Abstract:Abstract: The re-occurrence of the ship accident while sailing in Toba Lake shows that the operational standard procedure (SOP) on safety and security issues, which are then followed by affordable cost aspects, speed and…
timeliness, and convenience aspects have not been implemented effectively and maximally. Therefore the proponent team from the Indonesian Maritime Academy College in Medan proposed community service activities in the form of training and mentoring for target partners to provide scientific education along with the assistance of partner education facilities. The results of this activity are published in scientific journals, electronic mass media. In addition, the activity videos and the improvement of the knowledge and skills of partner HR are outcomes of this activity. The lecture and demonstration methods used in the process provide an understanding of the use of shipping safety equipment. The practice method is directly used to skill in using shipping safety equipment, of course, with the assistance of the proposing team. Observation method is done to observe the ability of partners both during the activity process and afterwards. Observation after the activity is intended to determine the impact of the activities that have been carried out.
Keywords: standard operating procedures, Toba lake, shipping safety equipment
Abstrak: Terjadinya kembali musibah kecelakaan kapal saat berlayar di Danau Toba menunjukkan bahwa standar operasional prosedur (SOP) persoalan keselamatan dan keamanan, yang selanjutnya baru diikuti dengan aspek biaya yang terjangkau, kecepatan dan ketepatan waktu, serta aspek kenyamanan belum dilaksanakan secara efektif dan maksimal. Oleh sebab itu tim pengusul yang berasal dari Perguruan Tinggi Akademi Maritim Indonesia Medan mengusulkan kegiatan pengabdian kepada masyarakat dalam bentuk pelatihan dan pendampingan terhadap mitra sasaran untuk memberikan edukasi ilmiah disertai dengan adanya bantuan sarana edukasi mitra. Hasil dari kegiatan ini dipublikasikan di jurnal ilmiah, media massa elektronik. Selain itu video kegiatan serta peningkatan pengetahuan dan keterampilan SDM mitra merupakan luaran dari kegiatan ini. Metode ceramah dan demonstrasi digunakan dalam proses memberikan pemahaman mengenai penggunaan peralatan keselamatan pelayaran. Metode praktik langsung digunakan untuk keterampilan menggunakan peralatan keselamatan pelayaran tentunya dengan pendampingan tim pengusul. Metode observasi dilakukan untuk mengamati kemampuan mitra baik selama proses kegiatan maupun sesudahnya. Evaluasi sesudah kegiatan ditujukan untuk mengetahui dampak dari kegiatan yang telah dilaksanakan.
Kata kunci: standar operasional prosedur, danau toba, peralatan keselamatan pelayaran
Abstract:Some housewives in Batam City do not work, relying solely on income from their husbands. During this time, housewives use their free time to socialize and have a good time with their neighbors without producing anything…
useful, so it's time to take advantage of these habits in order to produce something to support their family's economy. In order for income housewives to have new knowledge and abilities, crafting activities are carried out by using patchwork. This training is carried out to use patchwork to have more selling value such as hijab accessories. This training was carried out twice, which was given the understanding of housewives about the use of patchwork and then given the practice of learning by doing. In the implementation of the service carried out by practicing directly how to make a brooch with several models of patchwork. Aside from the guidance of making brooches from patchwork, researchers also provide assistance in managing financial management, so that in the future it can be used as a home business that can help support the family's economy. From the results of the evaluation at the service of the mothers, thousands of households have been able to make patchwork brooches with several variations and models
Abstract:Abstract: Community service aims to provide partners with the skills and knowledge to utilize tofu liquid waste to be organic fertilizer and provide assistance in making chimney smoke. This activity uses continuous training…
ing and mentoring methods to achieve the target of the solutions offered. During the activity the participants followed very enthusiastically and were committed to developing the production of organic fertilizer from liquid waste knowing to be a side business and a superior village product. In addition, smoke puffs which become a social problem for residents around the tofu industry have been handled by making chimneys.
Keywords: environmental pollution, liquid waste, tofu industry
Abstrak: Pengabdian kepada masyarakat ini bertujuan untuk memberikan keterampilan dan pengetahuan kepada mitra untuk memanfaatkan limbah cair tahu menjadi pupuk organik dan memberikan pendampingan pembuatan asap cerobong. Kegiatan ini dengan menggunakan metode pelatihan dan pendampingan berkesinambungan sehingga tercapai target dari solusi yang ditawarkan. Selama kegiatan berlangsung peserta mengikuti sangat antusian dan berkomitmen untuk mengembangkan produksi pupuk organik dari limbah cair tahu mejadi usaha sampingan dan produk unggulan desa. Selain itu kepulan asap yang menjadi masalah sosial warga sekitar industri tahu telah tertangani dengan dibuatnya cerobong asap.
Kata kunci : pencemaran lingkungan, limbah cair, industri tahu
Abstract:Abstract: Anomalous sound detection is essential for industrial predictive maintenance, as machine failures often originate from subtle acoustic changes during operation. However, high background noise and limitations of…
conventional Convolutional Neural Networks (CNN) reduce detection reliability. This study proposes a 1D-CNN-based anomaly detection framework with multi-view feature fusion and temporal segmentation to enhance detection performance. The approach combines MFCC, Log-Mel Spectrogram, and Chroma STFT features, while temporal segmentation divides audio signals into 5-second segments to better capture transient anomalies. Experiments on the MIMII dataset under varying Signal-to-Noise Ratio (SNR) conditions show that MFCC and Log-Mel fusion achieves the best performance, with 97.90% accuracy and ROC-AUC of 0.9789. The model maintains accuracy above 90% at −6 dB, demonstrating strong robustness in noisy industrial environments.
Keywords: industrial anomaly detection; 1D-CNN; multi-view feature fusion; temporal segmentation; MIMII dataset.
Abstrak: Deteksi anomali suara merupakan komponen penting dalam sistem pemeliharaan prediktif industri, karena kegagalan mesin sering diawali oleh perubahan akustik yang bersifat halus selama proses operasi. Namun, tingkat kebisingan yang tinggi serta keterbatasan arsitektur Convolutional Neural Network (CNN) konvensional dapat menurunkan keandalan deteksi. Penelitian ini bertujuan mengusulkan kerangka deteksi anomali berbasis 1D-CNN yang mengintegrasikan strategi fusi fitur multi-view dan segmentasi temporal untuk meningkatkan kinerja deteksi. Pendekatan yang digunakan menggabungkan fitur MFCC, Log-Mel Spectrogram dan Chroma STFT, sementara teknik temporal splitting membagi sinyal audio menjadi segmen berdurasi 5 detik untuk menangkap anomali yang bersifat sementara. Eksperimen menggunakan dataset MIMII pada berbagai kondisi Signal-to-Noise Ratio (SNR) menunjukkan bahwa kombinasi MFCC dan Log-Mel Spectrogram menghasilkan kinerja terbaik dengan akurasi 97,90% dan ROC-AUC sebesar 0,9789. Model juga mempertahankan akurasi di atas 90% pada kondisi kebisingan ekstrem (−6 dB) yang menunjukkan ketahanan yang baik dalam lingkungan industri yang bising.
Kata kunci: deteksi anomali industri; 1D-CNN; fusi fitur multi-view; segmentasi temporal; dataset MIMII
Abstract:Abstract: Rehabilitation programs are essential in correctional systems to equip inmates with the skills and behavioral readiness required for social reintegration. However, rehabilitation program assignment in many correctional…
ectional institutions remains dependent on manual and subjective assessments, which may result in inconsistent decisions. This study develops a Random Forest–based prediction system to support objective and data-driven rehabilitation program determination. A quantitative approach was applied using historical inmate data from January 2023 to January 2025, comprising 2,023 records. The research process included data preprocessing, an 80:20 training–testing split, model training, and performance evaluation using accuracy, precision, recall, and F1-score metrics. The results show that the model achieved an accuracy of 86.17% during training in Google Colab and 68.83% when deployed within the application system. This performance gap reflects real-world deployment and computational constraints rather than model failure. The proposed system provides consistent and objective rehabilitation program recommendations, thereby supporting more effective rehabilitation planning and decision-making in correctional institutions.
Keywords: correctional institutions; inmate rehabilitation programs; machine learning; random Forest; prediction system
Abstrak: Program pembinaan narapidana memiliki peran penting dalam sistem pemasyarakatan untuk membekali warga binaan dengan keterampilan serta kesiapan perilaku dalam proses reintegrasi ke masyarakat. Namun, pada banyak lembaga pemasyarakatan, penentuan program pembinaan masih bergantung pada penilaian manual yang bersifat subjektif, sehingga berpotensi menimbulkan ketidakkonsistenan dalam pengambilan keputusan. Penelitian ini mengembangkan sistem prediksi program pembinaan narapidana berbasis algoritma Random Forest guna mendukung pengambilan keputusan yang objektif dan berbasis data. Pendekatan kuantitatif diterapkan menggunakan data historis narapidana periode Januari 2023 hingga Januari 2025 sebanyak 2.023 data. Tahapan penelitian meliputi prapemrosesan data, pembagian data latih dan uji dengan rasio 80:20, pelatihan model, serta evaluasi performa menggunakan metrik akurasi, precision, recall, dan F1-score. Hasil penelitian menunjukkan bahwa model mencapai akurasi sebesar 86,17% pada tahap pelatihan di Google Colab dan 68,83% saat diimplementasikan pada sistem aplikasi. Perbedaan performa tersebut mencerminkan keterbatasan lingkungan operasional, bukan kegagalan model. Secara keseluruhan, sistem yang dikembangkan mampu memberikan rekomendasi program pembinaan yang lebih objektif dan konsisten, sehingga mendukung perencanaan pembinaan yang lebih efektif.
Kata kunci: mesin pembelajaran; program pembinaan narapidana; random Forest; sistem pemasyarakatan; sistem prediksi
Abstract:Abstract: The implementation of dress code regulations in university environments is generally still carried out conventionally, requiring significant time and effort and potentially leading to subjective assessments. This…
is study develops an automatic student dress code compliance detection system using computer vision based on the YOLOv8 model. The dataset consists of 1,800 annotated images divided into eight clothing categories, split into 78% training (1,404 images), 14% validation (254 images), and 8% testing (143 images). All images underwent preprocessing and data augmentation before training the YOLOv8 model with an input size of 640×640 pixels for 50 epochs. During testing, the YOLOv8 model achieved an overall performance of Precision 0.844, Recall 0.773, F1-Score 0.802, and mAP@0.5 0.841, and was able to detect clothing objects with good accuracy and stable performance under various image conditions. The system was integrated with a Flask-based backend and a web-based frontend to enable real time detection and compliance classification, with a response time of less than 2 seconds, supporting automatic and consistent identification of student dress code compliance as “Compliant” or “Violation.”
Keywords: compliance detection; computer vision; dress code regulations; real time detection; YOLOv8.
Abstrak: Penerapan aturan berpakaian di lingkungan kampus umumnya masih dilakukan secara konvensional sehingga membutuhkan waktu dan tenaga yang relatif besar serta berpotensi menimbulkan subjektivitas penilaian. Penelitian ini bertujuan mengembangkan sistem pendeteksi kepatuhan berpakaian mahasiswa secara otomatis berbasis visi komputer menggunakan model YOLOv8. Dataset yang digunakan terdiri dari 1.800 citra beranotasi yang terbagi ke dalam 8 kategori pakaian, dengan pembagian data sebesar 78% data latih (1.404 citra), 14% data validasi (254 citra) dan 8% data uji (143 citra). Seluruh citra diproses melalui tahapan pre-processing dan data augmentation, kemudian digunakan untuk melatih model YOLOv8 dengan ukuran input 640×640 piksel selama 50 epoch. Pada tahap pengujian, model mencapai performa keseluruhan dengan Precision 0.844, Recall 0.773, F1-Score 0.802, dan mAP@0.5 0.841, serta mampu mendeteksi objek pakaian dengan akurasi baik dan performa stabil pada berbagai kondisi citra. Sistem kemudian diintegrasikan dengan backend berbasis Flask dan frontend web untuk mendukung proses deteksi waktu nyata dan klasifikasi kepatuhan, dengan waktu respons sistem kurang dari 2 detik, sehingga mampu mengidentifikasi status kepatuhan berpakaian mahasiswa ke dalam kategori “Aman” dan “Melanggar Aturan” secara otomatis dan konsisten.
Kata kunci: aturan berpakaian; deteksi waktu nyata; pendeteksi kepatuhan; visi komputer; YOLOv8.
Abstract:Abstract: Teacher performance appraisal is a very important aspect in improving the quality of education today, but often occurs during the assessment process of subjectivity constraints and lack of a structured system,…
in this study aims to build a data structure modeling and facilitate the school MAS Islamiyah Hessa Air Genting in the assessment to determine the best teacher transparently and measurably by using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) algorithm. The TOPSIS method was chosen because it is able to provide ranking results based on the closeness of alternatives to the ideal solution. In this modeling, assessment criteria data such as pedagogical, professional, personality, social competencies, as well as other indicators such as teacher discipline and achievement are modeled structurally in a relational database. The results show that the designed data structure is able to support the decision-making process efficiently and objectively.
Keywords: data structure; decision support system; teacher assessment; topsis; ranking.
Abstrak: Penilaian kinerja guru merupakan aspek yang sangat penting dalam peningkatan mutu pendidikan saat ini, namun sering terjadi saat proses penilaian kendala subjektivitas dan kurangnya sistem yang terstruktur, dalam penelitian ini bertujuan untuk membangun pemodelan struktur data serta mempermudah pihak sekolah MAS Islamiyah Hessa Air Genting dalam penilaian untuk menentukan guru terbaik secara transparan dan terukur dengan menggunakan algoritma Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Metode TOPSIS dipilih karena mampu memberikan hasil perankingan berdasarkan kedekatan alternatif terhadap solusi ideal. Dalam pemodelan ini, data kriteria penilaian seperti kompetensi pedagogik, profesional, kepribadian, sosial, serta indikator lain seperti kedisiplinan dan prestasi guru dimodelkan secara terstruktur dalam basis data relasional. Hasil penelitian menunjukkan bahwa struktur data yang dirancang mampu mendukung proses pengambilan keputusan secara efisien dan objektif.
Kata kunci: struktur data; topsis; penilaian guru; sistem pendukung keputusan; perangkingan
Abstract:Abstract: The implementation of Geographic Information Systems (GIS) within organizations has become essential in accomplishing work activities in the modern era. Sideak Motor is a financing company in Kisaran City, Asahan…
an Regency, that provides loans using motorcycle registration certificates (BPKB) as collateral, with a customer base reaching 6,052. Sideak Motor faces difficulties in data management. During meetings concerning customer locations, data communication with owners and office staff is often problematic. Additionally, when duties are transferred, new field officers struggle to locate customers because the previous officers could only provide textual information. As a result, office staff have no precise knowledge of customer locations—only the field officers do. This study aims to design a web-based customer mapping system to facilitate information storage, reduce costs, save time, and produce an information system that enhances the efficiency and accuracy of customer data management. The resulting system presents the distribution of customer locations and provides accessible information such as personal data, addresses, route details, and photos of customers’ homes, thereby simplifying the operations of Sideak Motor.
Keywords: customer distribution mapping; geographic information system (GIS); sideak motor.
Abstrak: Penerapan sistem informasi geografis dalam organisasi menjadi hal utama untuk menyelesaikan suatu aktivitas pekerjaan pada era sekarang ini. Sideak Motor merupakan salah satu perusahaan pembiayaan dengan agunan BPKB sepeda motor di Kota Kisaran Kabupaten Asahan yang memiliki nasabah mencapai 6.052, Sideak Motor kesulitan dalam pengelolaan data, saat melakukan rapat mengenai lokasi nasabah sulit dilakukan komunikasi data dengan pemilik dan petugas kantor lainnya, serta pada saat pergantian tugas, petugas lainnya kesulitan mencari lokasi nasabah, karena petugas lapangan hanya bisa memberikan informasi berupa teks, dengan begitu petugas kantor tidak mengetahui lokasi pasti nasabah Sideak Motor, jadi yang mengetahui lokasi mengenai tempat tinggal nasabah hanya petugas lapangan. Penelitian ini memiliki tujuan untuk merancang sebuah sistem pemetaan nasabah berbasis web yang dapat mempermudah dalam penyimpanan informasi, mengurangi biaya, menghemat waktu serta menghasilkan sistem informasi yang dapat meningkatkan efisiensi dan akurasi pengelolaan data nasabah. Hasil sistem ini menyajikan sebaran pemetaan lokasi nasabah menyediakan informasi berupa biodata, alamat, rincian rute, dan gambar rumah nasabah yang dapat diakses secara cepat dan akurat sehingga dapat mempermudah pihak sideak motor.
Kata Kunci: pemetaan sebaran nasabah; sistem informasi geografis (SIG); sideak motor
Abstract:Abstract: Good pronunciation plays a crucial role in enhancing students' confidence, encouraging active participation in learning, and preparing them for academic and professional opportunities, such as English-language…
interviews. Poor pronunciation during scholarship or job interviews can hinder the interviewer's understanding, thereby reducing the chances of acceptance. This study aims to improve students' pronunciation fluency and develop a learning medium based on Automatic Speech Recognition (ASR) technology. The method employed involves the development of Progressive Web Apps (PWA) integrated with ASR technology from the app.lumi.education platform, supported by manual labeling for pronunciation validation. The research was conducted at LKP Vijaya Learning Centre, Tanjungbalai City. The results demonstrate that ASR-based media significantly enhances students' pronunciation accuracy and confidence. Thus, the integration of ASR technology into PWA effectively supports innovative and efficient pronunciation learning.
Keywords: automatic speech recognition; language learning; pronunciation; web-based application.
Abstrak: Pengucapan yang baik berperan penting dalam meningkatkan kepercayaan diri siswa, mendorong partisipasi aktif dalam pembelajaran, dan mempersiapkan mereka menghadapi peluang akademik maupun profesional, seperti wawancara berbahasa Inggris. saat menghadapi wawancara beasiswa atau pekerjaan berbahasa Inggris, pengucapan yang buruk dapat mengurangi pemahaman pewawancara, sehingga mengurangi peluang diterima. Penelitian ini bertujuan untuk meningkatkan kelancaran pengucapan siswa dan mengembangkan media pembelajaran berbasis teknologi Automatic Speech Recognition (ASR). Metode yang digunakan adalah pengembangan Progressive Web Apps (PWA) yang terintegrasi dengan ASR dari aplikasi app.lumi.education, didukung oleh pelabelan manual untuk validasi pengucapan. Penelitian dilakukan di LKP Vijaya Learning Centre, Kota Tanjungbalai. Hasil penelitian menunjukkan bahwa media berbasis ASR secara signifikan meningkatkan akurasi pengucapan dan kepercayaan diri siswa. Dengan demikian, integrasi teknologi ASR dalam PWA terbukti mendukung pembelajaran pengucapan secara inovatif dan efisien.
Kata kunci: aplikasi berbasis web; pengenalan suara otomatis; pembelajaran bahasa; pengucapan
Abstract:Abstract: Bekasi Regency, being one of the key cities in Indonesia, offers a suitable setting to study the intricacies of marriage decision-making during a quarter-life crisis. This study focuses on the application of clustering…
ustering algorithms to categorize individuals based on their marriage choices. Data was collected from a questionnaire completed by 110 respondents from Bekasi Regency, specifically individuals aged 18 to 30 who are single, including 80 women and 30 men. Data analysis was conducted using the RapidMiner software to evaluate the effectiveness of three clustering algorithms K-Means, X-Means, and K-Medoids in categorizing marriage decision patterns among young people experiencing a Quarter Life Crisis in Bekasi Regency. Results indicate that each algorithm has its own strengths and limitations in handling Quarter Life Crisis data.The results of the analysis show that the K-medoids algorithm provides the best clustering results with the lowest DBI value of 0.195, followed by the X-Means algorithm with a value of 0.199 and K-Means with a value of 0.207. These results can help understand the pattern of marriage decisions in the Quarter Life Crisis phase and help provide insights for policymakers in Bekasi Regency to make more effective intervention programs.
Keywords: K-Means; K-Medoids; X-Means
Abstrak: Sebagai salah satu kota besar di Indonesia, Kabupaten Bekasi memberikan konteks yang tepat untuk mempelajari kompleksitas pengambilan keputusan pernikahan di tengah krisis seperempat usia. Penelitian ini berfokus pada pemanfaatan algoritma clustering untuk mengelompokkan individu berdasarkan pilihan pernikahan mereka. Data diambil dari kuesioner yang diisi oleh 110 responden di Kabupaten Bekasi, yang terdiri dari individu lajang berusia 18 hingga 30 tahun, yaitu 80 perempuan dan 30 laki-laki. Analisis data dilakukan dengan perangkat lunak RapidMiner untuk mengevaluasi efektivitas tiga algoritma pengelompokan—K-Means, X-Means, dan K-Medoids—dalam mengelompokkan pola keputusan pernikahan di kalangan pemuda yang menghadapi Quarter Life Crisis di Kabupaten Bekasi. Hasilnya menunjukkan bahwa setiap algoritma memiliki keunggulan dan kelemahannya masing-masing dalam memproses data Quarter Life Crisis. Hasil analisis menunjukkan bahwa algoritma K-medoids memberikan hasil clustering terbaik dengan nilai DBI terendah yaitu 0.195, diikuti oleh algoritma X-Means dengan nilai 0.199 dan K-Means dengan nilai 0.207. Hasil ini dapat membantu memahami pola keputusan menikah pada fase Quarter Life Crisis dan membantu memberikan wawasan bagi pembuat kebijakan di Kabupaten Bekasi membuat program intervensi yang lebih efektif.
Kata kunci: K-Means; K-Medoids; X-Means