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All Journal Proceedings of KNASTIK Jurnal Buana Informatika Jurnal Ilmu Komputer dan Agri-Informatika JPSriwijaya JOIV : International Journal on Informatics Visualization Jurnal Teknoinfo MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Krea-TIF: Jurnal Teknik Informatika Journal of Science Innovare Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika IJEEIT : International Journal of Electrical Engineering and Information Technology Building of Informatics, Technology and Science Jurnal Leverage, Engagement, Empowerment of Community (LeECOM) JTIK (Jurnal Teknik Informatika Kaputama) Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Journal Social Science And Technology For Community Service Prosiding Seminar Nasional Sains Teknologi dan Inovasi Indonesia (Senastindo) BEES: Bulletin of Electrical and Electronics Engineering Jurnal Aplikasi Bisnis dan Komputer J-Icon : Jurnal Komputer dan Informatika Bulletin of Informatics and Data Science CHAIN: Journal of Computer Technology, Computer Engineering and Informatics Journal of Artificial Intelligence and Technology Information JIPETIK:Jurnal Ilmiah Penelitian Teknologi Informasi & Komputer Prosiding SeNTIK STI&K
Sufiatul Maryana
Universitas Pakuan
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Medicine & Pharmacology Neuroscience Public Health Social Sciences Other

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Automatic Door Access Model Based on Face Recognition using Convolutional Neural Network Tjut Awaliyah Zuraiyah; Sufiatul Maryana; Asep Kohar
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 1 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i1.2350

Abstract

Automatic door access technology by utilizing biometrics such as fingerprints, retinas and facial structures is constantly evolving. The use of masks during the Covid-19 Pandemic and post-pandemic has become an obligation wherever humans are active. The study aimed to create an automated door access model using Convolutional Neural Network (CNN) algorithms and Amazon Rekognition as cloud-based software. The CNN algorithm is applied to classify faces wearing masks or not wearing masks. The CNN architecture model uses sequential, convolution2D, max polling 2D, flatten dan dense. The hardware includes the Raspberry Pi, USB Webcam, Relay, and Magnetic Doorlock. The test results were obtained from the results of the accuracy plot on the Convolutional Neural Network model with an accuracy rate of 99% at an epoch value of 8 with a learning time of 67 seconds.
Decision Support System for Evaluating Textile Supplier Performance Based on Weights by Envelope and Slope and Mixed Aggregation by Comprehensive Normalization Technique for Multi-Criteria Setiawansyah Setiawansyah; Junhai Wang; Pritasari Palupiningsih; Sufiatul Maryana
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 7, No 1 (2026)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v7i1.29131

Abstract

The textile industry is highly dependent on supplier performance in ensuring the quality of raw materials, timely delivery, price stability, and supply continuity. The complexity of supplier evaluation involving many criteria often leads to subjectivity and inconsistencies in decision-making when using conventional approaches. This study proposes a decision support system to evaluate textile supplier performance based on a combination of Weights by Envelope and Slope (WENSLO) and Mixed Aggregation by Comprehensive Normalization Technique for Multi-Criteria (MACONT). The WENSLO method is used to determine the weight of criteria objectively based on data distribution characteristics, while MACONT is applied to assess and rank supplier alternatives through a comprehensive normalization and aggregation process. The case study was conducted involving nine suppliers and five evaluation criteria, namely material quality, timeliness, price, supply capacity, and responsiveness. The results of the study indicate that the proposed model is capable of producing clear and stable supplier rankings, with Supplier A9, Supplier A7, and Supplier A2 occupying the top three positions. These findings demonstrate that the integration of WENSLO and MACONT can enhance the objectivity and consistency of decision-making, as well as provide a more reliable and relevant framework for evaluating textile suppliers to support data-driven supply chain management.
Employee Performance Evaluation Using RECA-based Weighting and RAWEC: Evidence from Textile Manufacturing: Evaluasi Kinerja Karyawan Menggunakan Pembobotan Berbasis RECA dan RAWEC: Studi Empiris pada Industri Manufaktur Tekstil Setiawansyah, Setiawansyah; Wang, Junhai; Maryana, Sufiatul; Palupiningsih, Pritasari
Jurnal Buana Informatika Vol. 17 No. 1 (2026): Jurnal Buana Informatika, Volume 17, Nomor 1, April 2026
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jbi.v17i1.13709

Abstract

Employee performance evaluation in the textile industry production division still faces issues of subjectivity, limited indicators, and inconsistency in ranking that do not yet reflect the real contribution of employees. This study aims to assess employee performance using a multi-criteria decision-making approach by integrating the RECA method for determining objective criterion weights and the RAWEC method for generating performance rankings. Performance data is collected based on several key criteria, namely work productivity, production quality, timeliness, work discipline, and production error rates, which reflect the operational conditions in the textile manufacturing environment. The analysis results indicate that the applied approach clearly distinguishes employee performance and produces a stable ranking, with Gina taking first place with a final score of 0.483 and Citra with a score of 0.2933. These findings indicate that RECA and RAWEC support more reliable and data-driven managerial decisions in the textile industry.   Evaluasi kinerja karyawan di divisi produksi industri tekstil masih menghadapi masalah subjektivitas, keterbatasan indikator, dan ketidakkonsistenan pemeringkatan yang belum mencerminkan kontribusi nyata karyawan. Penelitian ini bertujuan untuk menilai kinerja karyawan menggunakan pendekatan pengambilan keputusan multi-kriteria dengan mengintegrasikan metode RECA untuk menentukan bobot kriteria objektif dan metode RAWEC untuk menghasilkan peringkat kinerja. Data kinerja dikumpulkan berdasarkan beberapa kriteria utama, yaitu produktivitas kerja, kualitas produksi, ketepatan waktu, disiplin kerja, dan tingkat kesalahan produksi, yang mencerminkan kondisi operasional pada lingkungan manufaktur tekstil. Hasil analisis menunjukkan bahwa pendekatan yang diterapkan mampu membedakan kinerja karyawan secara jelas dan menghasilkan pemeringkatan yang stabil, di mana Gina menempati peringkat pertama dengan nilai akhir 0.483 Citra dengan nilai 0,2933. Temuan ini menunjukkan RECA dan RAWEC mendukung keputusan manajerial yang lebih andal dan berbasis data di industri tekstil.
Implementasi Certainty Factor Untuk Diagnosa Penyakit Sapi Sufiatul Maryana; Dini Suhartini
CHAIN: Journal of Computer Technology, Computer Engineering, and Informatics Vol. 1 No. 1 (2023): Volume 1 Number 1 January 2023
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/chain.v1i1.5

Abstract

Sistem pakar untuk diagnosa penyakit sapi merupakan sistem pakar yang dirancang sebagai alat bantu untuk mendiagnosa jenis penyakit sapi secara khusus. Pengetahuan ini didapat dari berbagai sumber diantaranya penelitian dan seminar yang dilakukan pakar dalam bidangnya serta buku yang berhubungan dengan penyakit sapi. Sistem Pakar ini dilakukan dengan cara nantinya pengguna sistem memasukan nilai-nilai yang telah disediakan kedalam sistem yang kemudian diproses berdasarkan aturan-aturan atau rule yang di peroleh dari pakar sehingga nantinya didapatkan hasil kesimpulan diagnosa serta memberikan solusi terhadap masalah yang dihadapi oleh pengguna. Hasil penilaian sistem pakar menggunakan metode certainty factor untuk pengguna berdasarkan parameter yang ada, maka mendapatkan hasil tingkat keyakinan menggunakan metode certainty factor adalah penyakit kudis (scabies) dengan tingkat keyakinan sebesar 60%, penyakit sapi ingusan dengan tingkat keyakinan sebesar 12%, penyakit sapi ngorok dengan tingkat keyakinan sebesar 0%, penyakit sapi demam dengan tingkat keyakinan sebesar 16%, penyakit sapi surra dengan tingkat keyakinan sebesar 80%. maka hasil sistem pakar menggunakan metode certainty factor untuk pengguna berdasarkan parameter sapi sulit bernafas dan gemetaran mendiagnosa penyakit sapi surra dengan tingkat keyakinan 80%.
Co-Authors Abdat, Misel Umar Agung Prajuhana Putra Agung Prajuhana Putra Agung Prajuhana Putra Alfiansyah Alfiansyah Andi Mulyono Anggraeni, Ade Irma Arie Arie Qur’ania Arshad, Muhammad Waqas Asep Kohar Benny Nofika Benny Rachman Chandra, Iryanto Dian Kartika Utami Dieke Aprianto Edi Santosa Eneng Tita Tosida Fani Susanti Hamzah, Rizki Maulana Heni Sulistiani Herfina Herfina Herlinda Herlinda Hermawan Hermawan Hifshan Riesvicky Iyan Mulyana Junhai Wang Kamel Mahdi Lita Karlitasari Lita Karlitasari Mehta, Abhishek Mubarok, Yasir Pahmi mulyono, andi Mutiara Prihatini Nofika, Benny Oktaviani, Nabila Oktaviani Palupiningsih, Pritasari Prajuhana Putra, Agung Pritasari Palupiningsih Putri Dwi Lestari Rahma, Yunita Reno Cahyo Hutomo Setiawan, Andrian Setiawansyah Setiawansyah Sitna Hajar Hadad Soewarto Hardhienata Sri Wahjuni Sudrajat, Cecep Suriansyah, Muhammad Iqbal Tjut Awaliyah Zuraiyah Wang, Junhai Yudhia Mulya Yuli Wahyuni Yuri Rahmanto Zebua, Mitra Darma Zolla Zolla