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All Journal Informatics for Educators and Professional : Journal of Informatics Applied Information System and Management
Jafar Shadiq
Bina Insani University
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Languange, Linguistic, Communication & Media Other

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Web-Based Decision Support System for Selecting Exemplary Teachers usingTOPSIS Method Sumardiono Sumardiono; Norhafizah Ismail; Jafar Shadiq; Zahra Qotrun Nida; Solikin Solikin; Riska Suryani
Applied Information System and Management (AISM) Vol. 8 No. 1 (2025): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v8i1.45488

Abstract

This study creates an online Decision Support System (DSS) using the TOPSIS algorithm to fairly choose outstanding teachers from vocational schools in Bekasi City, which has 87 state and private vocational secondary schools with about 62,000 students. To tackle the current biased selection process, our research uses a multi-criteria approach that looks at discipline (25%), travel costs (20%), personality (20%), teaching administration (15%), and learning achievements (20%). Targeting this substantial educational population, our research addresses the current subjective selection process by implementing a multi-criteria approach evaluating discipline (25%), travel costs (20%), personality (20%), teaching administration (15%), and learning achievements (20%). The TOPSIS method was selected for its proven effectiveness in ranking alternatives based on geometric distance from ideal solutions, particularly valuable in large-scale educational contexts. Analysis of 14 teacher candidates from SMK Bina Karya Mandiri demonstrated the system's precision, with Didi Saputra, S.Pdi, emerging as top-ranked (preference value: 0.63). When extrapolated to Bekasi's 87 SMKs, the model shows potential to standardize teacher assessment citywide, reducing regional disparities in recognition practices. The web-based platform enhances accessibility, allowing principals across 21 sub-districts to input localized data while maintaining centralized benchmarking. Key findings reveal (1) discipline and personality collectively account for 45% of exemplary status determination, (2) cost-related factors show inverse correlation with remote school nominations, and (3) system implementation could reduce selection time by ≈68% compared to manual methods. This study contributes both a scalable framework for educational DSS and empirical data on vocational teacher excellence criteria in urban Indonesia.
Implementasi Sistem Timbangan Sampah Berbasis Internet of Things (IoT) untuk Meningkatkan Efisiensi Operasional Bank Sampah Jafar Shadiq; Hari Sapto Yudiarso; Dwi Ismiyana Putri; Fazril Mantovani; Rasya Pramudya Teja
INFORMATICS FOR EDUCATORS AND PROFESSIONAL : Journal of Informatics Vol. 10 No. 2 (2025): INFORMATICS FOR EDUCATORS AND PROFESSIONAL : JOURNAL OF INFORMATICS (Desember
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Bina Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51211/itbi.v10i2.3793

Abstract

Pengelolaan sampah berbasis komunitas melalui bank sampah masih menghadapi berbagai kendala, terutama pada proses penimbangan dan pencatatan transaksi yang masih dilakukan secara manual. Proses tersebut berpotensi menimbulkan kesalahan pencatatan, membutuhkan waktu pelayanan yang lama, serta memiliki tingkat transparansi data yang rendah. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem timbangan sampah berbasis Internet of Things (IoT) yang terintegrasi dengan sistem informasi bank sampah guna meningkatkan akurasi, efisiensi, dan transparansi pengelolaan data. Metode yang digunakan adalah metode prototype, yang memungkinkan pengembangan sistem dilakukan secara bertahap melalui proses perencanaan, analisis, perancangan, pembuatan prototipe, dan implementasi sistem akhir. Sistem dikembangkan menggunakan sensor load cell sebagai pendeteksi berat, modul HX711 sebagai penguat dan konverter sinyal, serta mikrokontroler NodeMCU ESP32 sebagai pengendali utama dan pengirim data ke server berbasis cloud. Hasil pengujian menunjukkan bahwa sistem timbangan IoT memiliki tingkat akurasi rata-rata sebesar 99,15% dengan error yang relatif rendah. Selain itu, penerapan sistem ini mampu mempercepat waktu transaksi, mengurangi risiko kesalahan pencatatan, serta meningkatkan transparansi data bagi pengelola dan warga bank sampah. Dengan demikian, sistem timbangan IoT yang dikembangkan terbukti efektif sebagai solusi teknologi untuk mendukung pengelolaan bank sampah berbasis komunitas dan berpotensi untuk diterapkan pada bank sampah lainnya.
Co-Authors Dwi Ismiyana Putri Fazril Mantovani Hari Sapto Yudiarso Norhafizah Ismail Rasya Pramudya Teja Riska Suryani Solikin Solikin Sumardiono Sumardiono Zahra Qotrun Nida