Garuda - Garba Rujukan Digital

Article Per Year (5 Year)

All

JITK (Jurnal Ilmu Pengetahuan dan Komputer)

jitk
Website

Published by STMIK Nusa Mandiri

ISSN : - EISSN : 25274864 DOI : -

Core Subject : Science,

Computer Science & IT

Kegiatan menonton film merupakan salah satu cara sederhana untuk menghibur diri dari rasa gundah gulana ataupun melepas rasa lelah setelah melakukan aktivitas sehari-hari. Akan tetapi, karena berbagai alasan terkadang seseorang tidak ada waktu untuk menonton film di bioskop. Dengan bantuan media internet, berbagai macam aplikasi nonton film android sangat mudah dicari. Hanya bermodalkan smartphone saja para penonton film dapat streaming berbagai macam jenis film di mana saja dan kapan saja mereka inginkan. Akan tetapi, karena banyaknya pilihan aplikasi nonton film android yang bisa digunakan, terkadang seseorang bingung memilihnya. Untuk itu, diperlukan suatu sistem pendukung keputusan yang dapat digunakan para pengguna sebagai alat bantu pengambilan keputusan untuk memilih dengan berbagai macam kriteria yang ada. Salah satu metode yang digunakan adalah metode Analytical Hierarchy Process (AHP). AHP melakukan perankingan dengan melalui penjumlahan antara vector bobot dengan matrik keputusan dengan tujuan agar hasil yang diberikan lebih baik dalam menentukan alternatif yang akan dipilih. Berdasarkan hasil penelitian yang dilakukan oleh 36 sampel responden didapatkan kriteria konten menjadi prioritas pertama pengguna untuk memilih aplikasi nonton film android dengan nilai bobot sebesar 0,224. Sedangkan Netflix menjadi alternatif dengan prioritas pertama keputusan pengguna dalam memilih aplikasi nonton film android dengan nilai bobot sebesar 0,352.

Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)

Articles 394 Documents

15 16 17 18 19

IMPLEMENTATION OF ELECTRE ALGORITHM IN DECISION SUPPORT SYSTEM FOR SELECTING EXEMPLARY STUDENT Eka Pandu Cynthia; Edi Ismanto
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 1 (2020): JITK Issue August 2020
Publisher : LPPM Nusa Mandiri

One of the activities undertaken by the school to reward students for increasing motivation and enthusiasm for learning is the process of selecting exemplary students. Based on the observation of one of the junior high schools in Pekanbaru, the problem of difficulty in selecting the model students was obtained. This is because there are so many aspects and components of assessment that must be considered and taken into account by the school, both in terms of academic and non-academic students. Decision support system (SPK) plays an important role in supporting a decision, this research makes a model design in the form of a decision support system by applying the ELECTRE (Elimination Et Choix Traduisant La Relite) algorithm. The ELECTRE method is one of the Multi-Attribute Decision Making (MADM) methods that can provide decision recommendations based on the complexity of the attributes or criteria used in a decision support system. In this study, there are 8 components of the criteria used in the process of selecting exemplary students, namely the average report card, ranking, absenteeism, morals, achievements, organization, attitudes, and points of the violation. Based on the test results of the model built, it was found that the ELECTRE algorithm was able to select and rank 6 alternative model students based on assessment components and predetermined criteria. With the results of student A obtaining the highest aggregate value (2), followed by students B, C, D, E, and F with aggregate value 1 and finally student G with aggregate value 0. So student A can be proposed as a model student

HERBAL PLANT DETECTION BASED ON LEAVES IMAGE USING CONVOLUTIONAL NEURAL NETWORK WITH MOBILE NET ARCHITECTURE I Nyoman Purnama
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 1 (2020): JITK Issue August 2020
Publisher : LPPM Nusa Mandiri

Indonesia is a country with a variety of flora/plant diversity. One type of flora wealth is herbal plants. Herbal plants are plants that have uses to treat a disease. The diversity of herbs often makes our mistakes in recognizing the type. Therefore we need a system that can recognize the types of herbs automatically with their use. In this study, the CNN (Convolutional Neural Network) algorithm is used. This algorithm is a deep learning method that can recognize and classify an object. In this study, we use 500 images for 5 types of leaves of herbal plants. Mobilenet architecture is used on an Android-based system so that it has the thickness of the convex filter that matches the image thus saving the size of the learning model. Based on the test results on 30 new images obtained an accuracy rate of 86.7%. So it can be concluded that the use of the CNN algorithm is quite good at detecting herbal plants based on the training data used.

IDENTIFICATION OF CHRONIC KIDNEY DISEASE USING NAIVE BAYES, ADABOOST, AND RANDOM FOREST LEARNING METHODS Raras Tyasnurita; Shafira Widya Hapsari
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 1 (2020): JITK Issue August 2020
Publisher : LPPM Nusa Mandiri

Chronic kidney disease is a decrease in function in the kidneys where the condition leads to kidney damage. This disease causes damage to the body's immunity, because the body fails to maintain fluid balance. Therefore, it becomes a critical need to identify whether a patient is a sufferer of chronic kidney disease or not. The classification methods used in this study are Naive Bayes, AdaBoost, and Random Forest. Recently, proper early recognition is needed to detect chronic kidney disease to prevent delays in its treatment. Given the large number of chronic kidney disease cases that occur, this study is expected to be an effort to control the increase in sufferers. The results showed that the Naive Bayes approach achieved 95.4% accuracy, which increased to 98.6% after AdaBoost was implemented, and Random Forest led at 99.3%.

CLASSIFICATION OF THE PROSPECTS FOR CITY TREES LIFE EXPECTANCY USING NAIVE BAYES METHOD Muhammad Rifqi Firdaus; Abdul Latif; Ipin Sugiyarto; Windu Gata
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 1 (2020): JITK Issue August 2020
Publisher : LPPM Nusa Mandiri

Besides the city is a large and extensive residential area. as a center for the activities of its citizens, both from economic, cultural, and development activities. Development in the city leads to the physical development of the city with the many facilities and infrastructure in the city, making activities in the city cause some pollution problems. To overcome this problem, the government often creates green open space in the middle of the city. Planting shade trees will help to balance the problem of pollution due to development. Trees can reduce temperatures, in addition to absorbing air and climate pollution. trees can help save energy. Naive Bayes is a classification with probability and statistical methods, namely predicting future opportunities based on experience based on the assumption of simplification that attribute values are conditionally free if given an output value. Data processing with Naive Bayes produces a Precision value of 0.840%, a recall value of 0.848%, and an AUC of 0.873%. These results indicate that the results are included in the excellent category.

SISTEM PENDUKUNG KEPUTUSAN PEMBERIAN KREDIT MENGGUNAKAN ALGORITMA C4.5 DAN METODE ANALYTICAL HIERARCHY PROCESS Aleksander Bagas; Nina Setiyawati
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 1 (2020): JITK Issue August 2020
Publisher : LPPM Nusa Mandiri

PT. BPR Mekar Nugraha is one of the people's credit banks that has a high problem of bad credit. This is caused by many factors with one of the main factors namely the purpose of using credit is not in accordance with the credit application form. One way to solve the problem is by building a credit decision support system (SPK). In this research, SPK granting credit using C4.5 Algorithm and Analytical Hierarchy Process Method (AHP). The C4.5 is used as a calculation of customer data and AHP is used as a calculation of credit collateral. It is hoped that the SPK can provide alternative decisions and help credit analysts in the process of granting credit to customers. Of the 60 testing data used in the test, 71% of the test results are in accordance with the calculation of credit granting manually

MAPPING OF POTENTIAL CUSTOMERS AS A CLOTHING PROMOTION STRATEGY USING K-MEANS CLUSTERING ALGORITHM Mardalius Mardalius; Tika Christy
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 1 (2020): JITK Issue August 2020
Publisher : LPPM Nusa Mandiri

The high demand for clothes causes the development of the clothing industry in Indonesia continues to increase. Increasing the number of competitors among apparel traders is also unavoidable. This is also experienced by clothing traders with an online concept. Therefore the right sales strategy is needed to be able to survive or even win the competition. One thing that can be done is to apply technology to promote to obtain and maintain potential customers. However, promotions that are carried out without a clear and measurable concept can cause harm if carried out on target. The same thing happened in the Mustika Gerai online clothing store which was the location of observation, so far the concept of promotion was carried out by lowering prices and discounts for all customers. As a result, what happens is that sales turnover decreases dramatically while new customers who expect it may not necessarily be achieved. The purpose of this study is to research by applying data mining technology in the Gerai Mustika customer data warehouse to map potential customers as targeted promotional strategies. The data mining technique used is the k-Means Clustering method. The process of extracting information in the form of pattern discovery/mapping is then integrated using the Rapidminer software. From the results of the analysis that has been done, it can be concluded that the application of the k-means method can map potential customers based on regions or sub-districts, namely cluster 1 has 3 districts, cluster 2 has 7 districts and cluster 3 has 13 districts. These results are strengthened by RapidMiner software testing with data accuracy following the results of calculations from 23 data

APRIORI ALGORITHM FOR IMPLEMENTATION OF RAW MATERIAL PURCHASE DATA ANALYSIS IN PT MAHAKAM BETA FARMA Dewi Risdawati; Nita Merlina
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 1 (2020): JITK Issue August 2020
Publisher : LPPM Nusa Mandiri

PT Mahakam Beta Farma is a manufacturing company in the pharmaceutical field and there are obstacles in the storage of raw materials so that the process of entering and exiting raw materials is not effective. The solution to this problem is to rearrange the location of raw materials in the warehouse to facilitate the distribution of raw materials when entering or leaving so that when needed for the production process does not require much time in the search, which will also have an impact on the smooth production process. The basis for determining the layout of raw materials in the warehouse is to analyze what raw materials are often purchased at the same time for 1 year with data mining using apriori algorithm method. The application used to process the purchase of raw material that is large enough is Tanagra 1.4. The results of this study obtained 12 patterns of purchase of raw materials with a minimum value of 80% support, 90% minimum confidence, and lift ratio o as materials to recommend the re-layout of raw materials in the warehouse.

MOBILE WEB APPLICATION PURWOKERTO TRADITIONAL FOOD GAME CLASIFICATION USING MOBILENET V2 Novian Adi Prasetyo
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 1 (2020): JITK Issue August 2020
Publisher : LPPM Nusa Mandiri

Indonesia is a large country where there are thousands of aspects of culture, language and tourism. All of these aspects are an identity for the Indonesian state and each region within it. Culinary is one aspect that is included in the field of tourism. In Indonesia, each region has a special food that is an icon of the area. With so many foods from foreign countries entering Indonesia, this is feared will make the younger generation lose their identity about the regional heritage in special foods. Current technological developments have become excellent in various fields to solve the challenges that exist in the surrounding environment, it does not rule out the possibility that technology can be used to preserve the special foods that exist in each region. Based on the problems outlined above, this research will build a mobile web-based application for the introduction of local specialties through imagery and implement computer vision to mobile devices with CNN MobileNet V2 architecture. In this study a mobile web application was produced that was able to recognize Purwokerto's special foods that could be run well on various devices and operating systems.

CLASSIFICATION OF LIVER DISEASE BY APPLYING RANDOM FOREST ALGORITHM AND BACKWARD ELIMINATION Irwan Herliawan; Muhammad Iqbal; Windu Gata; Achmad Rifai; Jajang Jaya Purnama
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 1 (2020): JITK Issue August 2020
Publisher : LPPM Nusa Mandiri

Cancer is a type of disease that is not realized by most people because most people associated with this disease lack understanding of cancer itself and are doing early detection of cancer, due to the majority of cancers found at an advanced stage and difficult to overcome to facilitate large expenditure to help cancer. Early detection of liver or liver cancer is very important to overcome the very high risk of death caused by liver or liver cancer. This study aims to help classify liver or liver cancer based on data from routine examination results of patients summarized in the Indian Liver Data Patient (ILDP) dataset. The method used in the classification process in this research is backward elimination modeling for testing optimization and Random Forest algorithm and split validation to validate the model. The results of this study yielded 76.00% and value of AUC 0.758 results. These results indicate that the results of this study are good enough to help classify breast cancer

IMPLEMENTATION OF DATA MINING ALGORITHM FOR PREDICTING POPULARITY OF PLAYSTORE GAMES IN THE PANDEMIC PERIOD OF COVID-19 Siti Fauziah; Daning Nur Sulistyowati; Norma Yunita; Siti Fauziah; Risca Lusiana Pratiwi
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 1 (2020): JITK Issue August 2020
Publisher : LPPM Nusa Mandiri

The existence of the COVID-19 virus makes everyone fill their time at home by doing various activities, one of them playing games on the phone. For the game to develop continuously, it needs an assessment that comes from the community and especially the game lovers themselves. This assessment is used to find out what category of game you want. Therefore the analysis is needed to determine the interests of game lovers by analyzing the popularity of a game. This research was conducted to predict the level of popularity of games in PlayStore applications to find out how many popular and unpopular games and the accuracy obtained with the C4.5 algorithm and Naive Bayes algorithm. The results obtained using the C4.5 algorithm showed 73 popular games and 12 unpopular games with an accuracy value of 85.83% with a precision of 85.83% and a recall of 100% and Naive Bayes showed 23 popular games and 62 unpopular games with an accuracy value of 80% with a precision of 96.11% and a recall of 81.01%. The evaluation results with the ROC curve show the AUC value using the Naive Bayes model of 0.776 and the C4.5 model of 0.500. Of the two models used, one of them is included in the classification of Good classification, namely the Naive Bayes algorithm model, because it has an AUC value between 0.80-0.90. While the C4.5 algorithm model is included in the Fair classification, has an AUC value between 0.70 - 0.80.

Page 17 of 40 | Total Record : 394

15 16 17 18 19

Filter by Year

2016 2025

Filter By Issues

All Issue Vol. 11 No. 2 (2025): JITK Issue November 2025 Vol. 10 No. 4 (2025): JITK Issue May 2025 Vol. 10 No. 3 (2025): JITK Issue February 2025 Vol. 10 No. 2 (2024): JITK Issue November 2024 Vol. 10 No. 1 (2024): JITK Issue August 2024 Vol. 9 No. 2 (2024): JITK Issue February 2024 Vol. 9 No. 1 (2023): JITK Issue August 2023 Vol. 8 No. 2 (2023): JITK Issue February 2023 Vol. 8 No. 1 (2022): JITK Issue August 2022 Vol 8 No 1 (2022): JITK Issue August 2022 Vol 7 No 2 (2022): JITK Issue February 2022 Vol 7 No 1 (2021): JITK Issue August 2021 Vol 6 No 2 (2021): JITK Issue February 2021 Vol 6 No 1 (2020): JITK Issue August 2020 Vol 5 No 2 (2020): JITK Issue February 2020 Vol 5 No 1 (2019): JITK Issue August 2019 Vol 4 No 2 (2019): JITK Issue February 2019 Vol 4 No 1 (2018): JITK Issue August 2018 Vol 3 No 2 (2018): JITK Issue February 2018 Vol 3 No 1 (2017): JITK Issue August 2017 Vol 2 No 2 (2017): JITK Issue February 2017 Vol 2 No 1 (2016): JITK Issue August 2016 More Issue

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name
-

Contact Email
-

Phone
-

Journal Mail Official
semdejafet1908@gmail.com

Editorial Address
-

Location
Kota adm. jakarta timur,

Dki jakarta

INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name -

Contact Email -

Phone -

Journal Mail Official semdejafet1908@gmail.com

Editorial Address -

Location Kota adm. jakarta timur, Dki jakarta INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
-

Contact Email
-

Phone
-

Journal Mail Official
semdejafet1908@gmail.com

Editorial Address
-

Location
Kota adm. jakarta timur,

Dki jakarta

INDONESIA