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Implementation Of Multi Experts Multi Criteria Decision Making For Rehabilitation And Reconstruction Action After A Disaster Wibowo Almais, Agung Teguh; Sarosa, Moechammad; Muslim, Muhammad Aziz
MATICS Vol 8, No 1 (2016): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (727.982 KB) | DOI: 10.18860/mat.v8i1.3480

Abstract

Abstract— This article is aimed to propose a method which used Non-Numeric assessment that is Multi Experts Multi Criteria Decision Making (MEMCDM) in order to construct supporting decision system in composing rehabilitation and reconstruction action after disaster. Because in all this time “Perencanaan dan Pengendalian Penanganan Bencana (P3B)” surveyor team does not have clear standard criteria to execute the compiling rehabilitation and reconstruction action after disaster. Method Multi Experts Multi Criteria Decision Making (MEMCDM) step is to determine the alternative, assessment scale, criteria, criteria quality, criteria quality negation, criteria aggregation, and the qualification expert score. In the stage of expert qualification score for primary and secondary data is different. In secondary data, the qualification score is based on the usage of expert amount. Meanwhile, for secondary data, the expert qualification score is based on the criteria amount which is chosen by the user. Training data that has been processed using method Multi Experts Multi Criteria Decision Making (MEMCDM) can form a pattern system to assess damage and losses after natural disasters. There for it could facilitate a team of surveyors in assessing the damage and losses after natural disasters.
Pengujian Optimization dan Non-Optimization Query Metode Topsis untuk Menentukan Tingkat Kerusakan Sektor Bencana Alam Safitri, Annisa Heparyanti; Wibowo Almais, Agung Teguh; Syauqi, A'la; Melani, Roro Inda
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol 6 No 1 (2022)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v6i1.532

Abstract

Volume data yang sangat besar dari tim surveyor Perencanaan dan Pengendalian Penanganan Bencana(P3B) menciptakan masalah yang luas dan beragam sehingga dapat menghabiskan sumber daya sistem dan waktu pemrosesan yang terbilang lama. Oleh karena itu penelitian ini mengusulkan solusi dengan melakukan Optimasi query pada metode TOPSIS yang diimplementasikan pada sistem pendukung kepeutusan untuk menentukan tingkat kerusakan pasca bencana. Berdasarkan 3 kali uji coba dengan jumlah data yang berbeda-beda yaitu ujicoba ke-1 menggunakan 114 data, ujicoba ke-2 sebanyak 228 data dan ujicoba ke-3 menggunakan 334 data. Selain itu, setiap ujicoba dilakukan lagi pengukuran re-spons time sebanyak 3 kali maka didapatkan hasil rata-rata (average) response time dari masing-masing langkah metode TOPSIS. Didapati bahwa hasil dari tahapan perangkingan menggunakan query optimiza-tion lebih cepat 0.00076 dibandingakan dengan qury non-optimization. Sehingga dapat di simpulkan bahwa response time yang didapat query optimization pada setiap langkah metode TOPSIS pada sistem pendukung keputusan kerusakan sektor pasca bencana alam lebih kecil dibandingkan dengan response time pada query non-optimization.
MEDIA PROMOSI DESA WISATA MENGGUNAKAN DESA.ID DESA GAMPINGAN KECAMATAN PAGAK KABUPATEN MALANG Agung Teguh Wibowo Almais; Abd. Rouf; A'la Syauqi; Mochamad Imamudin; Dyah Febriantina Istiqomah; Akbar Roihan; Shinta Rizki Firdina Sugiono
J-Dinamika : Jurnal Pengabdian Masyarakat Vol 6 No 2 (2021): December
Publisher : Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/j-dinamika.v6i2.2692

Abstract

Di Gampingan terdapat suatu spot panjat tebing yang unik dan sangat menarik untuk dijadikan destinasi wisata alam yang cocok untuk dikunjungi yaitu “Lembah Kera”. Selain “Lembah Kera” juga terdapat tempat wisata lainnya di desa Gampingan yang menawarkan aneka masakan ikan air tawar segar yaitu Mahonian. Tetapi tempat destinasi wisata di desa Gampingan tersebut masih awam didengar oleh masyarakat atau wisatawan di luar Malang dan sekitarnya. Karena problem tersebut maka perlu dibuat suatu media promosi secara elektronik yang bisa menjangkau masyarakat lebih luas agar destinasi wisata desa Gampingan bisa terkenal dan makin banyak pengunjung yang mengunjungi tempat wisata di desa Gampingan. Media promosi yang lagi berkembang sekarang ini adalah melalui media social (facebook, twitter, instagram dan whatsapp) tetapi selain menggunakan social media seharusnya desa harus memiliki portal sendiri yang berisi informasi tentang wisata desa tersebut. Oleh karena itu perlu di generate sebuah website desa yang nama domain sudah mengikuti peraturan kominfo tentang penataan nama domain instansi penyelenggara negara, yang mengharuskan desa memiliki domain website sendiri yaitu desa.id. Dengan domain desa.id diharapkan agar nama domain lebih mudah diakses oleh publik dengan lebih singkat dan jelas. Selain itu juga menjadi bukti nyata, bahwa desa dapat maju, mandiri, dan unggul.
Manajemen Perangkat Lunak Aplikasi Sistem Informasi Berbasis Android Nisrina Darin Farhanah; Agung Teguh Wibowo Almais
Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Vol. 5 No. 2 (2022): Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI)
Publisher : Utility Project Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jikomsi.v5i2.268

Abstract

Perangkat lunak ialah istilah khusus yang digunakan untuk penyebutan data yang disimpan dan diformat secara digital. Dalam proses pembuatannya, perangkat lunak membutuhkan pengetahuan (teknik) khusus dikarenakan perangkat lunak yang tak berwujud. Manajemen perangkat lunak dapat dinyatakan sebagai metode pembangunan perangkat lunak yang paling tepat. Metode penelitian yang digunakan adalah studi pustaka dari beberapa jurnal karya pendahulu, wawancara dengan ahli, dan observasi. Hasil analisis dari manajemen perangkat lunak yang tepat akan menghasilkan konsep manajememen yang terbaik pada sebuah sistem. Dapat disimpulkan bahwa manajemen perangkat lunak dalam pembuatan sistem aplikasi terdiri dari rencana pengelolaan, pembangunan desain, dan evaluasi manajemen melalui pengelolaan sumber daya dan pembuatan kerangka kerja pengelolaan yang tepat sesuai kebutuhan aplikasi tanpa melupakan komponen-komponen penting penyusun sistem informasi berbasis android.
Implementasi Decision Support System Dynamic Menggunakan Weight Product Untuk Menentukan Uang Kuliah Tunggal Dyah Ayu Wiranti; Kurnia Siwi Kinasih; Ainafatul Nur Muslikah; Dyah Wardani; Agung Teguh Wibowo Almais
Jurnal Ilmiah Informatika Vol. 5 No. 1 (2020): Jurnal Ilmiah Informatika
Publisher : Department of Science and Technology Ibrahimy University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/jimi.v5i1.546

Abstract

Single tuition is the extension of the single tuition, which can be interpreted as a payment system made at the time of admission in both State and private colleges in Indonesia. Where this single tuition can provide benefits for the equitable of each student and help the students who are less able in terms of the economy that is certainly derived from the underprivileged family. In the calculation process determines the single tuition money each student needs a long process and time. So, there is an idea to implement a Decision Support System Dynamic (DSSD) so that at the time of determination of single tuition can be evenly and by the actual situation. One method that can be used on DSSD is the Weighted Product (WP) method. By implementing the method of WP combined with the concept of DSSD, then generated values of confusion matrix (recall, precision, f-measure, and accuracy) obtained by looking for the value of comparison between test data with pattern data. Obtained confusion matrix value with system testing and get the results Precision 88.89%, Recall 82.76%, Accuracy 77.14%, F-Measure 85.71%.
PENERAPAN DECISION SUPPORT SYSTEM DYNAMIC MENGGUNAKAN SIMPLE ADDICTIVE WEIGHTING DALAM PENENTUAN PEGAWAI TERBAIK Tanti Rismawati; Muhammad Aji Pangestu; Agung Teguh Wibowo Almais
Jurnal Ilmiah Informatika Vol. 5 No. 1 (2020): Jurnal Ilmiah Informatika
Publisher : Department of Science and Technology Ibrahimy University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/jimi.v5i1.547

Abstract

Lots of applications or programs that are very useful to simplify human work. This includes applications that are made within a company. A company needs an intelligent system or an agent that controls the company's system. In a company has employees who work. This research will discuss the Dynamic Decision Support System in determining the best employees using one of the web-based Multi-Criteria Decision Making methods, which is Simple Additive Weighting (SAW). By using 2 types of data namely pattern data and test data. The data inputted were 15 data consisting of 10 test data and 5 pattern data. Then a confusion matrix can be obtained in the form of an accuracy value of 25%, a precision of 100%, a recall of 14%, and an F Measure of 24.5%.
Decision Support System dalam Menentukan Mahasiswa Bermasalah Menggunakan Metode Topsis Adinda Dhea Pramitha; Anis Fatul Fu'adah; Agung Teguh Wibowo Almais; Laela Nurul Qomariyah
Jurnal Ilmiah Informatika Vol. 5 No. 1 (2020): Jurnal Ilmiah Informatika
Publisher : Department of Science and Technology Ibrahimy University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/jimi.v5i1.550

Abstract

At present many old semester students are starting to be undisciplined in attending lectures, this is due to the increasing burden of their assignments causing the enthusiasm of students to relax. This can create serious problems in the department because it can affect the accreditation level of the department. The purpose of this journal, which is to help the department admins to determine students who have problems in the field of lectures, so that the department can find out how many problem students can affect the accreditation of majors. In this journal, we implement the Decision Support System for manufacturing the system. With the TOPSIS method for calculations on the system, and using the Confusion Matrix for testing the system. From testing using confusion matrix, it can be concluded that precision produces 75%, recall produces 75%, accuracy produces 73%, and f-measure produces 75%. This shows that the system has a pretty good ability because it has exceeded the value of 70%.
Smart Assessment menggunakan Backpropagation Neural Network Agung Teguh Wibowo Almais; Cahyo Crysdian; Khadijah Fahmi Hayati Holle; Akbar Roihan
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 21 No 3 (2022)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (628.717 KB) | DOI: 10.30812/matrik.v21i3.1469

Abstract

Penerapan scraping dan Backpropagation Neural Network dapat menjadikan penilaian Self- Assessment Questionnaire (SAQ) website Pemerintah Daerah Provinsi Jawa Timur lebih smart jika dibandingkan dengan model assessment yang sudah ada. Langkah awal yaitu melakukan scraping website Pemerintah Daerah Provinsi Jawa Timur untuk mendapatkan nilai SAQ. Hasil scraping tersebut akan digunakan sebagai data uji pada metode Backpropagation Neural Network, kemudian hasil data uji akan di proses menggunakan 4 jenis model data yang berbeda-beda dari segi jumlah iterasi dan hidden layer untuk mendapatkan akurasi terbaik. Pada model data A menggunakan iterasi 1000 dan 5 hidden layer menghasilkan nilai Mean Squared Error (MSE) 0,0117, Mean Absolute Percent Error (MAPE) 39,36% dan Akurasi 60.64%. Model data B menggunakan iterasi 1000 dan 7 hidden layer menghasilkan nilai MSE 0,0087, MAPE 29,49% dan Akurasi 70,50%. Model data C dengan menggunakan iterasi 2000 dan 9 hidden layer menghasilkan nilai MSE 0,0064, MAPE 24,46% dan Akurasi 75,53%. Model data D menggunakan iterasi 2000 dan 9 hidden layer menghasilkan nilai MSE 0,0036, MAPE 18,71% dan Akurasi 81,28%. Dari hasil ujicoba tersebut bahwa model data D yang menggunakan iterasi 2000 dan 9 hidden layer menghasilkan tingkat akurasi yang terbaik sehingga model data D dapat dijadikan acuan hasil penilaian website Pemerintah Daerah Provinsi Jawa Timur tahun 2021.
Prediction of State Civil Apparatus Performance Allowances Using the Neural Network Backpropagation Method Puan Maharani Kurniawan; Agung Teguh Wibowo Almais; M. Amin Hariyadi; M. Ainul Yaqin; Suhartono Suhartono
JOIV : International Journal on Informatics Visualization Vol 7, No 3 (2023)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.3.1698

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Performance allowance is a form of appreciation given by an agency to its human resources. The Office of the Ministry of Religion of Batu City provides performance allowances to civil servants who work in the agency. Several things that affect the provision of performance allowances, such as grade, deduction, taxable income, income tax, and total tax, are used in this study to produce the total gross performance allowances and total performance allowances received. Based on the data obtained, there are some missing data from the parameters of taxable income, income tax, and total tax. This study aims to predict performance allowance when there is missing data. The method used is Neural Network Backpropagation. This study uses 480 data with split data ratios of 50:50, 60:40, 70:30, and 80:20, with epochs 40,000 and a learning rate 0,9. Four types of models used in this study are distinguished based on the number of hidden layers and epochs used. Model A uses two hidden layers to produce the highest accuracy with a 50:50 data split ratio of 65,16%. Model B uses four hidden layers to produce the highest accuracy with a 50:50 data split ratio of 69,34%. Model C uses six hidden layers to produce the highest accuracy with a 50:50 data split ratio of 68,18%. Model D uses eight hidden layers to produce the highest accuracy with a 50:50 data split ratio of 70,90%.
Klasifikasi Tingkat Kerusakan Sektor Pasca Bencana Alam Menggunakan Metode MULTIMOORA Berbasis Web Aniss Fatul Fu'adah; Agung Teguh Wibowo Almais; A’la Syauqi
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 8 No. 3 (2023): September 2023
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2023.8.3.222-230

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During 2020-2021, 10,152 disasters occurred in Indonesia, significantly impacting the affected sectors. The recovery of these sectors needs to be done as quickly as possible to maintain human survival. This study aims to analyze the factors that affect sector damage after natural disasters in Indonesia and measure the classification accuracy. The data used in this research is data from the Regional Disaster Management Agency of Malang City in 2020. This study developed a web-based Decision Support System (DSS) using The Multiplicative Form Integrated MOORA (MULTIMOORA) method. This method is the result of the development of the MOORA method by adding a complete multiplication form to the MOORA method. In this study, the MULTIMOORA method was used to classify the level of damage to sectors after natural disasters. The results showed that using the MULTIMOORA method in this DSS resulted in an accuracy rate of 84% and was included in the good enough category.