cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Jeperson Hutahaean
Contact Email
jepersonhutahean@gmail.com
Phone
+6281266157563
Journal Mail Official
jepersonhutahean@gmail.com
Editorial Address
Jl. Acces Road Kuala Tanjung Inalum No. 29 Dusun: Bahagia Kelurahan: Pakam Raya Selatan Kecamatan: Medang Deras
Location
Kab. batu bara,
Sumatera utara
INDONESIA
Jurnal Informatika dan Teknologi Informasi
Published by PT. Bangun Harapan Bangsa
ISSN : -     EISSN : 28304799     DOI : https://doi.org/10.56854/jt.v1i1
Core Subject : Science,
Computer Science & IT
Jurnal Informatika dan Teknologi Informasi Penerbitan jurnal ini sebagai sarana untuk menampung artikel-artikel ilmiah yang berasal dari hasil penelitian, kajian-kajian atau makalah ilmiah dari para peneliti maupun dosen yang sudah dipilih pada bidang komputer. Artikel ilmiah yang dikirim pada redaksi harus merupakan naskah asli dan tidak pernah dipublikasi ditempat lain. Artikel ilmiah dalam setiap penerbitan merupakan tanggungjawab penulis. Terbit empat bulanan dengan E-ISSN: 2830-4799 SK 0005.28304799/K.4/SK.ISSN/2022.06 Topik utama yang diterbitkan mencakup:berisi kajian ilmiah informatika tentang : Sistem Pendukung Keputusan Sistem Pakar Sistem Informasi, Kriptografi Pemodelan dan Simulasi Jaringan Komputer Komputasi Pengolahan Citra Dan lain-lain (topik lainnya yang berhubungan dengan teknologi informasi) Terbit dalam 4 (Empat) bulanan yaitu pada bulan: Issue No 1: Mei, Issue No 2: September, Issue No 3: Januari
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 1 No. 3: Januari 2023" : 5 Documents clear
Implementasi Metode K-Means Clustering Untuk Menganalisa Penerima Bantuan Di Desa Palasah Mar’atun Sholihah, Oliffia; Suarna, Nana; Dwilestari, Gifthera; R, Nining
Jurnal Informatika dan Teknologi Informasi Vol. 1 No. 3: Januari 2023
Publisher : PT. Bangun Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56854/jt.v1i3.121

Abstract

Overcome welfare problems for the community through direct assistance to very poor families in Palasah Village. Related to the problems that have occurred so far, namely that the assistance program targets for poor people, many people who should not have received the assistance, turned out to be inaccurate and valid. So many residents are not registered and recorded accurately. The purpose of this study was to determine the distribution of the accuracy of aid recipients in Palasah Village, Majalengka Regency. The method used in this study is the k-means clustering method, with stages of data collection, training data and data testing that considers several criteria based on: age, economic conditions, housing conditions, and income. With the K-means clustering test k=10, it can produce davies bouldin with sequence k2=0,587, sequence k3=0,529, sequence k4=0,588, sequence k5=0,581, sequence k6=0,529, sequence k7=0,612, sequence k8=0,653, sequence k9 = 0.639, sequence k10 = 0.669, then the conclusion of the Cluster distance performance process produces the best dbi, which is 0.529 in the 3rd order. Can be implemented grouping the data for sewing equipment recipients with the K-Means clustering method, can find out which cluster residents get assistance with sewing tools in Palasah Village. Keywords: Cluster K-Means Algorithm, Social Assistance
Optimasi Penjadwalan Mata Pelajaran menggunakan Constraint Programming Nurcahyawati, Vivine; Muhamad Risqiwahid; Achmad Arrosyidi
Jurnal Informatika dan Teknologi Informasi Vol. 1 No. 3: Januari 2023
Publisher : PT. Bangun Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56854/jt.v1i3.134

Abstract

Schools are educational institutions that have teaching and learning activities, one of the teaching and learning processes is scheduling subjects carried out by the Deputy Principal Curriculum to arrange subject schedules every school year once. The preparation of the subject schedule used today still uses Microsoft Excel, causing problems including the crash schedule, the number of classes taught exceeds the teaching hours, and complications in arranging the schedule if there is a change of schedule. The solution to the problem above is to create subject scheduling applications in website -based schools using constraint programming and stages of system development using waterfall. The results of the study obtained in this study showed that the application succeeded in forming subject schedules that schools can use. Furthermore, the application can be in accordance with the boundaries related to the specified scheduling. As well as applications can help the preparation of subjects optimally with no 100%crresses. The system in the application requires a maximum of 10 minutes for the schedule creation process. Keywords: Scheduling, Constraint Programming, Waterfall, Course
Analisa Pengelompokan Dataset Komputer Menggunakan Algoritma X-Means Rokhmatan Khaerullah, Rizal; Suarna, Nana; Nurdiawan, Odi
Jurnal Informatika dan Teknologi Informasi Vol. 1 No. 3: Januari 2023
Publisher : PT. Bangun Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56854/jt.v1i3.135

Abstract

Computer dataset cluster analysis is a data mining technique that aims to identify a group of objects that have the same characteristics. The problem in this research is how to implement the X-Means Clustering algorithm in grouping computer datasets based on computer prices and specifications. The purpose of this study is to determine the implementation of the X-Means Clustering method in classifying computer datasets against prices and specifications. This computer dataset consists of several attributes with a large number of records so we need a process that can group the data, namely clustering. The use of clustering is expected to provide predictions on the grouping of the computer dataset. One of the clustering methods that can be used to group data is X-Means clustering. The results of the research from data mining grouping computer datasets with the x-means Cluster model produced as many as 3 clusters, namely cluster 0 with 710 members, cluster 1 with 136 items and cluster 2 with 15 items. Keywords: Cluster X-Means Algorithm
System Informasi Resto Kuru Yuk Chicken Berbasis Online Untuk Pemesanan Makanan Dan Minuman Samodra Anugrah, Syawal; Suarna, Nana; Dwilestari , Gifthera
Jurnal Informatika dan Teknologi Informasi Vol. 1 No. 3: Januari 2023
Publisher : PT. Bangun Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56854/jt.v1i3.136

Abstract

KuRuyuk Resto is a social interaction center where people can gather, talk, write, read, discuss or just pass the time. To realize customer satisfaction, Resto KuRuyuk must have a good ordering system to increase revenue. The research method used is to use data collection methods starting from observation, interviews, and literature study. As for software development through the R&D approach. The problem with KuRuyuk Resto is having difficulties in serving orders, still using manual recording and not yet computerized or still using conventional recording. The purpose of this research is to improve customer service and satisfaction in ordering food and beverages. The results of this study are that it can facilitate service and the effectiveness of workers' time becomes faster and more efficient. And can produce information quickly, precisely and accurately. After testing with SUS (System Usability Scale) an accuracy value of 76% was obtained.  Keywords: Information system, restaurant, improvement, sales, online based
Model Prediksi Perubahan Tutupan Lahan Pada Area Kebakaran Lahan Gambut Menggunakan Model Cellular Automata Markov Awal, Elsa Elvira; Sukaesih Sitanggang, Imas; Syaufina, Lailan
Jurnal Informatika dan Teknologi Informasi Vol. 1 No. 3: Januari 2023
Publisher : PT. Bangun Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56854/jt.v1i3.141

Abstract

During 2016 Riau Province experienced 10,676 hectares of forest and land fires on fire, where Rokan Hilir District was the largest area of forest fires that reach 3,416 hectares. The area of peatlands in Indonesia is currently experiencing degradation because of peatland fires that, result land-use, land-use changes, and forestry. The purpose of this study was to create a prediction model of land cover change in land fire areas using the Cellular Automata Markov model. The Markov Cellular Automata model is used to predict changes in land cover because this model is very suitable to be applied in high-detail spatial phenomena. The results of this study indicate that in the 2000-2003 period is used to predict land cover changes in 2006 due to forest the land fire in March 2002. The results show that plantations has the most significant change, namely 25.36% with a Kappa value of 95.74%. The prediction model of the period 2006-2009 is used to predict land cover changes in 2012 due to forest the land fire in July 2007. The results show that swamp shrub experienced a change of 74.94% with a Kappa value of 93.22%. The prediction model of the period 2014-2016 is used to predict land cover changes in 2018 due to forest the land fire in June 2015. The results show that swamp bushland cover class experienced the most significant reform of 55.07% with a Kappa value of 68.59%. The prediction results from the three periods show good and acceptable results, however the area of land cover as the result of prediction model has quite large difference with the actual land cover. Keywords: cellular automata markov, land fires, peatlands, land-use land-use changes and forestry

Page 1 of 1 | Total Record : 5

 1 

Filter by Year

2023 2023


Reset
Filter By Issues
All Issue Vol. 4 No. 1: Mei 2025 Vol. 3 No. 3: Januari 2025 Vol. 3 No. 2: September 2024 Vol. 3 No. 1: Mei 2024 Vol. 2 No. 3: Januari 2024 Vol. 2 No. 2: September 2023 Vol. 2 No. 1: Mei 2023 Vol. 1 No. 3: Januari 2023 Vol. 1 No. 2: September 2022 Vol. 1 No. 1: Mei 2022