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All Journal Pixel : Jurnal Ilmiah Komputer Grafis Elkom: Jurnal Elektronika dan Komputer Jurnal Ilmiah Media Sisfo
Setyawan Wibisono
unisbank semarang
Computer Science & IT Education

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Sistem Penunjang Keputusan Rekomendasi Kelulusan dan Pemeringkatan Santri Menggunakan Metode AHP-TOPSIS Muhammad Auva Al-Marom; Setyawan Wibisono
Jurnal Ilmiah Media Sisfo Vol 15 No 1 (2021): Jurnal Ilmiah Media Sisfo
Publisher : LPPM STIKOM Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/mediasisfo.2021.15.1.998

Abstract

Pondok pesantren merupakan salah satu lembaga pendidikan Islam yang ada di Indonesia. Dalam proses penilaian kelulusan dilakukan oleh ustadz penguji dan menggunakan cara manual sehingga bersifat tidak pasti yang akan berdampak pada kelulusan santri. Maka dibutuhkan suatu sistem yang membantu untuk menentukan kelulusan dan pemeringkatan dengan menggunakan kombinasi metode AHP (Analytical Hierarchy Process) dan TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). Pada AHP terdapat empat tahapan yaitu: menentukan kriteria, menentukan tabel perbandingan berpasangan, menghitung bobot prioritas dan menghitung konsistensi kriteria. Kriteria yang digunakan, mengacu pada target kelulusan pondok pesantren sesuai dengan kurikulum khusus pesantren yaitu hafalan juz 30 dan surat pilihan, membaca kitab Taqrib, menjadi imam, memimpin tahlil dan percakapan bahasa Arab. AHP digunakan untuk membantu menyeleksi kandidat atau hanya mengurutkan prioritas dari beberapa kandidat. Untuk menentukan tabel perbandingan berpasangan terlebih dahulu melakukan perbandingan kriteria guna menghasilkan bobot relatif antar kriteria maupun alternatif. Implementasi TOPSIS meliputi mencari data alternatif, pembobotan alternatif, normalisasi data, normalisasi berbobot, menentukan solusi ideal positif dan negatif, menghitung jarak ideal, sehingga menghasilkan perangkingan. Sistem pendukung keputusan ini menghasilkan nilai preferensi tertinggi yaitu 0,860862596 sehingga dapat digunakan untuk merekomendasikan kelulusan dan pemeringkatan santri pondok pesantren Hajroh Basyir Pati berdasarkan kriteria yang telah ditetapkan
Deteksi Dini Varian Covid-19 Dengan Metode CBR-AHP Dan Sorgenfrei Mohamad Riza Darmawan; Setyawan Wibisono
Pixel :Jurnal Ilmiah Komputer Grafis Vol 15 No 1 (2022): Vol 15 No 1 (2022): Jurnal Ilmiah Komputer Grafis
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/pixel.v15i1.747

Abstract

The case fatality rate caused by Covid-19 in Indonesia is around 2.9%. The death rate by age group is from all Covid-19 patients who died, including 0.5% aged 0-5 years, 0.5% aged 6-18 years, 2.8% aged 19-30 years, 12.7 % were aged 31–45 years, 36.8% were aged 46–59 years, and 46.7% were aged 60 years and over. With the large number of cases that occurred in Indonesia, it turned out to be due to the lack of proper handling of the early symptoms of the Covid-19 virus. To overcome this, it is needed as a tool for early detection of the Covid-19 variant by using the CBR-AHP expert system with the Sorgenfrei algorithm. The results of the consultation for the early detection of the Covid-19 variant were obtained from the highest similarity value of Sorgenfrei. Of all the variants found above, the highest similarity value of Sorgenfrei is Omicron with a similarity of 1,000. Omicron has the highest value because it has a value of a, which is the same symptom between old cases and large new cases.
Sistem Penunjang Keputusan Rekomendasi Kelulusan dan Pemeringkatan Santri Menggunakan Metode AHP-TOPSIS Muhammad Auva Al-Marom; Setyawan Wibisono
Jurnal Ilmiah Media Sisfo Vol 15 No 1 (2021): Jurnal Ilmiah Media Sisfo
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/mediasisfo.2021.15.1.998

Abstract

Pondok pesantren merupakan salah satu lembaga pendidikan Islam yang ada di Indonesia. Dalam proses penilaian kelulusan dilakukan oleh ustadz penguji dan menggunakan cara manual sehingga bersifat tidak pasti yang akan berdampak pada kelulusan santri. Maka dibutuhkan suatu sistem yang membantu untuk menentukan kelulusan dan pemeringkatan dengan menggunakan kombinasi metode AHP (Analytical Hierarchy Process) dan TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). Pada AHP terdapat empat tahapan yaitu: menentukan kriteria, menentukan tabel perbandingan berpasangan, menghitung bobot prioritas dan menghitung konsistensi kriteria. Kriteria yang digunakan, mengacu pada target kelulusan pondok pesantren sesuai dengan kurikulum khusus pesantren yaitu hafalan juz 30 dan surat pilihan, membaca kitab Taqrib, menjadi imam, memimpin tahlil dan percakapan bahasa Arab. AHP digunakan untuk membantu menyeleksi kandidat atau hanya mengurutkan prioritas dari beberapa kandidat. Untuk menentukan tabel perbandingan berpasangan terlebih dahulu melakukan perbandingan kriteria guna menghasilkan bobot relatif antar kriteria maupun alternatif. Implementasi TOPSIS meliputi mencari data alternatif, pembobotan alternatif, normalisasi data, normalisasi berbobot, menentukan solusi ideal positif dan negatif, menghitung jarak ideal, sehingga menghasilkan perangkingan. Sistem pendukung keputusan ini menghasilkan nilai preferensi tertinggi yaitu 0,860862596 sehingga dapat digunakan untuk merekomendasikan kelulusan dan pemeringkatan santri pondok pesantren Hajroh Basyir Pati berdasarkan kriteria yang telah ditetapkan
Implementasi AHP-WASPAS Untuk Pemilihan Internet Service Provider (ISP) dirgantara krisna gaesa; Setyawan Wibisono
Elkom : Jurnal Elektronika dan Komputer Vol 16 No 1 (2023): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i1.992

Abstract

Internet Service Provider (ISP) is a company that provides internet services. The ISP network is a national and international scale network so that customers can be connected globally. There are many factors that must be considered in selecting an ISP, making choosing an ISP a difficult task. Factors that influence ISP selection include cost, bandwidth, coverage area and type of connection. ISP providers offer a variety of advantages that make it difficult for customers to choose the right provider. The method applied in determining ISP providers is the AHP method used for weighting criteria while the WASPAS method is used for evaluating ISP providers with the criteria of cost, bandwidth, coverage area and type of connection. The rating process using the WASPAS method uses four assessment criteria, namely cost with a weight of 0.54, bandwidth with a weight of 0.38, coverage area with a weight of 0.05 and type of connection with a weight of 0.03. The final results of the ranking show that ISPs with low cost, large bandwidth and wide coverage areas will make these ISPs the best choice, this is because the criteria for cost, bandwidth and coverage area have high weight. Conversely, ISPs with high costs and small coverage areas will be the worst choices in the ranking list.
Implementasi AHP-WASPAS Untuk Pemilihan Internet Service Provider (ISP) dirgantara krisna gaesa; Setyawan Wibisono
Elkom : Jurnal Elektronika dan Komputer Vol 16 No 1 (2023): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i1.992

Abstract

Internet Service Provider (ISP) is a company that provides internet services. The ISP network is a national and international scale network so that customers can be connected globally. There are many factors that must be considered in selecting an ISP, making choosing an ISP a difficult task. Factors that influence ISP selection include cost, bandwidth, coverage area and type of connection. ISP providers offer a variety of advantages that make it difficult for customers to choose the right provider. The method applied in determining ISP providers is the AHP method used for weighting criteria while the WASPAS method is used for evaluating ISP providers with the criteria of cost, bandwidth, coverage area and type of connection. The rating process using the WASPAS method uses four assessment criteria, namely cost with a weight of 0.54, bandwidth with a weight of 0.38, coverage area with a weight of 0.05 and type of connection with a weight of 0.03. The final results of the ranking show that ISPs with low cost, large bandwidth and wide coverage areas will make these ISPs the best choice, this is because the criteria for cost, bandwidth and coverage area have high weight. Conversely, ISPs with high costs and small coverage areas will be the worst choices in the ranking list.
KLASIFIKASI JENIS JAMUR MENGGUNAKAN METODE NEURAL NETWORK DENGAN FITUR INCEPTION-V3 Okka Hermawan Yulianto; Setyawan Wibisono
Elkom : Jurnal Elektronika dan Komputer Vol 16 No 2 (2023): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i2.1281

Abstract

Mushrooms are very diverse with characteristics of each type, there are 1,433,800 types of mushrooms that have not been recognized. In this study, researchers used the Neural Network and Deep Learning Inception V3 methods as a feature extraction process in images to classify mushroom images based on genus with the Orange Data Mining application. There are 9 genera of mushrooms used in this study, namely Agaricus, Amanita, Boletus, Cortinarius, Entoloma, Hygrocybe, Lactarius, Russula, and Suillus. The total dataset used is 2,700, with 300 images for each genus. The test uses the cross-validation method which is applied to the confusion matrix to get precision, recall, F1-score, and accuracy values. In this study, the final classification results were obtained with an accuracy of 82.5% and the genus Boletus mushroom obtained the best results with an accuracy of 98.9%.
Co-Authors dirgantara krisna gaesa Mohamad Riza Darmawan Muhammad Auva Al-Marom Okka Hermawan Yulianto