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Web-Based Decision Support System for Selecting Exemplary Teachers using TOPSIS Method Sumardiono, Sumardiono; Ismail, Norhafizah; Shadiq, Jafar; Nida, Zahra Qotrun; Solikin, Solikin; Suryani, Riska
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

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.

Data-Driven Insights for Higher Education Marketing: Segmenting Applicant Pools Using K-Means Clustering Shadiq, Jafar; Wicaksono, Harjunadi; Budiarto, Rahmat; Salamah, Raisha Nur; Fakhrudin, Zidan Al Buqhori
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 2 (2025): September 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i2.11545

This research aims to optimize marketing strategies for new student recruitment at Bina Insani University (BiU), which faces intense competition. The current marketing efforts are generic and inefficient. Utilizing the CRISP-DM framework, this study applies the K-Means clustering data mining method to analyze primary data from applicants from 2021 to 2024. The analysis focuses on the attributes of previous school major, information source, and location. The findings successfully identified four distinct segments of prospective students: the "Proactive Outreach Segment," reached through school presentations; the "Social Network & Affiliation Segment," influenced by friends and relatives; the "Academic Recommendation Segment," who rely on guidance from teachers; and the "Digital & Non-Technical Segment," who actively seek information on social media. Based on the unique profile of each cluster, this study provides recommendations for specific and targeted marketing strategies to improve the effectiveness and efficiency of student recruitment

Web-Based Decision Support System for Selecting Exemplary Teachers usingTOPSIS Method Sumardiono, Sumardiono; Ismail, Norhafizah; Shadiq, Jafar; Nida, Zahra Qotrun; Solikin, Solikin; Suryani, Riska
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

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.

Pelatihan JavaScript Programming Dasar Pada ASN dan Non ASN Diskominfo Bekasi Shadiq, Jafar; Syafitri, Nadya; Setiyadi, Didik
Universal Raharja Community (URNITY Journal) Vol. 1 No. 1 (2021): URNITY (Universal Raharja Community)
Publisher : UNIVERSITAS RAHARJA

Peraturan Walikota Bekasi Nomor 54 Tahun 2018 tentang Perubahan Atas Peraturan Walikota Bekasi Nomor 79 Tahun 2016 tentang Kedudukan, Susunan, Organisasi, tugas pokok dan fungsi serta tata kerja pada Dinas Komunikasi, Informatika, Statistik, dan Penyandiaksaraan (Diskominfostandi) Kota Bekasi tertuang dalam Pasal 4 ayat (1) Bahwa Kepala Dinas mempunyai tugas membantu Walikota dalam memimpin, mengendalikan, dan mengkoordinasikan perumusan kebijakan teknis dan pelaksanaan fungsi pemerintahan yang menjadi kewenangan Dinas yang meliputi bidang manajemen informasi publik, teknologi informasi dan komunikasi, e-government dan statistik. dan coding untuk mencapai visi dan misi Dinas. Diperlukan kemampuan penguasaan teknologi dan informasi khususnya untuk ASN dan non ASN di Pemerintah Kota Bekasi, khususnya dalam penguasaan konsep JavaScript. Pelaksanaan Diklat Online PkM “Basic JavaScript” ini dilakukan sesuai dengan implementasi MoU yang telah dilakukan antara Pemerintah Kota Bekasi dengan Universitas Bina Insani. Melalui Diklat Online PkM "Basic JavaScript", dosen Fakultas Informatika Program Studi Sistem Informasi Universitas Bina Insani dapat memberikan bekal bagi ASN dan Non ASN di Pemerintah Kota Bekasi. Dengan adanya pelatihan konsep JavaScript ini diharapkan para ASNs dan Non ASNs dapat meningkatkan kemampuannya dan dapat mendukung penerapan Smart City di Kota Bekasi.

PENDETEKSI DENIAL OF SERVICE PADA JARINGAN WIRELESS FIDELITY BERBASIS INTERNET OF THINGS Devinder, Shunil; Shadiq, Jafar
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 7 No 4 (2025): EDISI 26
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v7i4.6681

Keamanan jaringan Wireless Fidelity (Wi-Fi) menjadi perhatian penting di era digital, khususnya karena ancaman serangan Denial of Service (DoS) dapat mengganggu layanan akademik mahasiswa serta rentan terhadap perangkat Internet of Things (IoT) yang banyak digunakan dalam sistem kritis. Penelitian ini bertujuan untuk mengembangkan sistem deteksi DoS berbasis ESP32 (BPI-Leaf-S3) dengan pemanfaatan mode promiscuous dan analisis ambang batas (threshold packet analysis). Metode penelitian melibatkan pemrograman perangkat IoT untuk memantau lalu lintas jaringan Wi-Fi dengan cara menghitung jumlah paket yang diterima dalam selang waktu tertentu dan membandingkannya dengan nilai ambang batas yang telah ditentukan. Deteksi serangan dilakukan ketika jumlah paket per detik melebihi ambang tersebut. Hasil penelitian menunjukkan bahwa sistem yang dikembangkan mampu mendeteksi adanya serangan DoS berdasarkan parameter lalu lintas paket per detik. Penelitian ini juga berhasil mengidentifikasi nilai ambang lalu lintas yang dapat dijadikan indikator awal serangan. Sistem yang diusulkan berpotensi membantu mencegah permasalahan server down akibat serangan DoS pada jaringan Wi-Fi dengan mendeteksi pola lalu-lintas mencurigakan sejak dini.

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