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All Journal Jurnal Nasional Komputasi dan Teknologi Informasi TIN: TERAPAN INFORMATIKA NUSANTARA
Siti Ramadhani
Universitas Islam Negeri Sultan Syarif Kasim, Riau
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Penerapan Metode Simple Additive Weighting (SAW) Dalam Sistem Pengukuran Tingkat Kepuasan Terhadap Kualitas Kinerja Sekolah Dimas Rifqi Ekaryanto; Elin Haerani; Fitri Wulandari; Siti Ramadhani
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 5, No 2 (2022): April 2022
Publisher : Program Studi Teknik Informatika, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v5i2.4184

Abstract

Abstrak - SMK Telkom adalah sekolah kejuruan swasta di Pekanbaru yang mempunyai banyak prestasi, baik dari prestasi akademik maupun prestasi non akademik. Tentunya untuk mencapai prestasi tersebut dibutuhkan adanya proses evaluasi terhadap kinerja sekolah. Pengukuran dilakukan untuk memberikan evaluasi guna meningkatkan kualitas pendidikan dan kualitas pelayanan yang terbaik serta bisa bersaing dengan sekolah lainnya. Untuk menentukan proses pengukurann dibutuhkan enam kriteria, yaitu tata usaha,  tenaga kependidikan, humas,  sarana dan prasarana, pembelajaran dan tenaga pendidik dengan bobot yang sudah di tentukan pada setiap kriteria. Responden dari penilaian terhadap kinerja sekolah adalah Orang Tua, Siswa, Guru, Pegawai dan Kepala Sekolah.Penelitian yang dilakukan menggunakan metode Simple Additive Weighting (SAW) untuk mendapatkan pengukuran terbaik berdasarkan kriteria yang sudah ditentukan. Sistem yang dibuat adalah perangkat lunak berbasis web yang dibuat menggunakan PHP dan MySQL sebagai database. Sistem ini diuji menggunakan metode Blackbox untuk menguji sistem berjalan dengan hasil 100%. Berdasarkan hasil pengujian User Acceptance Testing (UAT) dan Blackbox mendapatkan hasil skor 4,5 dari 5,00 “Sangat Setuju”.Kata kunci: Kinerja, Kriteria, Pendidikan, Pengukuran, Simple Additive Weighting                                                                                                                                  Abstract - Telkom Vocational School is one of the private vocational schools in Pekanbaru which has many achievements, both academic and non-academic. Of course, to achieve this achievement, a school performance evaluation process is needed. Measurements are carried out to provide evaluations in order to improve the quality of education and the best quality of service and be able to compete with other schools. To determine the measurement process, six criteria are needed, namely administration, education staff, public relations, facilities and infrastructure, educational staff and teaching staff with a predetermined weight on each criterion. Respondents from the school performance assessment are Parents, Students, Teachers, Employees and Principals. The study was conducted using the Simple Additive Weighting (SAW) method to obtain the best measurement based on predetermined criteria. The system created is a web-based software made using PHP and MySQL as the database. This system was tested using the Blackbox method to test the system running with 100% results. Based on the results of User Acceptance Testing (UAT) and Blackbox, the results obtained a score of 4.5 out of 5.00 "Strongly Agree".Keywords: Criteria, Education, Measurement, Performance, Simple Additive Weighting 
Penerapan Metode Simple Additive Weighting (SAW) Dalam Sistem Pengukuran Tingkat Kepuasan Terhadap Kualitas Kinerja Sekolah Dimas Rifqi Ekaryanto; Elin Haerani; Fitri Wulandari; Siti Ramadhani
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 5, No 2 (2022): April 2022
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v5i2.4184

Abstract

Abstrak - SMK Telkom adalah sekolah kejuruan swasta di Pekanbaru yang mempunyai banyak prestasi, baik dari prestasi akademik maupun prestasi non akademik. Tentunya untuk mencapai prestasi tersebut dibutuhkan adanya proses evaluasi terhadap kinerja sekolah. Pengukuran dilakukan untuk memberikan evaluasi guna meningkatkan kualitas pendidikan dan kualitas pelayanan yang terbaik serta bisa bersaing dengan sekolah lainnya. Untuk menentukan proses pengukurann dibutuhkan enam kriteria, yaitu tata usaha,  tenaga kependidikan, humas,  sarana dan prasarana, pembelajaran dan tenaga pendidik dengan bobot yang sudah di tentukan pada setiap kriteria. Responden dari penilaian terhadap kinerja sekolah adalah Orang Tua, Siswa, Guru, Pegawai dan Kepala Sekolah.Penelitian yang dilakukan menggunakan metode Simple Additive Weighting (SAW) untuk mendapatkan pengukuran terbaik berdasarkan kriteria yang sudah ditentukan. Sistem yang dibuat adalah perangkat lunak berbasis web yang dibuat menggunakan PHP dan MySQL sebagai database. Sistem ini diuji menggunakan metode Blackbox untuk menguji sistem berjalan dengan hasil 100%. Berdasarkan hasil pengujian User Acceptance Testing (UAT) dan Blackbox mendapatkan hasil skor 4,5 dari 5,00 “Sangat Setuju”.Kata kunci: Kinerja, Kriteria, Pendidikan, Pengukuran, Simple Additive Weighting                                                                                                                                  Abstract - Telkom Vocational School is one of the private vocational schools in Pekanbaru which has many achievements, both academic and non-academic. Of course, to achieve this achievement, a school performance evaluation process is needed. Measurements are carried out to provide evaluations in order to improve the quality of education and the best quality of service and be able to compete with other schools. To determine the measurement process, six criteria are needed, namely administration, education staff, public relations, facilities and infrastructure, educational staff and teaching staff with a predetermined weight on each criterion. Respondents from the school performance assessment are Parents, Students, Teachers, Employees and Principals. The study was conducted using the Simple Additive Weighting (SAW) method to obtain the best measurement based on predetermined criteria. The system created is a web-based software made using PHP and MySQL as the database. This system was tested using the Blackbox method to test the system running with 100% results. Based on the results of User Acceptance Testing (UAT) and Blackbox, the results obtained a score of 4.5 out of 5.00 "Strongly Agree".Keywords: Criteria, Education, Measurement, Performance, Simple Additive Weighting 
Deteksi Anomali pada Citra X-ray Dada Menggunakan Variational Autoencoder dengan Skema Sequential Hyperparameter Optimization Diki Aulio Fransisko; Febi Yanto; Benny Sukma Negara; Siti Ramadhani; Reski Mai Candra
TIN: Terapan Informatika Nusantara Vol 7 No 3 (2026): August 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i3.10864

Abstract

The limited availability of labeled medical images remains a major challenge in developing reliable deep learning-based disease detection systems. Conventional classification approaches generally require a large amount of abnormal data, whereas medical image annotation is time-consuming, costly, and highly dependent on radiological expertise. This study proposes an unsupervised anomaly detection model for chest X-ray images using a Variational Autoencoder (VAE), in which only normal images are utilized during the training process. The experiments were conducted on the COVID-19-Pneumonia-Normal Chest X-ray Images dataset, consisting of 5,228 images categorized into normal, pneumonia, and COVID-19 classes. The proposed framework includes image preprocessing, baseline VAE construction, sequential hyperparameter optimization, Beta-VAE implementation, and model evaluation using Accuracy, Precision, Recall, F1-Score, and the Area Under the Receiver Operating Characteristic Curve (AUROC). Experimental results demonstrate that the optimized model outperformed the baseline model, achieving an Accuracy of 97.50%, Precision of 96.32%, Recall of 100%, F1-Score of 98.12%, and an AUROC of 0.9999. These findings indicate that hyperparameter optimization and appropriate β coefficient selection improve latent representation learning, leading to more effective discrimination between normal and abnormal chest X-ray images. Therefore, the proposed approach has the potential to serve as an artificial intelligence-based early screening tool for chest radiograph analysis, particularly in scenarios where labeled medical data are limited.
Co-Authors Benny Sukma Negara Diki Aulio Fransisko Dimas Rifqi Ekaryanto Elin Haerani Febi Yanto Fitri Wulandari Reski Mai Candra