cover
Contact Name
Bakhtiyar Hadi Prakoso
Contact Email
bahtiyar.hp@gmail.com
Phone
+6282257197272
Journal Mail Official
bios@sinergis.org
Editorial Address
Perum. Griya Mangli Indah Blok AF-18 RT. 02 RW. 04, Kel. Mangli, Kec. Kaliwates, Kab. Jember, Jawa Timur, 68136
Location
Kab. jember,
Jawa timur
INDONESIA
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer
ISSN : -     EISSN : 27220850     DOI : https://doi.org/10.37148/bios
Core Subject : Science,
BIOS: Jurnal Teknologi Informasi dan Rekayasa Komputer (e-ISSN. 2722-0850) is a scientific journal in the field of information technology and computer engineering managed by the Asa Professional Research & Development Center (PUSLITBANG), Jember, East Java, Indonesia. This journal is managed by lecturers and practitioners who come from various university backgrounds in Indonesia, especially Jember, East Java.The BIOS journal is published 2 (two) times a year, namely every March and September. The BIOS journal published in each edition consists of 5-10 articles per volume. The focus and scope of this journal are in the field of Information Technology and others that are still knowledge related, including: Databases System Data Mining / Web Mining Data Warehouse Artificial Intelligence Business Intelligence Cloud & Grid Computing Decision Support System Human-Computer Interaction Mobile Computing & Application E-System Machine Learning Deep Learning Information Retrieval (IR) Computer Network Multimedia System Information System Geographic Information System (GIS) Accounting information system Database Security System & Network Security Cryptography Fuzzy Logic Expert System Image Processing Computer Graphic Computer Vision Semantic Web e-Health and others related to Information Technology and Computer Engineering.
Articles 5 Documents
Search results for , issue "Vol 2 No 1 (2021): March" : 5 Documents clear
Klasifikasi Data Antroprometri Individu Menggunakan Algoritma Naïve Bayes Classifier Sihombing, Johnson
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 2 No 1 (2021): March
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (456.584 KB) | DOI: 10.37148/bios.v2i1.15

Abstract

With the development of advances in computer technology today, most companies and organizations need a decision support system based on information systems, where the information is generally stored in the form of documents / text that is not structured. In this regard, a system for text management that is integrated with the decision support system is needed. One of them is the use of text data classification for anthropometric case studies of several samples. Anthropometry is a measurement of a person's body dimensions. The object of research is gender, first name, and height of a person. The research aims to determine the ratio of the number and height probability level of the number of men and women based on the input into an application using the Naïve Bayes Classifier method. The implementation design uses the Python programming language. The results showed that the height classification data frequency of women was more than the height classification data for men. And the number of height probability of a woman's body is greater than the number of height probability of a man's body.
Memanfaatkan Algoritma K-Means Dalam Memetakan Potensi Hasil Produksi Kelapa Sawit PTPN IV Marihat Pasaribu, Deny Franata; Damanik, Irfan Sudahri; Irawan, Eka; Suhada; Tambunan, Heru Satria
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 2 No 1 (2021): March
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (480.408 KB) | DOI: 10.37148/bios.v2i1.17

Abstract

Based on data on the results of oil palm production in PTPN IV Marihat displays several locations with fruit yields that vary in number. For this reason, grouping of potential fruit-producing locations is needed to know which locations produce large or small numbers of palm fruit. The production sharing is usually done based on the location or block of harvesting oil palm fruit. Therefore, a method is needed to facilitate the grouping of fruit producing locations. With the K-Means clustering approach, the division of location groups can be done based on harvested area (Ha), production realization (kg) and harvest year. In this research, clustering of potential fruit-producing areas was carried out using the K-Means algorithm. By using K-Means aims to facilitate the grouping of a block with a lot of fruit production, and low. The result of this research is that C1 (highest) is 14 Harvest Block data, and C2 (lowest) is 11 Harvest Block data.
Penerapan Algoritma Backpropagation dalam Memprediksi Hasil Panen Tanaman Sayuran Hutabarat, Dio; Solikhun; Fauzan, M.; Windarto, Agus Perdana; Rizki, Fitri
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 2 No 1 (2021): March
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (424.68 KB) | DOI: 10.37148/bios.v2i1.18

Abstract

This study aims to see the development of the number of vegetable crop yields in the following year. With this prediction, it is hoped that it can help the government and the community to be more careful in increasing the supply of crop stocks in order to meet the food needs of the people of Simalungun Regency. The data source is obtained from the Central Bureau of Statistics. In this study, researchers used the Backpropagation Algorithm. The Backpropagation Algorithm is an algorithm that functions to reduce the error rate by adjusting the weight based on the desired output and target. The results of this study show that the best architectural model is the 2-1-1 model with an accuracy rate of 75.0% and an epoch of 1392 iterations in 00:07 seconds. This research is expected to be a reference material in other studies that have the same research object and as a consideration for the government in making an even more accurate evaluation system
Penerapan Algoritma K-Means dalam Mengelompokkan Balita yang Mengalami Gizi Buruk Menurut Provinsi Chandra, Muhammad Dwi; Irawan, Eka; Saragih, Ilham Syahputra; Windarto, Agus Perdana; Suhendro, Dedi
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 2 No 1 (2021): March
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (479.571 KB) | DOI: 10.37148/bios.v2i1.19

Abstract

The purpose of this study was to screen toddlers who were experiencing severe malnutrition according to province. Sources of research data used were obtained from the Ministry of Health of the Republic of Indonesia. The variables used are toddlers who experience malnutrition according to the Province. In this study using Data Mining Techniques using the K-means algorithm. It is expected that the results of this study can provide input to the central government to pay more attention to nutritional intake in infants, so as to increase the growth and development of toddlers in Indonesia. . And the data obtained by high clusters are 15 Provinsi yaitu (Aceh, Sumatera Utara, Nusa Tenggara Barat, Nusa Tenggara Timur, Kalimantan Barat, kalimantan Tengah, Kalimantan Selatan, Sulawesi Tengah, Sulawesi Selatan, Sulawesi Tenggara, Sulawesi Tenggara, Gorontalo, Sulawesi Barat, Papua Barat, Papua), dan cluster rendah ada 19 yaitu (Sumatera Barat, Riau, Jambi, Sumatera Selatan, Bengkulu, Lampung, Kep. Bangka Belitung, Kep. Riau, Dki Jakarta, Jawa Barat, Jawa Tengah, DI Yogyakarta, Jawa Timur, Banten, Bali, Kalimantan Timur, Kalimantan Utara, Sulawesi utara, Maluku Utara).
Analisis Penilaian Kualitas Jenis Pelayanan Tebaik dengan Metode Analytic Network Process (ANP) di Kantor Dinas Kependudukan dan Pencatatan Sipil Kota Pematangsiantar Samosir, Fajar Rudi Sartomo; Damanik, Irfan Sudahri; Suhendro, Dedi; Solikhun; Susiani
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 2 No 1 (2021): March
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (468.542 KB) | DOI: 10.37148/bios.v2i1.21

Abstract

This study aims to determine the best service quality at the Pematangsiantar City Population and Civil Registration Office, which includes services for making Identity Cards (KTP), Family Cards (KK), birth certificates, marriage certificates and receipt making. The method used in this research is the Analytic Network Process (ANP) method. The data collection technique used is a questionnaire technique that is distributed directly to the people who come to take care of the needs of personal and family data files. The parameters used consist of the facilities provided, employee behavior, services, and provisions. Determining community satisfaction with a service can be seen from the quality of the type of service. The results of this study were obtained in rank-1 with a normal value of 0.49126400, rank-2 family cards with a value of 0.18988000, rank-3 birth certificates with a value of 0.16073800, marriage certificates rank-4 with a value of 0.09707200 and Finally, rank-5 receipt services with a value of 0.06104600 With this research it is hoped that it can help the Pematangsiantar City Population and Civil Registration Service to evaluate the services provided to the community in order to meet community expectations in terms of managing the needs of personal and family data files and knowing the types of best services.

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