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All Journal Jurnal Mahasiswa TEUB Indonesian Journal of Public Policy Review
Muhammad Rizal Habibi
Institut Teknologi Sepuluh Nopember (ITS)
Education Social Sciences

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Integrated Strategy Performance: Waste Management Findings at Griyo Mulyo Sidoarjo: Strategi Terpadu dalam Pengelolaan Limbah: Temuan di Griyo Mulyo Sidoarjo Habibi, Muhammad Rizal; Rodiyah, Isnaini
Indonesian Journal of Public Policy Review Vol. 26 No. 1 (2025): January
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijppr.v26i1.1445

Abstract

General Background: Rapid population growth and urbanization in Sidoarjo Regency, East Java, are increasing waste generation, straining the capacity of the Griyo Mulyo Final Processing Site (TPA). Specific Background: Despite efforts, the TPA experienced overload in 2021, necessitating an immediate and comprehensive strategic overhaul to ensure sustainable waste management. Knowledge Gap: Previous studies often lack a comprehensive strategic framework, while existing management suffers from challenges like low HR competence and technology mismatch. Aims: This study analyzes the strategy of the Environmental and Sanitation Agency (DLHK) in waste management at TPA Griyo Mulyo, based on Jack Kooten's four strategic dimensions. Results: The strategies are integrated: Institutional (TPA-BLUD transformation), Organizational (participatory leadership), Program (TPS3R, volume-based tariffs), and Resource Support (HR training, SIPPAS system), resulting in a 28.2% waste volume reduction (2019-2023). However, limitations persist regarding technology compatibility and staff competency. Novelty: The use of Jack Kooten's four strategic dimensions provides a new, comprehensive framework for evaluating integrated waste management performance in a local government context. Implications: The findings offer a model for local governments to build resilient waste management systems through institutional and technological adaptation, prioritizing human resource development to overcome operational constraints. Highlights: TPA Griyo Mulyo transitioned to a BLUD model to enhance operational flexibility and accountability. Integrated strategies led to a 28.2% reduction in Sidoarjo's annual waste volume from 2019 to 2023. Management remains constrained by HR competency gaps and technology mismatch with local wet waste characteristics. Keywords: Strategy, Waste Management, TPA Griyo Mulyo, Organizational Performance, Resource Support.
IMPLEMENTASI CNN-LSTM BERBASIS MEDIAPIPE UNTUK KLASIFIKASI BODYWEIGHT EXERCISE SECARA REAL-TIME Habibi, Muhammad Rizal; Purnomo, Muhammad Fauzan Edy; Muttaqin, Adharul
Jurnal Mahasiswa TEUB Vol. 14 No. 5 (2026)
Publisher : Jurnal Mahasiswa TEUB

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Inaktivitas fisik merupakan tantangan kesehatan global yang signifikan. Pertumbuhan aplikasi kebugaran digital belum diimbangi kemampuan mengenali jenis gerakan olahraga secara otomatis dan real-time. Penelitian ini mengusulkan model CNN-LSTM berbasis MediaPipe untuk mengklasifikasikan lima jenis bodyweight exercise, yaitu push-up, sit-up, squat, jumping jack, dan lunges, beserta kelas idle secara real-time. Data pose tubuh diekstraksi menggunakan MediaPipe dan diperkaya melalui rekayasa fitur geometris serta fitur dinamika gerakan sehingga menghasilkan representasi spasial-temporal yang lebih informatif. Convolutional Neural Network (CNN) digunakan untuk mengekstraksi pola geometris antar-landmark tubuh, sedangkan Long Short-Term Memory (LSTM) digunakan untuk mempelajari pola temporal gerakan. Studi ablasi dilakukan melalui tujuh skenario konfigurasi (K1–K7) yang mencakup variasi arsitektur, rekayasa fitur, dan augmentasi data. Hasil penelitian menunjukkan konfigurasi terbaik, yaitu K7 (CNNLSTM dengan fitur spasial-temporal dan augmentasi data) memperoleh akurasi ensemble sebesar 94,96%. Pengujian pada 13 subjek dengan tiga variasi sudut kamera menunjukkan sudut 45° dan 90° menghasilkan performa terbaik, sedangkan sudut 0° mengalami penurunan akurasi, khususnya pada push-up. Sistem mampu beroperasi secara real-time dengan rata-rata 17,05 FPS dan waktu inferensi 84,96 ms pada perangkat tanpa GPU khusus. Kata Kunci—Bodyweight Exercise, CNN-LSTM, Human Activity Recognition (HAR), Mediapipe. 
Co-Authors Adharul Muttaqin Isnaini Rodiyah Purnomo, Muhammad Fauzan Edy