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All Journal Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Jurnal Media Wahana Ekonomika Hasanuddin Economics and Business Review BALANCE Jurnal Akuntansi dan Bisnis Jurnal Ilmiah Edunomika (JIE) Jurnal Akuntansi dan Keuangan Journal of Applied Data Sciences International Journal of Accounting & Finance in Asia Pasific Journal of Management Studies and Development Kajian Akuntansi Balance : Jurnal Akuntansi dan Bisnis Jurnal Ekonomi Mengabdi
Muhammad Fahmi
Universitas Muhammadiyah Palembang
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Industrial & Manufacturing Engineering Social Sciences Other

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Early Mental Health Detection with Machine Learning : A Practical Approach to Model Development and Implementation Hermawan, Latius; Syakurah, Rizma Adlia; Meilinda, Meilinda; Stiawan, Deris; Negara, Edi Surya; Ramayanti, Indri; Fahmi, Muhammad; Rizqie, Muhammad Qurhanul; Hermanto, Dedy
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 13, No 2: June 2025
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v13i2.6111

Abstract

Academic pressures, lifestyle changes, and socio-economic factors significantly impact mental health, a critical determinant of academic success and well-being. Early detection and intervention are crucial to mitigate severe outcomes like academic underperformance and suicidal tendencies. Leveraging tools like the DASS-42, this study examines mental health patterns using Support Vector Machine (SVM) models, achieving accuracies of 88% for depression, 71% for stress, and 57% for anxiety. While the model excels in identifying "Normal" cases, its performance for "Mild," "Moderate," and "Severe" cases highlights limitations due to class imbalance and feature representation. The findings reveal that anxiety is the most volatile and severe condition, with peaks in 2018 and 2022, while stress remains manageable and depression moderately stable. Gender and program-specific differences emphasize the need for tailored interventions. Addressing challenges related to data quality, algorithmic transparency, and ethical concerns is essential for real-world applications. This study highlights the potential of machine learning in early detection and intervention for mental health issues. Future research should explore advanced feature engineering techniques and develop more interpretable models to enhance clinical decision-making.
Peran Big Money dalam Pasar Modal Indonesia: Analisis Dampak terhadap Likuiditas, Harga Saham, dan Arah Sentimen Pasar Muhammad Fahmi; Gumulya Sonny Marcel Kusuma; Muhammad Faris Afif; Junyka Widiyanti
Balance : Jurnal Akuntansi dan Bisnis Vol. 10 No. 2 (2025): Balance : Jurnal Akuntansi dan Bisnis
Publisher : Universitas Muhammadiyah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32502/balance.v10i2.989

Abstract

The main objective of this study is to analyze the role of Big Money in the Indonesian capital market. Specifically, the objectives of this study are to analyze the characteristics and behavior of Big Money in the Indonesian capital market, examine the impact of Big Money on Indonesian capital market liquidity, and identify the influence of Big Money on stock price movements in the Indonesian capital market. Secondary data from 2001-2024 was used. Data collection techniques were web scraping, observation, documentation, and literature review. The study found that Big Money plays a significant role in increasing liquidity through high trading volumes, but also triggers sharp fluctuations and volatility in stock prices, risking negatively impacting retail investors. Furthermore, big data-based fintech applications enable more accurate market predictions, creating an imbalance in access to information between large and small investors. This study emphasizes the importance of strict regulations to control the impact of Big Money in order to maintain market balance and protect all parties involved.
PENDAMPINGAN PENYUSUNAN DOKUMEN PENDUKUNG PENDAFTARAN BADAN HUKUM BADAN USAHA MILIK DESA AL-IKHLAS DESA MERANJAT II INDRALAYA SELATAN Muhammad Fahmi; Anggrelia Afrida; Efrina Masdaini; Rosalina Ghozali; Kholillah
Jurnal Ekonomi Mengabdi Vol 2 No 1: Jurnal Ekonomi Mengabdi - Publish April 2023
Publisher : Universitas Tridinanti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52333/jem.v2i1.115

Abstract

Penyusunan dokumen pendukung pendaftaran Badan Hukum Badan Usaha Milik Desa Al-Ikhlas Desa Meranjat II Indralaya Selatan mulai dari kelengkapan dokumen, sumberdaya manusia, pengetahuan terhadap informasi dan faktor lainnya. Tujuan dari pengabdian ini yaitu proses pendaftaran BUMDes mulai dari penyusunan dokumen sampai dengan pengiriman dokumen ke kemendesa.go.id. Pendampingan yang dilakukan yaitu (1) observasi mitra pengabdian (2) persiapan sarana dan prasarana pendampingan (3) pendampingan penyusunan dokumen BUMDes (4) pendampingan proses pendaftaran badan hukum BUMDes. Kegiatan ini telah meningkatkan pengetahuan dan keterampilan pengurus BUMDesa dalam hal penyusunan dokumen sehingga mempermudah proses pendaftaran Badan Hukum BUMDes
THE ANALYSIS OF CREDIT FINANCING OF HOME OWNERSHIP WITH MURABAHAH AT PT. BANK SYARIAH MANDIRI PALEMBANG Muhammad Fahmi; Poppy Febrina
Hasanuddin Economics and Business Review VOLUME 2 NUMBER 3, 2019
Publisher : Faculty of Economics and Business, Hasanuddin University, Makassar, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26487/hebr.v2i3.1547

Abstract

The purpose of this study was to find out whether the housing loan financing (mortgage) at Bank Syariah Mandiri Palembang Branch in accordance with murabaha and to know the process of granting mortgage with murabahah scheme in Bank Syariah Mandiri Branch Palembang to prospective recipients of financing. The research method used was descriptive method that was by collecting the data obtained and then interpret and analyze so as to provide information that can be used to solve the problems encountered. The data used were primary data and secondary data. The results of this study indicate mortgage loans at PT. Bank Syariah Mandiri has been in accordance with the murabahah financing agreement and analysis on PSAK No. 102 concerning Murabahah as the basis of consideration of the Conformity of House Ownership Credit at Bank Syariah Mandiri Palembang Branch Office.
Internal Auditor Performance: Audit Structure, Compensation, Recommendation Quality, OCB, and Role Conflict Ida Zuraida; Betri; Muhammad Fahmi; Frizki Danu Rakhmat
Journal of Management Studies and Development Vol. 5 No. 02 (2026): Journal of Management Studies and Development
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/IISTR.jmsd.002444

Abstract

Internal auditor performance plays a crucial role in strengthening corporate governance, internal control, and risk management within banking institutions. However, empirical evidence regarding the influence of audit structure, compensation, recommendation quality, OCB, and the moderating role of role conflict remains inconsistent. This study aims to examine the effects of audit structure, compensation, recommendation quality, and OCB on internal auditor performance, as well as the moderating effect of role conflict. A quantitative survey was conducted involving internal auditors from state-owned and regional-owned banks in Palembang City. Of the 117 distributed questionnaires, 58 valid responses were analyzed using multiple linear regression and MRA. The results indicate that audit structure, compensation, recommendation quality, and OCB simultaneously have a significant effect on internal auditor performance. Individually, OCB positively and significantly influences internal auditor performance, whereas audit structure and compensation show positive but insignificant effects, and recommendation quality has a negative but insignificant effect. Furthermore, role conflict does not significantly moderate the relationships between the independent variables and internal auditor performance. These findings highlight the importance of fostering extra-role behavior to enhance internal auditor performance beyond structural and financial aspects. The study contributes to the literature on internal auditing by providing empirical evidence from the Indonesian banking sector and offers practical implications for bank management in developing strategies to strengthen auditor performance through organizational support and OCB. Future studies are recommended to include broader samples and additional organizational and behavioral variables.
Sentiment and Emotion Classification Model Using Hybrid Textual and Numerical Features: A Case Study of Mental Health Counseling Indri Ramayanti; Latius Hermawan; Rizma Adlia Syakurah; Deris Stiawan; Meilinda Meilinda; Edi Surya Negara; Muhammad Fahmi; Ahmad Ghiffari; Muhammad Qurhanul Rizqie
Journal of Applied Data Sciences Vol 6, No 3: September 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i3.632

Abstract

Mental health issues among individuals, particularly in counseling contexts, require practical tools to understand and address emotional states. This study explores the application of machine learning models for emotion detection in mental health counseling conversations, focusing on four algorithms: Bernoulli Naive Bayes, Decision Tree, Logistic Regression, and Random Forest. The dataset, derived from transcribed counseling sessions, underwent preprocessing, including stemming, stopword removal, and TF-IDF vectorization to create structured inputs for classification. Emotional categories such as "Depresi" (Depression), "Kecewa" (Dissapointed), "Senang" (Happy), "Bingung" (Confused) and "Stres" (Stress) were analyzed to evaluate model performance. Results indicated that Logistic Regression achieved the highest accuracy at 82%, showcasing its reliability and scalability, followed closely by Random Forest with 81%, demonstrating robustness in handling complex data structures. Bernoulli Naive Bayes performed competitively at 80%, excelling in computational efficiency, while Decision Tree recorded the lowest accuracy at 70%, reflecting its limitations in managing overlapping features and high-dimensional data. These findings highlight the potential of machine learning in addressing the increasing demand for scalable mental health support tools. The study underscores the importance of model selection, balanced datasets, and feature engineering to improve classification accuracy. Future work includes developing AI-driven chatbots for real-time emotion detection and integrating multimodal data to enhance interpretability. This research contributes to advancing automated solutions for mental health care, offering new pathways for timely and personalized interventions.
Determinants of Government Financial Performance: An SDGs-Based Analysis of Revenue and Industrial Value Added Welly Welly; Muhammad Fahmi; Muhammad Orba Kurniawan; Nanda Adeliyanti
International Journal of Accounting and Finance in Asia Pasific (IJAFAP) Vol 9, No 3 (2026): October 2026
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/ijafap.v9i3.4779

Abstract

Government financial performance is important for fiscal capacity and sustainable regional development, particularly where revenue mobilization and industrial contributions vary across provinces. This study examines the association of government revenue relative to gross domestic product (GDP) and industrial value added with government financial performance across Indonesian provinces within the Sustainable Development Goals (SDGs) framework. Using a quantitative approach, the study analyzes 170 province-year observations from 2019–2023 using panel data regression analysis. Government financial performance is proxied by the regional financial independence ratio, while the explanatory variables are government revenue-to-GDP and manufacturing value added-to-GDP. The results show that government revenue and industrial value added are positively associated with government financial performance (B = 46.962, p 0.001; B = 2.312, p 0.001), with industrial value added having the larger standardized coefficient (b = 0.446 vs. b = 0.271). The model reports R² = 0.191 and adjusted R² = 0.181. These findings highlight the potential importance of domestic resource mobilization and productive industrial capacity for subnational fiscal resilience in Indonesia.
Co-Authors Afrida, Anggrelia Ahmad Ghiffari Arta Pradana Ayassy, Naufal Rafi Dedy Hermanto Deris Stiawan Edi Surya Negara Efrina Masdaini Fauziah, Alfina Damayanti Frizki Danu Rakhmat Ghazali, Rosalina Gumulya Sonny Marcel Kusuma Hairani Hairani Ida Zuraida Ida Zuraidah Indri Ramayanti Junyka Widiyanti Katiallo, Taufik Kholillah Kurnia Krisna Hari Ladewi, Yuhanis Latius Hermawan Latius Hermawan Meilinda Meilinda Meilinda Meilinda Meilinda, Meilinda Muhammad Faris Afif Muhammad Orba Kurniawan Muhammad Qurhanul Rizqie Nanda Adeliyanti Negara, Edi Surya Poppy Febrina Punawan, Herry Rizma Adlia Syakurah Rizqie, Muhammad Qurhanul Rosalina Ghozali Sirajuddin, Betri Sunardi Syakurah, Rizma Adlia Welly, Welly Yulian Sahri