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All Journal Musamus Journal of Technology & Information Musamus Devotion Journal Brilliance: Research of Artificial Intelligence International Journal of Multidisciplinary Sciences and Arts
Zubaedah, Reza
Jurusan Sistem Informasi, Fakultas Teknik Universitas Musamus
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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PELATIHAN PENGGUNAAN APLIKASI PENDATAAN PENDUDUK PADA DISTRIK TANAH MIRING Reza Zubaedah; Nasra Pratama Putra; Stanly H. D Loppies
Musamus Devotion Journal Vol 3 No 2 (2021): Musamus Devotion Journal
Publisher : Musamus University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35724/mdj.v3i2.2701

Abstract

Tanah Miring District is a district in Merauke regency consisting of 2986 inhabitants and there are fourteen villages namely Yasa Mulya, Sumber Harapan, Waninggap Say, Waningap Miraf, Isano Mbias, New Life, Amunkay, Yaba Maru, Tambat Sarmayam Indah, Follow Bob, Soa, Bersehati, and Kamangi. At the District Office the manual data collection process so that errors often occur such as obstacles when searching for information about new residents, as well as residents who moved from the district. With the existence of KKN - TEMATIK UNMUS 2019 in the form of population data collection in the Tanah Miring District which is a technological development to facilitate population data collection so that the data collection process is no longer done manually. Constraints in the training district of using the application have not been implemented optimally so that the team of lecturers do the service by conducting training in the use of population data collection applications. Stages made by the team ie the trainees were given material about the application features and manuals and then the participants were given the opportunity to discuss the material that was given. Opportunities for questions and answers are given to clarify matters that are still in doubt. Participants practice to use the application. Participants are given further guidance to print reports. The results of the training are analyzed for further input and improvement. By conducting interviews with trainees as much as 80% of participants can understand the results of the training
PENGGUNAAN METODE EUCLIDEAN DISTANCE PADA CASE BASE REASONING UNTUK DIAGNOSIS DIABETES MELLITUS Reza Zubaedah
Musamus Journal of Technology & Information Vol 1 No 02 (2019)
Publisher : Musamus University

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Jenis kecerdasan buatan bagian dari sistem pakar yaitu Case Based Reasoning (CBR) yaitu metode membandingkan nilai kesamaan (similarity) antara data kasus baru dan data kasus yang tersimpan dalam basis kasus. Data pada pasien diabetes mellitus dapat digunakan kembali untuk dijadikan basis kasus dengan menggunakan beberapa atribut seperti identitas pasien, gejala yang dialami dan hasil tes gula darah. Perhitungan similarity dapat dilakukan dengan mencocokan data kasus dan data kasus baru menggunakan metode euclidean distance merupakan salah satunya. Untuk mengecek ke akuratan data yang digunakan pada casebase yang dibandingkan dengan data yang ada kasus yang baru bias memakai pengujian K fold -cross validation. K fold -cross validation akan menghilangkan bias pada data pada pengujian kali ini datakasus yang ada akan dibagi menjadi beberapa fold yang dipilih secara acak. Penelitian kali ini data akan dibagi menjadi 2, 3,5,7,10 dan 12 fold memperoleh nilai akurasi rata - rata sebesar 79.71% , 83.24%, 91.63%, 91.13%, 91.11% dan 91.14%
KLASIFIKASI TIPE DIABETES MELLITUS MENGGUNAKAN BAYESIAN MODEL Reza Zubaedah
Musamus Journal of Technology & Information Vol 2 No 1 (2019): Musamus Journal of Technologi & Information (MJTI)
Publisher : Musamus University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35724/mjti.v2i1.2451

Abstract

Tes gula darah sewaktu bisa digunakan untuk mengetahui seorang pasien terkena diabetes mellitus. Namun untuk mengetahui tipe jenisa diabetes dokter harus tahu gejala apa saja yang dialami oleh pasien. Setiap pasien yanbg menderita diabetes harus diketahui jenis tipe diabetes disebabkan penanagan yang akan diterima oleh pasien akan berbeda. Data kasus pasien diabetes mellitus bisa digunakan untuk mengklasifikasikan jenis diabetes mellitus dan digunakan kembali untuk ,mencocokan nilai kesamaan dengan data training yang telah diklasifikasi. Salah satu metode klasifikasi adalah bayesian clasification yang dapat digunakan untuk mengklasifikasi berdasarkan kelas – kelas yang telah ditentukan. Metode bayesian clasification akan digunakan untuk mengklasifikasikan tipe diabetes berdasarkan input gejala yang dialami pasien dan kelas yang telah ditentukan. Hasil penelitian menggunakan metode bayesian sebesar 89%.
Decision Support System for High School Entrance Selection Reza Zubaedah; Hertanto Prasetyo
Brilliance: Research of Artificial Intelligence Vol. 2 No. 2 (2022): Brilliance: Research of Artificial Intelligence, Article Research May 2022
Publisher : ITScience (Information Technology and Science)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v2i2.1566

Abstract

Currently, when going to high school, a selection will be made to select students based on zoning alone. Admissions using zoning are very detrimental to students who are outside the zoning but have better grades. Schools also want to have quality students however, the existence of government regulations makes it a trick if only zoning is used as a reference. The existence of a decision support system using the SAW method helps to make alternatives by having several criteria that are used as a benchmark when making a decision. In making this decision support system can display the results of student rankings based on SAW calculations and the development method using waterfalls and making this system web-based using PHP MySQL and HTML.This research produced a decision support system that can help make it easier for schools to determine the selection of new students based on the existing zoning system and produce rankings. The results of testing accuracy increased from 56% to 100%.
PENGGUNAAN METODE EUCLIDEAN DISTANCE PADA CASE BASE REASONING UNTUK DIAGNOSIS DIABETES MELLITUS Reza Zubaedah
Musamus Journal of Technology & Information Vol 1 No 02 (2019): Musamus Journal of Technologi & Information (MJTI)
Publisher : Musamus University

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Jenis kecerdasan buatan bagian dari sistem pakar yaitu Case Based Reasoning (CBR) yaitu metode membandingkan nilai kesamaan (similarity) antara data kasus baru dan data kasus yang tersimpan dalam basis kasus. Data pada pasien diabetes mellitus dapat digunakan kembali untuk dijadikan basis kasus dengan menggunakan beberapa atribut seperti identitas pasien, gejala yang dialami dan hasil tes gula darah. Perhitungan similarity dapat dilakukan dengan mencocokan data kasus dan data kasus baru menggunakan metode euclidean distance merupakan salah satunya. Untuk mengecek ke akuratan data yang digunakan pada casebase yang dibandingkan dengan data yang ada kasus yang baru bias memakai pengujian K fold -cross validation. K fold -cross validation akan menghilangkan bias pada data pada pengujian kali ini datakasus yang ada akan dibagi menjadi beberapa fold yang dipilih secara acak. Penelitian kali ini data akan dibagi menjadi 2, 3,5,7,10 dan 12 fold memperoleh nilai akurasi rata - rata sebesar 79.71% , 83.24%, 91.63%, 91.13%, 91.11% dan 91.14%
KLASIFIKASI TIPE DIABETES MELLITUS MENGGUNAKAN BAYESIAN MODEL Reza Zubaedah
Musamus Journal of Technology & Information Vol 2 No 01 (2019): Musamus Journal of Technology & Information (MJTI)
Publisher : Musamus University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35724/mjti.v2i01.2451

Abstract

Tes gula darah sewaktu bisa digunakan untuk mengetahui seorang pasien terkena diabetes mellitus. Namun untuk mengetahui tipe jenisa diabetes dokter harus tahu gejala apa saja yang dialami oleh pasien. Setiap pasien yanbg menderita diabetes harus diketahui jenis tipe diabetes disebabkan penanagan yang akan diterima oleh pasien akan berbeda. Data kasus pasien diabetes mellitus bisa digunakan untuk mengklasifikasikan jenis diabetes mellitus dan digunakan kembali untuk ,mencocokan nilai kesamaan dengan data training yang telah diklasifikasi. Salah satu metode klasifikasi adalah bayesian clasification yang dapat digunakan untuk mengklasifikasi berdasarkan kelas – kelas yang telah ditentukan. Metode bayesian clasification akan digunakan untuk mengklasifikasikan tipe diabetes berdasarkan input gejala yang dialami pasien dan kelas yang telah ditentukan. Hasil penelitian menggunakan metode bayesian sebesar 89%.
PELATIHAN PENGGUNAAN APLIKASI PENDATAAN PENDUDUK PADA DISTRIK TANAH MIRING Reza Zubaedah; Nasra Pratama Putra; Stanly H. D Loppies
Musamus Devotion Journal Vol 3 No 2 (2021): Musamus Devotion Journal
Publisher : Musamus University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35724/mdj.v3i2.2701

Abstract

Tanah Miring District is a district in Merauke regency consisting of 2986 inhabitants and there are fourteen villages namely Yasa Mulya, Sumber Harapan, Waninggap Say, Waningap Miraf, Isano Mbias, New Life, Amunkay, Yaba Maru, Tambat Sarmayam Indah, Follow Bob, Soa, Bersehati, and Kamangi. At the District Office the manual data collection process so that errors often occur such as obstacles when searching for information about new residents, as well as residents who moved from the district. With the existence of KKN - TEMATIK UNMUS 2019 in the form of population data collection in the Tanah Miring District which is a technological development to facilitate population data collection so that the data collection process is no longer done manually. Constraints in the training district of using the application have not been implemented optimally so that the team of lecturers do the service by conducting training in the use of population data collection applications. Stages made by the team ie the trainees were given material about the application features and manuals and then the participants were given the opportunity to discuss the material that was given. Opportunities for questions and answers are given to clarify matters that are still in doubt. Participants practice to use the application. Participants are given further guidance to print reports. The results of the training are analyzed for further input and improvement. By conducting interviews with trainees as much as 80% of participants can understand the results of the training
Decision Support System for Selecting House using Analythical Hierarchy Process Reza Zubaedah; Stanly Hence Dolfi Loppies; Fransiskus Xaverius
International Journal of Multidisciplinary Sciences and Arts Vol. 2 No. 1 (2023): International Journal of Multidisciplinary Sciences and Arts, Article June 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v2i1.2490

Abstract

Houses are the primary needs of everyone other than clothing and food needs. When consumers choose a house criteria that are used such as facilities, payment methods, type of house, land area, number of rooms, bathrooms, kitchens, living rooms, models, prices, developers and housing names. Sometimes choosing a house is difficult because of the many criteria that you always want to meet in accordance with consumer standards. The existence of a system is expected to help consumers provide alternatives in accordance with the choice of criteria as input and output systems in the form of alternative sequences of results from the system. The use of the Analytical Hierarchy Process (AHP) method solves a complex situation that is not structured into several components in a hierarchical arrangement, by giving subjective values ??about the relative importance of each variable, and determining which variables have the highest priority to influence the results. Data collection methods used are literature studies, interviews and observations. The test method is a test for interface functionality and application questionnaire. The results obtained by this system are in the form of a decision support system that can provide an alternative selection of houses that can be used as a comparison with the choice of criteria according to consumer
Co-Authors Fransiskus Xaverius Hertanto Prasetyo Nasra Pratama Putra Stanly H. D Loppies Stanly Hence Dolfi Loppies