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All Journal Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences SAINSTECH: Jurnal Penelitian dan Pengkajian Sains dan Teknologi Khazanah: Journal of Islamic Education and Science
Muhammad Suhaili
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Religion Arts Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Mechanical Engineering Social Sciences Other

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Application of Analytical Hierarchy Process (AHP) Methods in Decision Making of Lecturer Performance Determination on the Utilization of Online Learning in Polytechnic Media Kreatif Tri Fajar Yurmama Supiyanti; Herly Nurrahmi; Muhammad Suhaili
Budapest International Research and Critics Institute (BIRCI-Journal): Humanities and Social Sciences Vol 4, No 4 (2021): Budapest International Research and Critics Institute November
Publisher : Budapest International Research and Critics University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33258/birci.v4i4.3303

Abstract

In the development of technology, decision making is something that will be done by all humans in life. Making a decision is not an easy matter because every decision made and carried out by someone must consider a risk to be borne. Decision Support System (DSS) is a system which utilizes the use of computers in every decision-making process. The achievement of the learning objectives that have been set or have just been achieved depends on the ability of human resources (lecturers) in carrying out their duties. To be able to recognize the ability and potential of a lecturer for his work, a university must have an assessment system to support decisions in determining the performance of a lecturer. The purpose of this research is to obtain a method that has a high accuracy value with the analytical hierarchy process (AHP) method so that a high accuracy and fast method is obtained to determine the performance of lecturers in the use of online learning. The result of this research is obtained criteria to produce a solution in determining the performance of lecturers such as criteria, attendance, performance, opportunity, and integrity.
Perbandingan Metode Backpropagation dan Analytical Hierarchy Process (AHP) dalam Penentuan Kinerja Dosen Herly Nurrahmi; Tri Fajar Yurmama Supiyanti; Muhammad Suhaili
SAINSTECH: JURNAL PENELITIAN DAN PENGKAJIAN SAINS DAN TEKNOLOGI Vol 34 No 2 (2024): Sainstech : Jurnal Penelitian dan Pengkajian Sains dan Teknologi
Publisher : Institut Sains dan Teknologi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37277/stch.v34i2.2100

Abstract

Pengambilan suatu keputusan adalah bukan suatu perihal yang mudah dikarenakan setiap keputusan yang dibuat dan dilakukan oleh seseorang harus mempertimbangkan suatu resiko yang akan ditanggung. Sistem Pendukung Keputusan (SPK) merupakan suatu sistem dimana yang memanfatkan penggunaan komputer dalam setiap proses pengambilan keputusan. Pencapaian dari tujuan pembelajaran yang telah ditetapkan atau baru dicapai tergantung pada kemampuan sumber daya manusia (dosen) didalam menjalankan tugas-tugasnya. Untuk dapat mengenali kemampuan dan potensi seorang dosen atas hasil kerjanya, maka sebuah perguruan tinggi harus memiliki sebuah sistem penilaian untuk mendukung keputusan dalam menentukan kinerja seorang dosen. Adapun tujuan dari penelitian ini untuk mendapatkan metode yang memiliki nilai akurasi tinggi dengan membandingkan metode backpropagation dengan metode analytical hirarki Diagram (AHP) sehingga akan didapatkan metode yang akurasi tinggi dan cepat untuk menentukan kinerja dosen dalam pemanfataan pembelajaran daring. Untuk kriteria yang digunakan pada metode ini adalah kriteria absensi, performance, opportunity, dan integritas. Dari penelitian yang telah dilakukan didapat metode backpropagation memiliki akurasi yang tinggi dari pada metode analytical hirarki Diagram (AHP). Hasil akhir dari penelitian ini adalah pembobotan yang telah dilakukan oleh masing-masing kriteria dengan menggunakan Analytic Hierarchy Process (AHP) dan backpropagation menghasilkan solusi yang dapat digunakan untuk mendukung keputusan untuk menentukan kinerja dosen. Kata Kunci: Backpropagation, AHP, Kinerja, Dosen
Application of Machine Learning Algorithms Based on Islamic Moral Values for Mitigating Negative Content on Digital Media Majid, Moch Nurcholis; Muhammad Suhaili
Khazanah: Journal of Islamic Education and Science Vol. 1 No. 2 (2025): Khazanah: Journal of Islamic Education and Science
Publisher : Institut Bahri Asyiq Galis Bangkalan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61815/khazanah.v1i2.871

Abstract

Information bias in digital media has evolved into a systemic problem driven by algorithmic designs that prioritize user engagement optimization without adequate value orientation. This condition has contributed to polarization, amplification of sensational content, and unequal information representation. This study aimed to reconstruct data science algorithms based on Prophetic Ethics as a normative-operational framework to mitigate information bias in digital media. The research employed a descriptive qualitative approach with a systematic meta-analysis of scholarly publications from 2016 to 2025 retrieved from reputable academic databases. Data were analyzed using content analysis and thematic analysis to synthesize patterns of algorithmic bias and formulate a reconstruction model grounded in the principles of ṣidq (truthfulness), amānah (trustworthiness), tablīgh (transparency), and faṭānah (wisdom). The findings indicated that algorithmic bias occurred across all stages of the data processing pipeline and required structural reconstruction rather than partial technical adjustments. The proposed model integrated data validation, accountable governance, transparent modeling, and social welfare optimization within recommendation system design. This study contributed to the development of a value-oriented data science paradigm and expanded the discourse on algorithmic ethics in contemporary digital societies.
Co-Authors Majid, Moch Nurcholis Nurrahmi, Herly Tri Fajar Yurmama Supiyanti