Subhan, Muhammad Ferindin Nuha
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TEMPAT SAMPAH BERBASIS DRUM UNTUK MENINGKATKAN EFISIENSI DAN MERINGANKAN PEKERJA SAMPAH Arimbawa, Anak Agung Gde Rai; Amiratun, Silvia; Subhan, Muhammad Ferindin Nuha; Sari, Puspita; Safutro, Syaifudin Hadi; Wibisono, Abdillah
Jurnal Graha Pengabdian Vol 6, No 3 (2024): SEPTEMBER
Publisher : Universitas Negeri Malang

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Abstract

Pengabdian kepada masyarakat yang dilakukan oleh Universitas Negeri Malang yaitu KKN (Kuliah Kerja Nyata). Tujuan dari kegiatan KKN ini diantaranya yaitu melaksanakan Tri Dharma Perguruan Tinggi dalam pengbadian masyarakat, mengenalkan mahasiswa dalam kehidupan bermasyarakat, memperluas hubungan baik antara universitas dengan pemerintah serta masyarakat sasaran dan membantu terwujudnya ketersediaan data atau profil desa dengan mengidentifikasi serta menganalisis data yang dapat digunakan untuk perencanaan pembangunan desa dengan target Tujuan pembangunan berkelanjutan. Pelaksanaan KKN dilaksanakan di beberapa desa yang terdapat di kabupaten malang, salah satunya adalah Desa Belung, Kecamatan Poncokusumo, Kabupaten Malang , mulai dari tanggal 19 Juni sampai tanggal 02 Agustus 2024. Desa Belung terlihat sudah cukup baik dalam beberapa aspek diantaranya pendidikan, sosial dan ekonomi serta pertanian. KKN diawali dengan proses observasi desa guna menjajagi desa dan melihat potensi desa yang akan menjadi sasaran utama dalam pelaksanaan KKN. Program-program dirancang berurutan mulai dengan diskusi antar kelompok KKN, aparat desa, serta masyarakat setempat, khususnya yang bersangkutan langsung dengan program-program yang dirancang. Pelaksanaan program KKN dilakukan secara seimbang diawali dengan perencanaan, pelaksanaan, serta evaluasi di akhir setiap program. Kata Kunci: Kebersihan, Kesehatan, Kesadaran, Buanglah sampah pada tempatnya Abstract : Community service carried out by the State University of Malang is KKN (Real Work Lecture). The objectives of this KKN activity include implementing the Tri Dharma of Higher Education in community service, introducing students to community life, expanding good relations between the university and the government and target communities and helping to realize the availability of data or village profiles by identifying and analyzing data that can be used for planning. village development with the target of sustainable development goals. The KKN implementation was carried out in several villages in Malang Regency, one of which is Belung Village, Poncokusumo District, Malang Regency, starting from June 19 to August 2 2024. Belung Village looks quite good in several aspects including education, social and economic as well as agriculture. KKN begins with a village observation process in order to explore the village and see the potential of the village which will be the main target in implementing KKN. The programs are designed sequentially starting with discussions between KKN groups, village officials and local communities, especially those directly concerned with the programs being designed. The implementation of the KKN program is carried out in a balanced manner starting with planning, implementation and evaluation at the end of each program. Keywords: Cleanliness, Health, Awareness, Throw away rubbish in the right place.
Sensor Fusion of Laser and Inertial Units with Kalman-KMeans-Fuzzy Framework for Real-Time Railway Geometry Monitoring Fikri, Ahmad Atif; Subhan, Muhammad Ferindin Nuha; Suryanto, Heru; Muhdi, Krisna Dwipa; Pratama, Daniel Febrian; Iqbal, Ahmad
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 3 (2025): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i3.13780

Abstract

Maintaining railway track geometry integrity is essential to ensuring transportation safety and predictive maintenance. Conventional manual inspection methods are limited by low sampling frequency, subjective interpretation, and delayed anomaly detection. This study introduces a real-time, embedded monitoring system using VL53L0X infrared laser sensors and an MPU6050 IMU to measure gauge, cross-level height, and inclination. Sensors are mounted on a lightweight aluminum trolley and sampled every 0.5 seconds using an Arduino-based platform. A Kalman Filter reduces measurement noise, with tuned covariance matrices based on field calibration. Filtered outputs are clustered via K-Means (K = 2), validated by the Elbow Method and Silhouette Score (>0.6). Maintenance categories are assigned through a fuzzy logic system, with a ±1 mm sensitivity analysis confirming >85% decision stability. Field results demonstrate a measurement noise, achieving RMSE and MAE values of 0.8165 mm and 0.3175 mm for gauge and height, and 0.3086° and 0.0952° for inclination, respectively and a SNR gain from 0.5 dB to 21.7 dB. The low-cost, modular setup supports scalable, condition-based maintenance and demonstrates robustness in noisy environments. This approach offers a practical foundation for future integration with predictive analytics and digital twin technologies in smart rail infrastructure.