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PENINGKATAN PEMAHAMAN MANAJEMEN KRISIS BERBASIS AL-QUR’AN MELALUI KAJIAN TAFSIR TEMATIK DI MASJID NURUL HUDA CIKARANG BARAT Aceng Badruzzaman; Kisanda Midisen; Ermanto
Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Vol. 3 No. 3 (2025): Juni
Publisher : CV. Alina

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59407/jpki2.v3i3.2438

Pengabdian kepada masyarakat ini bertujuan untuk meningkatkan pemahaman masyarakat tentang manajemen krisis dari perspektif Al-Qur'an melalui kajian tafsir tematik. Kajian ini dilaksanakan di Masjid Jamia Nurul Huda, Kelurahan Bojongkoneng, Cikarang Barat, dengan pendekatan partisipatif berbasis masyarakat. Metode yang digunakan meliputi observasi, wawancara dengan tokoh agama, dan diskusi kelompok terfokus dengan masyarakat setempat. Hasil kajian menunjukkan bahwa melalui pendekatan tafsir tematik, masyarakat lebih memahami ayat-ayat Al-Qur'an yang relevan dengan manajemen krisis, seperti prinsip kesabaran, strategi menghadapi kesulitan, dan pentingnya kesiapsiagaan menghadapi keadaan darurat. Kajian ini juga membantu membangun kesadaran kolektif tentang pentingnya perencanaan dan mitigasi krisis berbasis nilai-nilai Islam. Peningkatan pemahaman ini berkontribusi dalam memperkuat ketahanan sosial dan spiritual masyarakat dalam menghadapi berbagai tantangan hidup. Dengan kajian ini, diharapkan metode serupa dapat diterapkan di berbagai komunitas lain guna memperluas manfaatnya dalam konteks pemberdayaan masyarakat berbasis nilai-nilai Islam.

L1 Interference in Students’ Translations: A Corpus-Based Analysis of Collocation Errors and Pedagogical Implications Ardi, Havid; Ermanto; Juita, Novia; Rany, Vy
International Journal of Language Pedagogy Vol. 5 No. 1 (2025)
Publisher : Language Pedagogy Study Program, Faculty of Languages and Arts, Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ijolp.v5i1.113

Collocation is challenging for translators as the words differ across languages. This study examines collocation errors in translations produced by English Department students who took the Indonesian-English Translations subject. The text discussed the Minangkabau tradition written in Indonesian. Employing a corpus-based approach, the research analyzes students' translations to identify recurring collocational mismatches, classify error types, and first-language (L1) interference in English as an L2, which is studied in terms of the insufficient mastery of English phraseology. The translations made by English Department students were compiled from student submissions and compared against reference corpora (e.g., COCA, BNC) as natural collocations. Tools such as AntConc and Kortara were used to quantify deviations and categorize errors into four primary types: (1) verb-noun, (2) adjective-noun mismatches, (3) unnatural noun-noun phrases, (4) adverb-adjective, (5) verb-preposition, and (6) clause base. Findings reveal that 58.94% of errors arise from noun-noun combinations, where students applied Indonesian syntactic or lexical patterns to English, resulting in unnatural collocations. The study highlights the pedagogical need for explicit collocation instruction in translation training, especially for language pairs with significant structural and cultural differences. It advocates for incorporating corpus tools into classrooms to enhance students’ awareness of natural collocations and reduce L1 interference.

Prinsip-Prinsip dan Strategi Dakwah Islamiyah dalam Konteks Kontemporer Aceng Badruzzaman; Ermanto
Da'watuna: Journal of Communication and Islamic Broadcasting Vol. 5 No. 3 (2025): Da'watuna: Journal of Communication and Islamic Broadcasting
Publisher : Intitut Agama Islam Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/dawatuna.v5i3.7804

This article examines Islamic da'wah's principles and strategies in a contemporary context, with a focus on the relevance and adaptability of da'wah methods to modern-day challenges. In the era of rapid globalization and information technology, Islamic da'wah requires an innovative and contextual approach to achieve optimal effectiveness. This research uses a qualitative approach with literature analysis and case studies of several successful da'wah movements. The research results show that the basic principles of da'wah, such as sincerity, patience, and wisdom, remain the main foundation. However, da'wah strategies need to be adapted to utilize digital technology, social media, and interreligious dialogue. In addition, research has shown that inclusive da'wah, focused on socio-economic solutions for society, effectively engages people and encourages their participation. Thus, this article makes an important contribution to enriching the Islamic da'wah literature and offers practical guidance for preachers in conveying the Islamic message more effectively in the contemporary era.

Perbandingan Metode Klasifikasi dalam Memprediksi Penyakit Ginjal Kronis Ermanto; Surojudin, Nurhadi
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 3 (September 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i3.1263

Chronic Kidney Disease (CKD) is a global health issue with an increasing prevalence that poses a significant economic burden on healthcare systems. Early detection of CKD is crucial to provide proper treatment before the disease progresses to end-stage renal failure. With technological advancements, machine learning methods have been widely utilized to support medical diagnosis with greater speed and accuracy. This study aims to compare the performance of two popular classification algorithms, Decision Tree C4.5 and Naïve Bayes, in predicting CKD using a public dataset from the UCI Machine Learning Repository consisting of 400 patient records with 24 clinical attributes. The research process involved systematic preprocessing steps, including handling missing values, transforming categorical data into numerical form, and selecting relevant attributes. Model evaluation was conducted using 10-Fold Cross Validation with performance metrics such as accuracy, precision, recall, Area Under the Curve (AUC), and statistical T-Test. The results show that Decision Tree C4.5 achieved an accuracy of 93.00%, precision of 84.27%, recall of 100%, and an AUC of 0.944, while Naïve Bayes obtained an accuracy of 93.50%, precision of 85.23%, recall of 100%, and an AUC of 0.948. Although the performance differences between both algorithms are relatively small and statistically insignificant, Naïve Bayes demonstrated slightly better results in terms of accuracy and AUC, while Decision Tree C4.5 offers advantages in interpretability through its classification rules. In conclusion, both algorithms are effective for early CKD diagnosis, and the choice may depend on practical needs, whether emphasizing interpretability or computational efficiency. This study contributes to the development of more accurate and efficient clinical decision support systems for improving healthcare services in CKD management.

Perbandingan Metode Klasifikasi dalam Memprediksi Penyakit Ginjal Kronis Ermanto; Surojudin, Nurhadi
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 3 (September 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i3.1263

Chronic Kidney Disease (CKD) is a global health issue with an increasing prevalence that poses a significant economic burden on healthcare systems. Early detection of CKD is crucial to provide proper treatment before the disease progresses to end-stage renal failure. With technological advancements, machine learning methods have been widely utilized to support medical diagnosis with greater speed and accuracy. This study aims to compare the performance of two popular classification algorithms, Decision Tree C4.5 and Naïve Bayes, in predicting CKD using a public dataset from the UCI Machine Learning Repository consisting of 400 patient records with 24 clinical attributes. The research process involved systematic preprocessing steps, including handling missing values, transforming categorical data into numerical form, and selecting relevant attributes. Model evaluation was conducted using 10-Fold Cross Validation with performance metrics such as accuracy, precision, recall, Area Under the Curve (AUC), and statistical T-Test. The results show that Decision Tree C4.5 achieved an accuracy of 93.00%, precision of 84.27%, recall of 100%, and an AUC of 0.944, while Naïve Bayes obtained an accuracy of 93.50%, precision of 85.23%, recall of 100%, and an AUC of 0.948. Although the performance differences between both algorithms are relatively small and statistically insignificant, Naïve Bayes demonstrated slightly better results in terms of accuracy and AUC, while Decision Tree C4.5 offers advantages in interpretability through its classification rules. In conclusion, both algorithms are effective for early CKD diagnosis, and the choice may depend on practical needs, whether emphasizing interpretability or computational efficiency. This study contributes to the development of more accurate and efficient clinical decision support systems for improving healthcare services in CKD management.

Analisis Pola Pengangguran Menggunakan Metode Clustering Algoritma K-Means Di Wilayah Kabupaten Cirebon Misbakhul Anam; Annisa Maulana Majid; Ermanto
Jurnal Teknologi dan Manajemen Industri Terapan Vol. 4 No. 4 (2025): Jurnal Teknologi dan Manajemen Industri Terapan
Publisher : Yayasan Inovasi Kemajuan Intelektual

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55826/jtmit.v4i4.743

Pengangguran merupakan salah satu permasalahan sosial dan ekonomi yang dihadapi oleh banyak daerah di Indonesia, termasuk salah satunya di wilayah Kabupaten Cirebon. Penelitian ini bertujuan untuk mengidentifikasi dan menganalisa lebih dalam terkait pola pengangguran di wilayah Kabupaten Cirebon pada tingkat Kecamatan menggunakan teknik clustering algoritma K-Means yang dipadukan dengan aplikasi RapidMiner. Data penelitian terkait pola pengangguran diperoleh dari Dinas Ketenagakerjaan Kabupaten Cirebon periode tahun terbaru yakni tahun 2024, yang meliputi data riwayat pencari kerja seperti Latar Belakang Pendidikan dari terendah sampai tertinggi (SD-S1), Jenis Kelamin, Alamat, serta data jumlah Penyerapan Angkatan Kerja Perusahaan berdasarkan Kecamatan. Hasil 3 cluster dengan kategori Pola Pengangguran Tinggi, Pengangguran Rendah, dan Pengangguran Sedang, dipilih sebagai hasil final dalam penelitian ini dengan nilai evaluasi DBI 0.063 yang menunjukan hasil kualitas clustering mendapatkan nilai yang sangat baik. Visualisasi grafik dan pemetaan wilayah menggunakan ArcGIS pada penelitian ini bertujuan untuk mempermudah dalam memberikan rekomendasi bagi pemerintah daerah, khususnya Dinas Ketenagakerjaan Kabupaten Cirebon, dalam merancang program dan kebijakan yang lebih tepat sasaran dan terstruktur untuk menanggulangi indikasi pola pengangguran yang ada di wilayah Kecamatan Kabupaten Cirebon berbasis data.

A Design of Learning Activities That Created Students' Self-Regulated Learning through LMS Moodle Usman, Estika Satriani; Zaim, M.; Ermanto; Walpita, Chandima Kumara; Etfita, Fauzul
International Journal of Language Pedagogy Vol. 4 No. 2 (2024)
Publisher : Language Pedagogy Study Program, Faculty of Languages and Arts, Universitas Negeri Padang, Indonesia

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

Current Learning systems have enabled students to construct their knowledge by themselves. However, using various LMS will cause different learning situations and experiences for students in learning. This study investigates the effectiveness of Moodle-based learning activities in fostering self-regulated learning (SRL) among undergraduate students. The research was conducted over 8 weeks with 100 participants, employing a mixed-methods approach that included pre-and post-surveys, learning analytics, and qualitative data from focus groups and interviews. The findings reveal significant improvements in key SRL components: goal setting, self-monitoring, self-evaluation, and time management. Quantitative data from the Motivated Strategies for Learning Questionnaire (MSLQ) showed statistically significant gains across all SRL dimensions (p < 0.01). Learning analytics indicated that student engagement increased, reflected in doubled login frequency, a 33.3% rise in task completion rates, and a 66.7% increase in time spent on learning tasks. Qualitative data supported these results, highlighting the positive impact of Moodle’s tools on students' autonomy, motivation, and reflective learning practices. The study concludes that Moodle-based activities can effectively promote SRL by providing structured, interactive, and reflective learning experiences. Recommendations are made for educators to integrate diverse Moodle activities that target different SRL components and for institutions to provide continuous support and infrastructure improvements.

The Optimization of Budget Absorption in the Use of General Allocation Funds (DAU) for the Health Sector in Bengkalis Regency Hafizhah Maulia; Ermanto; Jasrida Yunita
JURNAL KESMAS DAN GIZI (JKG) Vol. 8 No. 1 (2025): Jurnal Kesmas dan Gizi (JKG)
Publisher : Fakultas Kesehatan Masyarakat Institut Kesehatan Medistra Lubuk Pakam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35451/57ctme05

This study aims to identify and analyze the factors influencing the low absorption rate of the General Allocation Fund (DAU) for the health sector by the Bengkalis Regency Health Office in 2024. The research employed a qualitative approach using data collection methods such as direct observation, interviews, and document analysis. Data were analyzed using a Fishbone diagram to identify root causes, the USG (Urgency, Seriousness, Growth) method to determine problem priorities, and the Delphi method to formulate solutions. The findings revealed that by the third quarter of 2024, DAU absorption was only 58%, far below the target. The main issues included poor inter-sectoral coordination, administrative delays, and limited human resource capacity. Proposed strategies include developing SOPs, establishing cross-sectoral teams, and implementing technology-based monitoring systems to enhance efficiency, transparency, and accountability. This study provides practical recommendations for optimizing DAU absorption to support better public health services.

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