantangannya. Kegiatan berlangsung secara interaktif dengan melibatkan mahasiswa sebagai moderator dan pemateri, serta didampingi oleh dosen pendamping. Berdasarkan pengamatan, kegiatan ini meningkatkan pemahaman peserta mengenai karier di bidang TI dan mendorong refleksi diri terhadap potensi dan minat mahasiswa. Hasil pengabdian menunjukkan pentingnya sinergi antara kampus dan dunia industri dalam mempersiapkan lulusan yang adaptif dan kompeten. Kegiatan ini diharapkan dapat menjadi langkah awal dalam membangun strategi pengembangan karier mahasiswa yang lebih terarah.
Pelatihan Penulisan Proposal Skripsi Dan Tips Penggunaan Aplikasi Mendeley Mutmainah, Siti; Ansor Lorosae, Teguh; Fathir, Fathir
Jurnal Penelitian, Pengabdian dan Pemberdayaan Masyarakat Vol. 3 No. 1 (2026): Jurnal Penelitian, Pengabdian dan Pemberdayaan Masyarakat (JP3M)
Publisher : Yayasan Assyifa Assyaka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71301/jp3m.v3i1.197

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kemampuan mahasiswa dalam menulis proposal skripsi secara sistematis serta memberikan pemahaman dan keterampilan dalam penggunaan aplikasi Mendeley sebagai alat manajemen referensi. Permasalahan yang dihadapi mahasiswa antara lain rendahnya pemahaman terhadap struktur penulisan proposal skripsi dan kurangnya kemampuan dalam mengelola sitasi serta daftar pustaka secara benar. Metode yang digunakan dalam kegiatan ini adalah pelatihan dan pendampingan yang dilaksanakan melalui penyampaian materi, praktik langsung, serta diskusi interaktif. Subjek kegiatan adalah mahasiswa Universitas Muhammadiyah Bima yang sedang atau akan menyusun proposal skripsi. Hasil kegiatan menunjukkan adanya peningkatan pemahaman mahasiswa terhadap sistematika penulisan proposal skripsi serta kemampuan dalam menggunakan aplikasi Mendeley untuk pengelolaan referensi. Pelatihan ini memberikan dampak positif dalam meningkatkan kesiapan mahasiswa dalam menyusun proposal skripsi yang sesuai dengan kaidah penulisan ilmiah dan etika akademik.
Improving the Accuracy of Social Media Sentiment Classification with the Combination of TF-IDF Method and Random Forest Algorithm Siti Mutmainah; Fathir; Erin Eka Citra
Journix: Journal of Informatics and Computing Vol. 1 No. 1 (2025): April
Publisher : Ran Edu Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63866/journix.v1i1.2

Abstract

Sentiment classification on social media text data is one of the main challenges in public opinion analysis. The large volume of data and the diversity of informal languages make sentiment analysis a challenge in itself, especially in the context of Indonesian. This research aims to improve the accuracy of social media sentiment classification by combining Term Frequency-Inverse Document Frequency (TF-IDF) method as a text representation technique and Random Forest algorithm as a classification model. The dataset used consists of 20,000 Indonesian opinion data collected from Twitter and Instagram, and has been labeled into three sentiment categories: positive, negative, and neutral. This data went through a preprocessing stage, including text cleaning, tokenization, stopword removal, stemming, and normalization. Experimental results show that the combination of TF-IDF and Random Forest yields an accuracy of 91.2% with average precision, recall, and F1-score values above 0.90. The confusion matrix analysis revealed that the model was highly effective in classifying positive and negative sentiments, although there were challenges in distinguishing neutral sentiments. These findings indicate that the approach used is quite reliable and can be used as a foundation for the development of sentiment analysis systems on an industrial scale as well as further research.
Genetic Algorithm Optimization for Solving the Traveling Salesman Problem in the Indonesian Business Environment Siti Mutmainah; Teguh Ansyor Lorosae; Erin Eka Citra
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.v1i2.14

Abstract

The Traveling Salesman Problem (TSP) is one of the combinatorial optimization problems that is highly relevant in distribution and logistics route planning. This study aims to optimize the Genetic Algorithm (GA) for solving TSP in the Indonesian business environment, which has complex geographical characteristics and diverse logistics infrastructure. The proposed approach combines dynamic parameter adaptation and regional clustering to improve convergence efficiency and solution quality. Experiments were conducted on the distribution route data of an Indonesian logistics company with three scenarios: conventional GA, adaptive GA, and clustering-based GA. Performance evaluation was based on total travel distance, computation time, solution stability, and convergence rate. The results show that adaptive AG produces the best performance, with a reduction in total travel distance of up to 20% more efficient, faster convergence time (95 iterations compared to 120 iterations in conventional AG), and solution stability reaching 90.6%. These findings indicate that parameter adaptation in AG can significantly improve the effectiveness of TSP optimization in the Indonesian business context. The contribution of this research not only strengthens the development of adaptive metaheuristic algorithms but also provides practical benefits for the logistics industry in designing more efficient, cost-effective, and sustainable distribution routes.
Multi-Scale Convolutional Neural Network-Based Classification of Tuberculosis Chest X-ray Images M Ridwan; syafrudin _; Sahrul Fauzan Djiaulhaq; Siti Mutmainah; Teguh Ansyor Lorosae
Indonesian Applied Research Computing and Informatics Vol. 1 No. 2: December (2025)
Publisher : PT. Teras Digital Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64479/iarci.v1i2.60

Abstract

Tuberculosis (TB) is an infectious disease caused by the bacterium Mycobacterium tuberculosis, which mainly attacks the lung organs. One of the most commonly used methods of TB diagnosis is thorax X-ray imaging. The images of the examination results are visually analyzed by medical personnel to identify certain patterns or characteristics that indicate TB disease. However, the manual analysis process takes time and depends on the doctor's experience. Therefore, this study utilizes Artificial Intelligence (AI) technology as a diagnostic tool to provide alternative solutions that are faster and more efficient in determining TB status in patients. This study proposes the use of the Multi-Scale Convolutional Neural Network (CNN) method to classify tuberculosis disease based on thorax X-ray images. The data used was in the form of lung X-ray images that acted as inputs at the image processing stage. The dataset collected consisted of 790 images divided into two classes, namely normal lungs and lungs indicated by tuberculosis. The CNN architecture includes three convolutional layers with a kernel size of 3×3, three max pooling layers  of 2×2, and one fully connected layer with a softmax activation function. Each convolutional layer uses 128 filters, and the model learning process is optimized using the Adam Optimizer algorithm. The training process was carried out for 15 epochs and resulted in an accuracy rate of 81%. Furthermore, at the model evaluation stage, an accuracy of 79% was obtained, indicating that the proposed method has sufficient performance in classifying tuberculosis disease.
MobileNetV2 Transfer Learning Implementation for Waste Classification Fifi Andriani; Ade Yuliati; Anis Yaturahmah; Siti Mutmainah
Indonesian Applied Research Computing and Informatics Vol. 1 No. 2: December (2025)
Publisher : PT. Teras Digital Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64479/iarci.v1i2.62

Abstract

Waste management issues represent one of the major challenges in maintaining environmental sustainability, as the waste sorting process is still largely performed manually, requiring significant time and effort and relying heavily on human accuracy, which makes it inefficient and prone to errors. Therefore, this study utilizes Artificial Intelligence (AI) technology as a solution to support more effective and sustainable environmental management by proposing the use of the Convolutional Neural Network (CNN) algorithm to classify waste types based on digital images. The data used consist of waste images as inputs in the image processing stage, which are then classified into several waste categories. The CNN architecture applied consists of multiple convolutional layers with a kernel size of 3×3, max pooling layers for feature extraction, and a fully connected layer with a softmax activation function to determine the output class, while the model training process is optimized using the Adam Optimizer algorithm. The experimental results demonstrate that the proposed CNN model is capable of classifying waste types with a good level of accuracy, indicating that this AI-based approach can serve as an effective supporting solution for intelligent, efficient, and sustainable waste management systems and contribute to environmental conservation efforts.
Co-Authors Ade Yuliati Anas Satria Anis Yaturahmah Ansor Lorosae, Teguh Citra, Erin Eka Dahlan Dhomas Hatta Fudholi Dikan , Noval Erin Eka Citra Erin Eka Citra Fathir Fathir Fathir Fifi Andriani Fudholi, Dhomas Hatta Ghufran, Syed Muhammad Hayaty, Mardhiya Khairunnas, Khairunnas Khairunnisa LUKMAN, LUKMAN M Ridwan M. Fikram Miftahul Jannah Muhammad Akbar Muhammad Amirul Mu'min Muhammad Hayun Nur Hunul Khatimah Nurdiniawati Nurfadila Nurfidianty Annafi, Nurfidianty Patryansya , Yoga Purwoko, Agus Ramadhan, Sahrul Randitha Missouri Rizki, Afsa Sabar Aritonang Rajagukguk Sahrul Fauzan Djiaulhaq Sahrul Ramadhan Saifullah Setiawan, Muhammad Iwan Sri Wahyuningsih Sutriawan syafrudin _ Syarifuddin Syarifuddin Sya’Ban, Ahmad Taufiqurahman, Taufiqurahman Teguh Ansyor Lorosae Tri Stiyo Famuji Widayati, Ulfa Yuliyanti yuliyanti Zumhur Alamin