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All Journal Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial IJCIT (Indonesian Journal on Computer and Information Technology) Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Jurnal Teknik Komputer AMIK BSI Paradigma Jurnal Pilar Nusa Mandiri JUTIM (Jurnal Teknik Informatika Musirawas) EVOLUSI : Jurnal Sains dan Manajemen IMTechno: Journal of Industrial Management and Technology Jurnal Abdimas Komunikasi dan Bahasa SPEED - Sentra Penelitian Engineering dan Edukasi Akademika

Evy Priyanti

Universitas Bina Sarana Informatika

Author-ID : 2545019

Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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KOMPARASI KLASIFIKASI PADA PREDIKSI PENDAPATAN RUMAH TANGGA Evy Priyanti
Swabumi Vol 7, No 2 (2019): Volume 7 Nomor 2 Tahun 2019
Publisher : Universitas Bina Sarana Informatika Kota Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/swabumi.v7i2.6529

Kebutuhan akan kehidupan sehari-hari tidak terlepas dari pendapatan yang dihasilkan, baik pendapatan harian, mingguan atau bulanan. Oleh karena itu prediksi pendapatan rumah tangga sangat penting dikarenakan akan membantu dalam menciptakan pendapatan yang lebih baik, dalam memprediksi suatu data dapat dilakukan dengan beberapa algoritma diantaranya dengan algoritma K-nearest neighbor dan algorima Neural Network. Pada penelitian kali ini akan dikomparasi bagaimana algoritma K-Nearest neighbor dengan Neural network dalam memprediksi pendapatan rumah tangga pada sensus yang dilakukan di Bereu pada tahun 1996. Algoritma K-Nearest neighbor menghasilkan nilai akurasi sebesar 70,49% sedangkan algoritma Neural Network menghasilkan akurasi sebesar 83,62%, hal ini membuktikan bahwa algoritma Neural Network dapat bekerja lebih baik dalam memprediksi pendapatan rumah tangga di Bereu yang dilakukan oleh Ronny Kohavi dan Barry Becker pada 1 mei 1996 yang terdiri dari 48842 dataset dan 14 atribut. Beberapa atribut menjadi faktor penentu dalam menciptakan pendapatan yang lebih tinggi, diantaranya status pernikahan yang utuh yang terdiri dari minimal suami dan istri dalam satu atap dan pendidikan yang tinggi mendapatkan peluang untuk mendapatkan penghasilan yang lebih tinggi dari pasangan itu sendiri yang nantinya dapat mempengaruhi pendapatan rumah tangga lebih dari $50.000/tahun. Selain itu faktor pengalaman bekerja juga menjadi salah satu faktor penentu tingginya pendapatan rumah tangga. Faktor ketidakharmonisan dalam rumah tangga juga menjadi salah satu fakto pendapatan yang kurang dari $50.000/tahun.

RANCANG BANGUN SISTEM INFORMASI E-LEARNING PADA SMK PGRI 37 JAKARTA Evy Priyanti; Rahmad Budi Ansyah; Fachrul Ramadhani; Huzaiful Yaman
Swabumi Vol 8, No 1 (2020): Volume 8 Nomor 1 Tahun 2020
Publisher : Universitas Bina Sarana Informatika Kota Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/swabumi.v8i1.7456

Based on Permendikbud No. 60 of 2014 states that the implementation of PRAKERIN using a block system is carried out for half a semester around 3 months, with this enormous amount of time making students lacking in teaching and learning in class. Therefore it is very necessary methods that can support the education system that can facilitate students in learning, one of them with e-learning systems. This system can help students in learning and also greatly help the teaching board in developing material because e-learning methods can be opened with more free time. Some subjects can be made e-learning systems so that students have more time to learn and develop the knowledge they have. E-learning at SMK PGRI 37 Jakarta makes students progress in learning lessons that cannot be learned in class because of the limited time available. E-learning systems can be developed to the maximum in accordance with the changing times due to the sophistication of technology that can facilitate human work at this time. E-learning at SMK PGRI 37 Jakarta is one of the breakthroughs that utilizes technology for the development of students' abilities and development.

PENERAPAN ALGORITMA REGULARIZED DISCRIMINANT ANALYSIS UNTUK KLASIFIKASI KANKER PARU Evy Priyanti
Swabumi Vol 8, No 2 (2020): Volume 8 Nomor 2 Tahun 2020
Publisher : Universitas Bina Sarana Informatika Kota Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/swabumi.v8i2.9153

Lung cancer is a type of cancer that starts from the lungs with abnormal cell growth. Lung cancer is a type of cancer with the largest number of sufferers. In this research, Regularized Discriminant Analysis (RDA) analysis is used to classify the types of lung cancer that exist. Regularized Discriminant Analysis (RDA) is a generalization of Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA). If the alpha parameter is set to 1, this operator performs an LDA. Likewise if the alpha parameter is set to 0, this operator performs QDA. Discriminant analysis is used to determine which variables distinguish between two or more groups that occur naturally. With an accuracy value of 60%, it can be ascertained the type of lung cancer suffered by patients for ease of care and treatment.

Sistem Informasi Pemilihan PTN Pada Sekolah Menengah Tingkat Atas Negeri 4 Bogor Nining Suryani; Maulana Rizki; Evy Priyanti
IMTechno: Journal of Industrial Management and Technology Vol. 3 No. 2 (2022): Juli 2022
Publisher : LPPM Universitas Bina Sarana Informatika

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

The growth of several universities in Indonesia indicates that the knowledge gained is important for life or for finding work. The process of selecting universities, especially public universities for students is a complicated process and they may make a mistake in choosing a public university which in the end makes them feel they have wasted a lot of time. Therefore, the need for a computer-based system is deemed necessary to meet the information needs. This study uses the SDLC and waterfalls methods while the data collection is done by using the methods of observation, interviews, and literature study. The determination of the selection of this university will use the Analytical Hierarchy Process (AHP) method as a determinant of the weight of each criterion to determine the priority of each university. For the manufacture of this system used the Unified Modeling Language (UML) design model. This study aims to produce a system design that can be used for the selection of state universities and can assist in providing evaluations based on student and student criteria, including location, accreditation, scholarships, facilities and SMEs.

Efektifitas Pemanfaatan Zoom Meeting dalam Meningkatkan Kinerja DKM Jami Darul Hikmah Veti Apriana; Evy Priyanti; Raden Mohammad Riezky Pahlevi
Jurnal Abdimas Komunikasi dan Bahasa Vol. 1 No. 2 (2021): Desember 2021
Publisher : LPPM Universitas Bina Sarana Informatika

Pandemi Covid 19 yang berlangsung pada saat ini membuat pengurus DKM Jami’ Darul Hikmah harus melakukan kegiatannya atau aktivitasnya secara daring menggunakan sarana media online. Media online yang dipakai untuk melakukan kegiatan/aktivitas dengan menggunakan zoom karena lebih familiar dan banyak pengguna sehingga perlu diadakan sosialisasi berupa Workshop untuk penggunaan Zoom. Kegiatan dan aktivitas yang sudah dilakukan pada saat ini tidak dapat dilakukan secara tatap muka dengan banyak orang dikarenakan masih berlangsungnya Pademi Covid 19. Akan tetapi pada saat ini para pengurus DKM Jami’Darul Hikmah, perlu ada menggunakan Zoom Meeting agar kegiatan / aktivitas menjadi lebih efektif, yang menjadi permasalahan selama ini pengurus DKM Jami’Darul Hikmah hanya menggunakan media komunikasi dengan Whatsapp sehingga menyulitkan para pengurus untuk melakukan interaksi dikarenakan terbatasnya fungsi yang ada di Whats App untuk kegiatan / aktivitas yang mengundang banyak orang seperti kegiatan pendidikan,pelatihan, pengajian umum, ceramah, memperingati Hari Besar Agama Islam. Metode pelaksanaan kegiatan Workshop ini dilaksanakan secara daring. Hasil luaran berupa peningkatan pengetahuan, keterampilan dari pengurus DKM Jami’Darul Hikmah.

Implementasi Algoritma Naïve Bayes Untuk Rekomendasi Sekolah Perawat Evy Priyanti - AMIK BSI Jakarta; Nining Suryani - AMIK BSI Karawang
SPEED - Sentra Penelitian Engineering dan Edukasi Vol 10, No 4 (2018): Speed 2018
Publisher : APMMI - Asosiasi Profesi Multimedia Indonwsia

ABSTRAK - Pendidikan perawat sangat dicari di beberapa daerah bahkan dibeberapa Negara, dengan berkembangnya dunia kedokteran maka perawat mengambil hal vital dalam hal ini. Semakin banyaknya siswa yang mendaftarkan diri di sekolah perawat maka pihak sekolah memerlukan beberapa kriteria dalam mengambil keputusan yang harus dilakukan secara tepat dan cepat, kriteria tersebut nantinya akan diklasifikasi menjadi beberapa bagian dan Naïve bayes memiliki beberapa keunggulan dalam pengklasifikasian data adalah meningkatnya performa dalam mengklasifikasi data. Data set nursery ini sangat tepat jika menggunakan algoritma Naïve Bayes. Naïve Bayes sangat tepat dalam penelitian ini karena dapat menghitung peluang dengan ketepatan akurasi sebesar 90,32% pada dataset Nursery yang diambil dari UCI dataset pada sekolah perawat yang berada di Ljubljana, Slovenia dengan delapan atribut dan satu atribut keluaran.Kata Kunci: Algorithma, Perawat, Naïve BayesABSTRACT - Nurse education is highly sought after in some regions even in some countries, with the development of medicine, nurses take vital things in this regard. The more students who enroll in the nursing school then the school requires some criteria in making decisions that must be done accurately and quickly, these criteria will be classified into several parts and Naïve Bayes has several advantages in classifying data is increasing performance in classifying data. This data set nursery is very appropriate if you use the Naïve Bayes algorithm. Naïve Bayes is very appropriate in this study because it can calculate the opportunity with accuracy accuracy of 90.32% in the Nursery dataset taken from the UCI dataset in the nursing school in Ljubljana, Slovenia with eight attributes and one output attribute.Keywords: Algorithma, Nurse, Naïve Bayes

Penerapan Decision Tree Untuk Klasifikasi Tingkat Pendapatan Evy Priyanti
IJCIT (Indonesian Journal on Computer and Information Technology) Vol 7, No 1 (2022): IJCIT Mei 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Semua orang pasti menginginkan pendapatan yang besar. Banyak faktor yang membuat pendapatan setiap orang berbeda dari mulai faktor Usia, jenis pekerjaan, status Pendidikan, pekerjaan, ikatan pernikahan, warna kulit, jenis kelamin, keuntungan, durasi waktu kerja, asal negara. Penelitian ini bertujuan untuk menentukan faktor penentu dalam meraih pendapatan yang besar menggunakan metode decision tree. Decision tree ini memiliki banyak kelebihan diantaranya sangat mudah diimplementasikan dan disajikan dalam bentuk diagram. Dengan mengklasifikasikan faktor-faktor penentu pendapatan menggunakan decision tree maka akan jelas terlihat faktor penentu yang dapat membuat seseorang memiliki pendapatan lebih besar. Penelitian ini menghasilkan data dengan pendapatan terbesar didapatkan pada atribut relasi. Seseorang dengan relasi yang luas dapat memiliki peluang pendapatan yang lebih besar yaitu sebesar 75.12%. Selain itu faktor usia dan lama bekerja juga menjadi faktor terbesar lainnya. Dengan kata lain memperluas jaringan komunikasi dan rekan kerja yang luas akan berdampak positif bagi penambahan nilai pendapatan.Everyone wants a big income. There are many factors that make everyone's income different, starting from age, type of work, education status, occupation, marriage ties, skin color, gender, benefits, duration of work, country of origin. This research aims to determine the determining factors in achieving a large. This decision tree has many advantages including very easy to implement and presented in the form of a diagram. By classifying income determinants using the decision tree method. It will be clear that the determining factors that can make a person have a greater income. This research resulted in data with the largest income obtained on relationship attributes. A person with extensive relationships can have a greater income opportunity, which is 75.12%, besides age and length of work are also the other biggest factors. In other words, expanding the network of communication and extensive co-workers will have a positive impact on adding value to income.

PERANCANGAN SISTEM INFORMASI PERSEDIAAN OBAT BERBASIS WEB PADA APOTEK BANTARJAYA BEKASI Annisa Rahmanita; Nining Suryani; Evy Priyanti
JUTIM (Jurnal Teknik Informatika Musirawas) Vol 7 No 2 (2022): JUTIM (Jurnal Teknik Informatika Musirawas) DESEMBER
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jutim.v7i2.1690

Based on the results of researchers' observations of the Bantarjaya Pharmacy, especially the drug procurement system, this research was carried out. The drug procurement process at the Bantarjaya Pharmacy is currently out of control and faces various challenges. Among them, there are often inconsistencies between recorded drug data and drugs that are actually available, and reports are still made manually, so that data recording becomes incorrect and ineffective. Expired but not easily identifiable drugs is another problem that often arises. The researcher came to the conclusion that the Bantarjaya Pharmacy needed a good drug supply system to make it easier for officers to collect drug data, both incoming and outgoing, as well as for stock verification. The waterfall method, data collection techniques, observations, interviews, and literature studies are used in the design of this drug supply information system. The design of a computerized drug supply information system can be an ideal way to overcome the problems that exist at the Bantarjaya Pharmacy which used to still use a manual approach. Because Bantarjaya Pharmacy can operate more effectively and efficiently if there is a computerized system.

Perancangan Mobile Sample Preparation Unit Dengan Model Process Lay Out Girman Sihombing; Evy Priyanti; Nining Suryani
IMTechno: Journal of Industrial Management and Technology Vol. 4 No. 1 (2023): Januari 2023
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/imtechno.v4i1.1640

One of the most important activities in Mining industry is the exploration step, Because the result of this activities will be as a basis of taking a decision about the continuity of mining activities in the future. This step must give the accuracy of information about the mineral content and the geological condition where the mining activity is done. The sample preparation is one of the parts of laboratory activities in exploration step. This activity is the first process before analyzing the sample content, so that this process must be organized and controlled as well for getting high quality final analysis result which is based on its precision and accuracy value. In getting the precision and accuracy of value content in the sample, the beginning process until finish in the laboratory activities must be assured that no value interference from the other source or other sample. The Mobile Sample Preparation Unit (MSPU) is one of the designs which can be applied in remote area where the exploration activities are done.

Penerapan Decision Tree Pada Penentuan Waralaba Evy Priyanti
Swabumi Vol 11, No 1 (2023): Volume 11 Nomor 1 Tahun 2023
Publisher : Universitas Bina Sarana Informatika Kota Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/swabumi.v11i1.13911

Data mining is the process of extracting data into useful information. The extraction process in data mining itself consists of several parts including classification, estimation, prediction, cluster, and association. To get the best results from a data required an algorithm that processes the data. The algorithm that will be used is a decision tree or decision tree. Decision tree or decision tree is data mining with classification where the algorithm has simple rules that can make it easier and can handle noisy data and missing values. In this study using franchise data to obtain the best location for a franchise. This Franchise data is processed using a Decision tree where the accuracy results obtained are 81%. These results indicate that the level of reliability and reliability is very consistent. Franchising is currently very mushrooming and is a very good prospect for business development during the current pandemic. For this reason, a good analysis is needed to be able to determine the right type and location of the franchise, so that the profits can be maximized. To be able to obtain greater opportunities than other competitors.

Co-Authors Annisa Rahmanita bayu Nur Bayu Nur Kuncoro Fachrul Ramadhani Fadhil Muhammad Abdurrahman Girman Sihombing Hidayat, Tino Huzaiful Yaman Kuncoro, Dwiyanto maulana rizki Nining Suryani Raden Mohammad Riezky Pahlevi Rahmad Budi Ansyah Rahmanita, Annisa Riezky Pahlevi, Raden Mohammad Sofyan Wahyu Tamrin Lanori Veti Apriana Veti Apriana, Veti

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