Article Per Year (5 Year)
p-Index From 2021 - 2026
0.882
P-Index
This Author published in this journals
All Journal Pixel : Jurnal Ilmiah Komputer Grafis Elkom: Jurnal Elektronika dan Komputer Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Innovative: Journal Of Social Science Research
Jati Sasongko Wibowo
Unisbank Semarang
Humanities Computer Science & IT Education Law, Crime, Criminology & Criminal Justice Public Health Other

Published : 5 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 5 Documents
Search

 1 
Sistem Pendukung Keputusan Pemilihan Komputer Mining Rig Dengan Metode COPRAS Rahartyan Wisnu Herlambang; Jati Sasongko Wibowo
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.v15i1.643

Abstract

Computer mining rigs are specially designed for only one purpose which is to mine crypto assets efficiently and effectively. Mining takes a lot of time, therefore it is very important to pay attention to computers for mining. The better the quality of the PC or computer, the faster the mining process will be. So far, consumers in choosing a mining rig computer only observe the mining rig computer without looking at special criteria such as price, motherboard, processor, VGA, power supply and RAM. COPRAS method assessment criteria include price criteria, motherboard, processor, VGA, power supply and RAM.. The system development method uses a prototype, the system design uses UML and the system manufacture uses PHP and MySQL. The results of the computer mining rig recommendations calculated using the COPRAS method are 12 GPUs 381 mh/s with a value of Ui = 1,000, Rig RTX 2060 with a value of Ui = 0,8157, Rig 6 x RTX 3060 with a value of Ui = 0,7108 and Rig RTX 2060 II with a value of Ui = 0.7014..
Implementasi Algoritme Apriori Pada Sistem Persediaan Obat Apotik Puskesmas Della Pratiwi; Jati Sasongko Wibowo
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 12, No 1: April 2023
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v12i1.1106

Abstract

One line of business that offers health services is the pharmacy, which can help people achieve optimal health. In the pharmacy service, data on drug use are published daily. Inappropriate data processing can result in missing values or damage to the data. To deal with problems that commonly occur in pharmacies, especially at the Bandarharjo health center, a system has been built that can help pharmacists work faster and get accurate information, namely by processing a list of drug information and using the data mining algorithm (Apriori) to find out drug sales patterns as a reference in planning drug placement and controlling future inventory. Trials with RStudio to calculate 100 event data, with a minimum support value parameter of 0.5 and a minimum confidence of 0.5, resulted in 2 rules namely {Rantidin tab 150 mg, Dexamethasone 0.5 mg tab with confidence reaching 54%} and {Dexamethasone 0.5 tab, Rantidin 150 mg with confidence reaching 39%}. The resulting rule will be a reference in setting the layout of drugs based on the interrelationships between drugs, as well as supply predictions that refer to the percentage of Confidence Level.Keywords: Pharmacy, Association Rules, Data Mining, Apriori Algorithm. AbstrakSalah bidang usaha yang menawarkan layanan kesehatan adalah apotek, yang dapat membantu orang mencapai kesehatan yang optimal. Dalam layanan apotek, data penggunaan obat dipublikasikan setiap hari. Pengolahan data yang tidak tepat dapat mengakibatkan missing value atau kerusakan pada data.  Untuk Penanggulangan Masalah yang umum terjadi di Apotek, khususnya di puskesmas Bandarharjo, dibangun sistem yang dapat membantu apoteker bekerja lebih cepat dan mendapatkan informasi yang akurat, yaitu dengan mengolah daftar informasi obat serta menggunakan algoritme datamining (Apriori) untuk mengetahui pola penjualan obat sebagai acuan dalam merencanakan penempatan obat dan mengendalikan persediaan di masa mendatang. Uji coba dengan RStudio untuk menghitung 100 data event, dengan parameter support value minimal 0.5 dan confidence minimal 0.5, dihasilkan 2 rule yaitu {Rantidin tab 150 mg; Dexamethasone 0.5 mg tab dengan confidence mencapai 90%} dan {Dexamethasone 0.5 tab; Rantidin 150 mg dengan confidence mencapai 61%}. Rule yang dihasilkan menjadi acuan dalam mengatur tata letak obat berdasarkan keterkaitan antar obat, serta prediksi persediaan yang mengacu pada prosentase Tingkat Kepercayaan dukungan (Confidence).
Sistem Rekomendasi Magang Berbayar Menggunakan Metode Content-based Filtering Rieza Ichlas UI Amal Sukma Putra; Jati Sasongko Wibowo
Innovative: Journal Of Social Science Research Vol. 3 No. 3 (2023): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v3i3.2324

Abstract

Media informasi terkait magang masih sulit didapatkan sehingga menyulitkan mahasiswa dan mahasiswi untuk mencari tempat magang. Informasi ini biasanya terdapat pada papan informasi perusahaan, pamflet, brosur, media sosial dan media lainnya. Informasi yang diberikan kepada media terkadang kurang lengkap dalam memberikan persyaratan yang dibutuhkan serta cara pendaftaran yang kurang jelas. Penelitian ini bertujuan untuk membangun sebuah sistem yang dapat digunakan untuk memberikan rekomendasi kepada mahasiswa dan mahasiswa dalam mencari informasi magang berbayar dengan menggunakan metode content-based filtering. Sistem rekomendasi magang berbayar menggunakan algoritma content-based filtering yang dapat menampilkan 10 rekomendasi berdasarkan kriteria atau kata kunci yang dicari. Proses pencarian Unicorn Startup Companies menggunakan algoritma content-based filtering untuk mendapatkan rekomendasi paid apprenticeship yaitu perusahaan Bukalapak dengan kemiripan terbesar yaitu 0,866.
SISTEM PENDUKUNG KEPUTUSAN SELEKSI PENERIMA BEASISWA DENGAN METODE NAÏVE BAYES Qori Alfina Pratiwi; Jati Sasongko Wibowo
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.v16i1.1042

Abstract

Lot of problems arise in selecting scholarship recipients in a large number of submissions, the existence of several searches used, and the selection of files for scholarship applicants is still manual, so a system is needed that can speed up, help, and make it easier in the decision-making process to lighten work. student section. In supporting decisions this system will use the Naïve Bayes Classifier Method to determine what is acceptable and not acceptable. The NBC method can analyze and make improvements to old data, and the resulting data will provide simpler probability values that can later be used to make decisions. From the results of the research that has been carried out, it can be realized that the application of the data mining algorithm using the Naïve Bayes Classifier can be carried out to select scholarship recipients at Stikubank University Semarang. The result of the selection of Unisbank Semarang scholarship recipients is the accuracy value. 72% of the 135 data which is divided into 100 training data and 35 test data.
SISTEM PENDUKUNG KEPUTUSAN SELEKSI PENERIMA BEASISWA DENGAN METODE NAÏVE BAYES Qori Alfina Pratiwi; Jati Sasongko Wibowo
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.v16i1.1042

Abstract

Lot of problems arise in selecting scholarship recipients in a large number of submissions, the existence of several searches used, and the selection of files for scholarship applicants is still manual, so a system is needed that can speed up, help, and make it easier in the decision-making process to lighten work. student section. In supporting decisions this system will use the Naïve Bayes Classifier Method to determine what is acceptable and not acceptable. The NBC method can analyze and make improvements to old data, and the resulting data will provide simpler probability values that can later be used to make decisions. From the results of the research that has been carried out, it can be realized that the application of the data mining algorithm using the Naïve Bayes Classifier can be carried out to select scholarship recipients at Stikubank University Semarang. The result of the selection of Unisbank Semarang scholarship recipients is the accuracy value. 72% of the 135 data which is divided into 100 training data and 35 test data.
Co-Authors Della Pratiwi Qori Alfina Pratiwi Rahartyan Wisnu Herlambang Rieza Ichlas UI Amal Sukma Putra