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All Journal Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial Jurnal Teknik Komputer AMIK BSI JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Pilar Nusa Mandiri Informatics for Educators and Professional : Journal of Informatics JITK (Jurnal Ilmu Pengetahuan dan Komputer) EQIEN - JURNAL EKONOMI DAN BISNIS INTERACTION: Jurnal Pendidikan Bahasa Jurnal Infortech Jurnal Info Sains : Informatika dan Sains SPEED - Sentra Penelitian Engineering dan Edukasi Informatics and Computer Engineering Journal Journal of Artificial Intelligence and Engineering Applications (JAIEA)

Robi Aziz Zuama

Universitas Bina Sarana Informatika

Author-ID : 2550287

Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

Published : 15 Documents Claim Missing Document

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Pembelajaran Mesin untuk diagnosis tingkat kerusakan hati akibat hepatitis C - UBSI, Robi Aziz Zuama
SPEED - Sentra Penelitian Engineering dan Edukasi Vol 13, No 3 (2021): Speed Juli 2021
Publisher : APMMI - Asosiasi Profesi Multimedia Indonwsia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (234.333 KB)

Abstract - This paper describes how machine learning in the medical field for the diagnosis of liver damage due to hepatitis C, the severity of hepatitis C can be divided into hepatitis, fibrosis and cirrhosis. An automated classification method is proposed for diagnosis using a series of commonly used diagnostic test data, models such as Support Vector Machine (SVM), Random Forest (RF), Naive Bayes, Logistic Regression and kNN have been proposed in this task. The model is validated using 10-fold validation to be evaluated using a confusion matrix and find out which method is the best. We found that SVM is the best model with an accuracy value of 0.883, the accuracy is quite good compared to other models, this study can be a reference for the development of an automated model for the diagnosis of liver damage due to hepatitis C.Keyword: Hepatitic C, Machine Learning, hepatitic, fibrosis, cirrhosis,Abstrak - Makalah ini menjelaskan bagaimana machine learning dalam bidang medis untuk diagnosis tingkat kerusakan hati akibat hepatitis C, tingkat keparahan akibat hepatitis c dapat dibedakan menjadi hepatitis, fibrosis dan cirrhosis. Metode klasifikasi otomatis diusulkan untuk mendiagnosis dengan menggunakan serangkaian data tes diagnosis yang umum digunakan, model seperti Support Vector Machine (SVM), Random Forest (RF), Naive Bayes, Logistic Regression dan kNN telah diusulkan dalam tugas ini. Model di validasi menggunakan 10-fold validation untuk dievaluasi menggunakan confusion matrix dan menemukan metode mana yang terbaik. Kami menemukan bahwa SVM menjadi model yang terbaik dengan nilai akurasi 0,883, akurasi cukup baik dibandingkan model lainnya, penelitian ini dapat menjadi acuan untuk pengembangan model otomatisasi diagnosis tingkat kerusakan hati akibat hepatitis C.Keyword: Hepatitic C, Machine Learning, hepatitic, fibrosis, cirrhosis,

Employee Performance Apparaisal Using Decision Support System by AHP and TOPSIS Methods Achmad Baroqah Pohan; Sofian Wira Hadi; Syaifur Rahmatullah; Robi Aziz Zuama; Achmad Rifai; Deni Gunawan
JURNAL TEKNIK KOMPUTER Vol 7, No 1 (2021): JTK-Periode Januari 2021
Publisher : Universitas Bina Sarana Informatika

During this time the performance appraisal of PT. Injep Inti Cemerlang has not been implemented optimally, especially in employee performance appraisal. Performance appraisal so far is only determined from the results, there are no clear appraisal criteria. Based on this reason, a decision support system is needed to help find the best alternative for the employees selection. In this research a decision support system for employee performance appraisal will be developed based on Attitude, Responsibility, Attendance, Discipline and Collaboration. This research aims to design a decision support system for employee performance appraisal using data collection methods by observation, interviews and giving questionnaires to employees of PT. Injep Inti Cemerlang. The data collected is carried out the process of analyzing data and looking for weighting values using the AHP method and for ranking using the TOPSIS method, where each criterion is appraisal factors and alternatives in this case employees are compared the criteria that have been weighted through the process of calculating the AHP and TOPSIS method starting from giving the weighting of criteria by calculating with Ms. Excel and calculating with Expert Choice software. The results have been obtained from weighting the next ranking by the TOPSIS method. thus providing a value output that results in a system that employees appraisal. This decision support system helps the employee performance apprasial at PT. Injep Inti Cemerlang in determining the employee who has the best performance

Perancangan Sistem Informasi Pengolahan Data Member Pada Rai Fitness Sukabumi Yuri Yuliani; Yuri Rahayu; susilawati susilawati; Robi Aziz Zuama
Informatics and Computer Engineering Journal Vol 1 No 2 (2021): Periode Agustus 2021
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) Universitas Bina Sarana Informatika

The processing of member data at Rai Fitness Sukabumi is still done manually and some problems in the data processing system used today include the data entry process that is less efficient and optimal and the recording of acceptance and addition of members is still not recorded and good. This final research method is to conduct research, observation, interviews with the Front Office Rai Fitness Sukabumi, and literature study. Then the system design is carried out using UML (Unified Modeling Language) Providing convenience for the Front Office in the process of inputting data on registration and adding members, facilitating the performance of the Front Office in making journals and reports on registration, and adding members. The establishment of a data recording application that is stored properly and neatly in one database. Information system design. Member data processing for registration and member extension aims to facilitate the Front Office in carrying out data processing on registration and addition of members. Report makers are needed faster than before, namely, presenting the report requires more time and accuracy. Keywords : Information System Design, Member Data Processing

Implementasi Simple Additive Weighting untuk Rekomendasi Pemilihan Jurusan pada Sekolah Menengah Kejuruan Robi Aziz Zuama; irwan agus sobari
Jurnal Infortech Vol 1, No 2 (2019): Desember 2019
Publisher : Universitas Bina Sarana Informatika

Pemilihan jurusan yang tepat bagi siswa baru akan berdampak besar pada kemampuan siswa itu sendiri. Pemilihan jurusan menjadi sangat penting, karena siswa dapat menentukan jurusan yang akan membawa ke passion-nya di masa depan. Dalam Memilih jurusan, biasanya siswa bertanya kepada yang bukan ahli pada bidang tersebut seperti orang tua, teman sebaya dan orang-orang terdekat atau bahkan menentukan jurusan dengan berlandaskan kepopuleran suatu jurusan, padahal jurusan tersebut bukan menjadi passion calon siswa tersebut. Metode simple adaptive weighting dapat membantu siswa membuat rekomendasi jurusan yang tepat berdasarkan kriteria-kriteria terukur dari kemampuan siswa itu sendiri. penelitian ini mengusulkan metode Simple Additive Weighting (SAW) karena perhitungan yang simple dan berlandaskan bobot kemampuan siswa itu sendiri. Hasilnya siswa mendapatkan rekomendasi-rekomendasi dari hasil perhitungan bobot dari setiap alternatif jurusan sesuai dengan kemampuan siswa itu sendiri, dengan metode ini siswa tidak lagi salah mengambil jurusan

DETEKSI OTOMATIS KANKER PAYUDARA MENGGUNAKAN METODE MORPHOLOGICAL RECONSTRUCTION DENGAN K-MEANS CLUSTERING PADA CITRA MRI Gunawan Gunawan; Robi Aziz Zuama; Ramdhan Saepul Rohman; Hamdun Sulaiman; Muhamad Abdul Ghani
Swabumi Vol 7, No 1 (2019): Volume 7 Nomor 1 Tahun 2019
Publisher : Universitas Bina Sarana Informatika Kota Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/swabumi.v7i1.5662

AbstractBreast cancer is still a major health problem for women around the world, the population of Indonesia is 237.8 million in 2010 and detected by cancer patients is estimated at 1.02 million. The purpose of this study is to reconstruct the image of the MRI scan to clarify the object of cancer so that it can be more easily identified whether a person really has breast cancer or not, in this study using the morphological reconstruction method with the k-means algorithm to segment the image, the results obtained sensitivity of around 92.86%, specificity of 78.57%, and accuracy of 85.71%. Keywords - cancer, morphological reconstruction, k-means, image. AbstrakKanker payudara masih menjadi masalah kesehatan utama bagi wanita di seluruh dunia, Jumlah penduduk Indonesia 237,8 juta jiwa pada tahun 2010 dan terdeteksi penderita kanker diperkirakan 1,02 juta jiwa. Tujuan penelitian ini untuk merekonstruksi citra dari hasil scan MRI untuk memperjelas objek kanker sehingga dapat lebih mudah diidentifikasi apakah seseorang benar-benar terkena kanker payudara atau tidak, dalam penelitian ini menggunakan metode rekonstuksi morfologi dengan algoritma k-means untuk melakukan segmentasi citra, hasilnya didapatkan nilai sensitivitas sekitar 92,86%, spesifisitas 78,57%, dan akurasi 85,71%.Kata kunci – kanker, rekonstruksi morfologi, k-means, citra.

Analisis Performa Algoritma Machine Learning pada Prediksi Penyakit Cerebrovascular Accidents Robi Aziz Zuama; Syaifur Rahmatullah; Yuri Yuliani
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 1 (2022): Januari 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i1.3488

Cerebrovascular Accidents (stroke) are a disease that threatens and causes death and disability and disability in the world, in Indonesia the number of people affected by stroke is increasing every year. Stroke can be prevented by adopting a healthy lifestyle, eating nutritious food, and doing physical activity. The purpose of this study is to create an effective stroke prediction model, the system uses parameters from lifestyle factors, controllable factors such as medical risk factors, and uncontrollable factors. Four classification algorithms are proposed, namely multi-layer perceptron, KNN, Decision Tree, and Random Forest. The results show that the classification algorithm can work effectively by producing a perfect score of 99.99% accuracy at the 10K-Fold Validation level of validation.

ANALISIS PERFORMA ALGORITMA NAIVE BAYES PADA DETEKSI OTOMATIS CITRA MRI Fajar Akbar; Amin Nur Rais; Irwan Agus Sobari; Robi Aziz Zuama; Biktra Rudiarto
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 5 No 1 (2019): JITK Issue August 2019
Publisher : LPPM Nusa Mandiri

The brain in humans becomes part of the central nervous system of the human body. The use of imaging with MRI is one that can be used as a first step to detect parts of the human brain. The imaging step is the first step in diagnosing brain tumor. By performing feature extraction, which aims to process the classification of brain tumors, between normal and abnormal brain images using the naive Bayes method. Obtained 41 images which then became 39 datasets. Feature extraction results with 2 classes, normal as many as 20 data and abnormal data 19. The calculation results obtained the value of the normal class of 0.513 and the abnormal class of 0.487 the value of the calculation accuracy of 84.17%.

PEMILIHAN KARYAWAN TERBAIK PADA BANK DKI DENGAN METODE TOPSIS Syaifur Rahmatullah; Robi Aziz Zuama; Aditia Darmawan
Eqien - Jurnal Ekonomi dan Bisnis Vol 11 No 1 (2022): EQIEN- JURNAL EKONOMI DAN BISNIS
Publisher : Sekolah Tinggi Ilmu Ekonomi Dr Kh Ez Mutaqien

The selection of the best employees is very important to be done by the company in order to see the quality of human resources and to increase the productivity and achievement of a company. The problem with Bank DKI is that there is no assessment for the best employees, causing employees to have low work motivation. In the process of selecting the best employee candidates, the company has not used alternative methods to produce the best candidates efficiently and accurately. In supporting these needs, a decision system is needed that can produce a system to facilitate the determination and selection of the best employees through several relevant criteria.

Pendekatan Machine Learning dalam Memprediksi Keluarga Penerima Program PKH Irwan Agus Sobari; Robi Aziz Zuama
JURNAL TEKNIK KOMPUTER Vol 9, No 1 (2023): JTK Periode Januari 2023
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jtk.v9i1.14165

Masalah kemiskinan di Indonesia masih menjadi fokus utama pemerintah dalam menetaskannya, program keluarga harapan (PKH) menjadi program prioritas pemerintah dalam upaya memberantas kemiskinan di Indonesia, fokus utama PKH adalah memberikan bantuan kepada Rumah Tangga Sangat Miskin (RTSM) untuk bisa mengakses pendidikan, kesehatan dan kesejahteraan sosial. Dalam menentukan keluarga yang berhak menerima bantuan PKH sering mengalami masalah, seperti kurang tepat sasaran dalam menentukan RTSM, ini di dasarkan kepada kelalaian petugas sehingga kurang akurat dalam validasi data yang banyak. Sistem otomatis yang dapat memprediksi RTSM dapat menjadi solusi atas permasalahan ini, sistem yang didasarkan pada model machine learning. Penelitian ini bertujuan untuk menganalisis model machine learning Decision Tree (DT), Support Vector Machine (SVM), Naive Bayes (NB) dan Logistic Regression (LR) dalam memprediksi RTSM yang akurat. Hasil menunjukkan bahwa Logistic Regression menjadi model yang optimal untuk di implementasikan dengan nilai AUC sebesar 0,999

Implementasi Metode Waterfall Dalam Mengembangkan Sistem Informasi Ujian Online Dengan Fitur Proctoring Robi Aziz Zuama; Muhamad Abdul Ghani; Deni Gunawan; Abdul Latif Matihudin
INFORMATICS FOR EDUCATORS AND PROFESSIONAL : Journal of Informatics Vol 7 No 2 (2023): INFORMATICS FOR EDUCATORS AND PROFESSIONAL : JOURNAL OF INFORMATICS (Juni 2023)
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Bina Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51211/itbi.v7i2.2382

Sistem ujian online berbasis web dengan fitur pengawasan proctoring telah menjadi tren yang populer dalam lembaga pendidikan dan perguruan tinggi saat ini. Penelitian ini bertujuan untuk merancang dan mengembangkan sistem informasi ujian online yang aman dan terpercaya dengan fitur pengawasan proctoring. Sistem ini memberikan fleksibilitas waktu dan tempat bagi peserta ujian, sambil mengurangi biaya dan upaya administratif yang terkait dengan ujian konvensional. Metode pengembangan Perangkat lunak yang digunakan yaitu waterfall, dengan tahapan analisis kebutuhan, perancangan, implementasi, testing, dan perawatan. Model yang diusulkan mampu mengefisiensikan kegiatan ujian disekolah serta kecurangan dalam ujian dapat di minimalisir.

Co-Authors Abdul Latif Matihudin Achmad Baroqah Pohan Achmad Rifai Aditia Darmawan Amin Nur Rais Arina Selawati Astuti, Rachmawati Darma Biktra Rudiarto Deni Gunawan Deni Gunawan Eka Herdit Juningsih Fajar Akbar Hamdun Sulaiman Mareanus Lase Mohammad Syamsul Azis Muhamad Abdul Ghani Nurul Ichsan Ramdhan Saepul Rohman, Ramdhan Saepul Sobari, Irwan Agus Sofian Wira Hadi Susilawati Susilawati Syaifur Rahmatullah Syaifur Rahmatullah Syaifur Rahmatullah Veithzal Rivai Zainal Yuliani, Yuri Yuri Rahayu

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