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JITK (Jurnal Ilmu Pengetahuan dan Komputer)
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
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SELECTION OF FEED SUPPLIER IN SEA FISH CULTIVATION USING ANALYTICAL HIERARCHY PROCESS (AHP) METHOD Dasril Aldo; Muhamad Apri
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 1 (2020): JITK Issue August 2020
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1104.813 KB) | DOI: 10.33480/jitk.v6i1.1440

Abstract

The problem that often occurs in the cultivation of seawater fish is the lack of efficiency in determining the right supplier, usually the fish culture simply selects the supplier, namely by contacting the supplier asking for the help of sea fish needed and the price according to the order or not. If appropriate, the company issues a purchase order. Receiving results is not optimal because it does not consider other considerations such as quality, price, service, delivery time, and guarantee. This study aims to overcome these problems and make it easier for farmers to select appropriate suppliers of marine fish feed. Analytical Hierarchy Process (AHP) method used as a support in this study for the analysis of suppliers of data obtained from Batam Aquaculture Fisheries Center (BPBL) Batam with contributions in the form of Quality, Price, Service, Delivery, Delivery, and Guarantee. The stages of this method are determining the value of pairs, making the value of the criteria, Calculating the Eigen Value of the Principle, Calculating the Eigen Value of the Principle of the final value in making decisions. From the evaluation of the 5 supplier data, the results obtained rank rankings of each supplier with Supplier_003 as rank 1 with a value of 4.25 and Supplier_002 as rank 2 with value. 3.99 is accepted as a decision of Supplier_003 as the selected supplier and Supplier_002 Reserve supplier, while other suppliers are not selected. With these results, the decision support system using the AHP method can be applied as a supplier of fish suppliers at the Batam Aquaculture Fisheries Center (BPBL)
OPINION MINING ABOUT PARFUM ON E-COMMERCE BUKALAPAK.COM USING THE NAÏVE BAYES ALGORITHM Rizal Rizal; Muhammad Fikry; Annisa Helmina
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 1 (2020): JITK Issue August 2020
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1403.945 KB) | DOI: 10.33480/jitk.v6i1.1448

Abstract

Information plays a very important role in the rapid development of the world. Many people use online media to search for information, one of which is to find out information about the negative or positive of a product in e-commerce based on the comments that exist. To find out the classification of all comments-comet takes quite a long time in reading it. So, to make it easier than that all made a classification system to determine the classification of comments. In this classification process, the Naive Bayes algorithm is used as a solution to the problem. The process with the Naïve Bayes algorithm requires training data which is used as learning material from the system. The training data used is taken from one e-commerce site, Bukalapak.com regarding perfume products. Taking comments from Buakalapak.com used crawling techniques to retrieve comments from the whole product. The training data needed in this system is 1000 comments consisting of 500 positive training comments and 500 negative training comments. To get the accuracy value, it requires 300 test comments consisting of 150 positive test comments and 150 negative test comments. From the results of testing with Naive Bayes, the accuracy rate can be quite good, namely with a precision value of 96.44%, 96.34% recall, and an accuracy of 96.33%.
K-MEANS CLUSTERING AREAS PRONE TO TRAFFIC ACCIDENTS IN ASAHAN REGENCY Nurul Rahmadani; Elly Rahayu; Ayu Lestari
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 2 (2021): JITK Issue February 2021
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1382.878 KB) | DOI: 10.33480/jitk.v6i2.1519

Abstract

Traffic accidents on the highway still contribute to the high mortality rate in Indonesia, so it is of particular concern to the police in this country. Accidents occur in various places with different time events, this makes it difficult to determine which areas have a high level of traffic accident vulnerability. Information about traffic accident-prone areas is needed by the community and law enforcement. This information can be taken into consideration for supervision and anticipatory action, especially for the police. The initial stage of traffic accident prevention is to know the factors that cause traffic accidents obtained through traffic accident data analysis. The information system in this study analyzed traffic accident-prone areas in Asahan Regency. The analysis can be done with data mining, namely K-Means Clustering which can group data into several groups according to the characteristics of the data. The results of this study are the Asahan District Police Satlantas can find out the accident-prone areas in the most vulnerable categories, quite vulnerable and not vulnerable.
DEVELOPMENT DASHBOARD HR LEARNING BASED OLAP IN LIFE INSURANCE COMPANY William Frado Pattipeilohy; Sanwani Sanwani; Ade Priyatna
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 2 (2021): JITK Issue February 2021
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1286.324 KB) | DOI: 10.33480/jitk.v6i2.1664

Abstract

Currently in the business world, companies have the challenge to survive and even thrive in the face of business changes that are so fast and flexible both in terms of markets, consumers, products to competitors. Companies are required to be able to take quick and appropriate decisions in the face of all these business changes. Implementation of Business Intelligence in a company becomes a real solution in facing all those challenges. Where by using Business Intelligence, management within a company can make appropriate decisions based on valid data that has been processed into knowledge and presented from various perspectives needed. This research developed an integrated system in the form of an OLAP-based dashboard to present data reports, especially in the Human Resources Division. Various data in the excel file upload are automatically generated by ETL to the database using SSIS and consolidated into a data warehouse. Processing using SSAS, which is displayed in the form of a dashboard using Reporting Services with a more interesting summary form. With the development of the HR Learning and Development dashboard, top-level management companies get reports for quick, precise and accurate decision making.
IMPLEMENTATION OF PARTICLE SWARM OPTIMIZATION BASED MACHINE LEARNING ALGORITHM FOR STUDENT PERFORMANCE PREDICTION Muhammad Iqbal; Irwan Herliawan; Ridwansyah Ridwansyah; Windu Gata; Abdul Hamid; Jajang Jaya Purnama; Yudhistira Yudhistira
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 2 (2021): JITK Issue February 2021
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1716.24 KB) | DOI: 10.33480/jitk.v6i2.1695

Abstract

Education plays an important role in the development of a country, especially educational institutions as places where the educational process has an important goal to create quality education in improving student performance. Based on research conducted in the last few decades the quality of education in Portugal has improved, but statistics show that the failure rate of students in Portugal is high, especially in the fields of Mathematics and Portuguese. On the other hand, machine learning which is part of Artificial Intelligence is considered to be helpful in the field of education, one of which is in predicting student performance. However, measuring student performance becomes a challenge since student performance has several factors, one of which is the relationship of variables and factors for predicting the performance of participating in an orderly manner. This study aims to find out how the application of machine learning algorithms based on particle sworm optimization to predict student performance. By using experimental research methods and the results of empirical studies shown in each model, namely random forest, decision tree, support vector machine and particle swarm optimization based neural network can improve the accuracy of student performance predictions.
DETERMINATION OF PERMANENT LECTURERS IN IBM ASMI INFORMATION SYSTEM PRODUCT WITH SAW AND CURRENT METHOD Rendi Septian; Istiqal Hadi; Ridwansyah Ridwansyah; Windu Gata; Widiastuti Widiastuti; Muhammad Iqbal
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 2 (2021): JITK Issue February 2021
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1295.058 KB) | DOI: 10.33480/jitk.v6i2.1740

Abstract

Abstract— Determining the quality standards of lecturers refers to the criteria of education, research, and community service. The campus can carry out the first process for selecting permanent lecturers effectively by looking at several criteria. By using a Decision Support System (DSS), the four categories can be used as guidelines for decision-makers to choose permanent lecturers. The goal of writing this journal is to support the effectiveness of the time for decision-makers to choose permanent lecturers in the early stages by combining the Additive Ratio Assessment (ARAS) and Simple Additive Weighting (SAW) methods. Where the SAW method has the advantage of accurate assessment because the value of criteria and weights have been determined, while the ARAS method compares each criterion value to each optimal alternative as a whole to get an ideal alternative. The result of combining the two methods can describe the prospective lecturers who are suitable to be used as permanent lecturer criteria. Judging from the ranking results in calculations, the values obtained are 0.146341, 0.134146, and 0.121951. These results prove that ranking with an assessment using the combination of SAW and ARAS methods results in an effective, accurate, and efficient assessment. Keywords: Additive Ratio Assessment, Decision Support Systems, Permanent lecturer, Simple Additive Weighting. Intisari— Menentukan standar kualitas dosen mengacu kepada kriteria pendidikan, penelitian, dan pengabdian kepada masyarakat. Pihak kampus dapat melakukan proses pertama untuk pemilihan dosen tetap secara efektif dengan melihat beberapa kriteria. Dengan menggunakan Sistem Penunjang Keputusan (SPK), keempat kategori tersebut bisa dijadikan pedoman bagi pengambil keputusan untuk memilih dosen tetap. Tujuan penulisan jurnal ini adalah untuk membantu keefektifan waktu bagi pengambil keputusan untuk memilih dosen tetap tahap awal dengan penggabungan metodeAdditive Ratio Assessment (ARAS) dan Simple Additive Weighting (SAW).Dimana metode SAW mempunyai keunggulan penilaian akurat karena untuk nilai kriteria dan bobot telah ditentukan, sementara metode ARASmelakukan perbandingan setiap nilai kriteria terhadap masing alternatif optimal secara keseluruhan untuk mendapatkan alternatif yang ideal. Hasil penggabungan dua metode tersebut dapat menggambarkan calon dosen yang sesuai untuk dijadikan kriteria dosen tetap.Dilihat dari hasil perangkingan dalam perhitungan, nilai yang didapat 0,146341 ,0,134146 dan 0,121951. Hasil ini membuktikan bahwa perangkingan dengan penilaian menggunakan penggabungan metode SAW dan ARAS menghasilkan penilaian yang efektif, akurat dan efisien. Kata Kunci: Additive Ratio Assessment, Sistem Penunjang Keputusan, Dosen Tetap, Simple Additive Weighting.
APRIORI ALGORITHM IMPLEMENTATION TO DETERMINE PURCHASE PATTERNS OF RAW MATERIALS AT PT PENJALINDO NUSANTARA Dedi Rozaq Prastyo; Sri Dianing Asri
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 2 (2021): JITK Issue February 2021
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1189.331 KB) | DOI: 10.33480/jitk.v6i2.1909

Abstract

PT. Penjalindo Nusantara is a manufacturing company in the packaging field where production depends on customer demand or what is commonly known as job orders so that timely production work and availability of sufficient materials are mandatory for the company. There was a problem in the implementation of the raw material supply strategy by PT. Penjalindo Nusantara caused delays in the supply of raw material stocks. The solution to this problem is to apply the Apriori algorithm to find out what raw materials are being purchased simultaneously so that it can be the basis for implementing a purchasing strategy in supporting the effectiveness of procurement of raw material stocks and also saving time in sending raw materials by suppliers. This research uses a Web-based data mining application to find the raw material purchase pattern. The result of this research is obtained 11 patterns of purchasing raw materials using a minimum value of 90% support and a minimum of 100% confidence with a lift ratio of 1 as a reference for determining which raw materials will be purchased at the same time.
SYSTEMATIC LITERATURE REVIEW: IMPLEMENTATION OF KNOWLEDGE MANAGEMENT IN THE ORGANIZATION Azizah Nurfauziah Yusril; Evy Nurmiati
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 2 (2021): JITK Issue February 2021
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1043.391 KB) | DOI: 10.33480/jitk.v6i2.1929

Abstract

Knowledge management is an activity that organizations use to achieve goals and gain competitive advantages. This study features a systematic literature review that discusses the implementation of knowledge management in organizations covering 39 articles published from 2015 to 2020. This study aims to answer four research questions. The results show that the trend of knowledge management research in Indonesia is dominated by research related to the designing of knowledge management systems. The application of knowledge management in Indonesia has been applied in various fields. There are various models and methods that can be used in creating a knowledge management system
IMPLEMENTATION OF ENSEMBLE TECHNIQUES FOR DIARRHEA CASES CLASSIFICATION OF UNDER-FIVE CHILDREN IN INDONESIA Andriansyah Muqiit Wardoyo Saputra; Arie Wahyu Wijayanto
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 2 (2021): JITK Issue February 2021
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1265.736 KB) | DOI: 10.33480/jitk.v6i2.1935

Abstract

Diarrhea is an endemic disease in Indonesia with symptoms of three or more defecations with the consistency of liquid stool. According to WHO, diarrhea is the second largest contributor to the death of under-five children. Data and cases of children under five years who have diarrhea are very difficult to find, so the data analysis process becomes difficult due to the lack of information obtained. Difficulties in the data analysis process can be overcome by rebalancing, so the category ratios are balanced. The method that is popularly used is SMOTE. To solve imbalanced data and improve classification performance, this study implements the combination of SMOTE with several ensemble techniques in diarrhea cases of under-five children in Indonesia. Ensemble models that are used in this study are Random Forest, Adaptive Boosting, and XGBoost with Decision Tree as a baseline method. The results show that all SMOTE-based methods demonstrate a competitive performance whereas SMOTE-XGB gains a slightly higher accuracy (0.88), precision (0.96), and f1-score (0.86). The implementation of the SMOTE strategy improved the recall, precision, and f1-score metrics and give higher AUC of all methods (DT, RF, ADA, and XGB). This study is useful to solve the imbalanced problems in official statistics data provided by BPS Statistics Indonesia
COMPARISON OF REGIONAL CLUSTER ANALYSIS ACCORDING TO INCLUSIVE DEVELOPMENT INDICATORS IN JAVA ISLAND 2018 BETWEEN HIERARCHICAL AND PARTITIONING CLUSTERING STRATEGIES Akhmad Fatikhurrizqi; Arie Wahyu Wijayanto
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 2 (2021): JITK Issue February 2021
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1401.374 KB) | DOI: 10.33480/jitk.v6i2.1939

Abstract

Gross Domestic Product (GDP) is one of the most common indicators to reflect a nation’s development. Indonesia's GDP has an average growth rate of 5 percent over the 2015-2019 period with the highest growth rate occurred in 2018. Furthermore, the provinces in Java Island contributed the most out of any province to Indonesia’s GDP in that year. However, the development in Java Island still has several issues, such as high poverty, unequal income distribution, and high unemployment. This problem indicates that the economic growth in Java Island has not been inclusive concerning development. This study aims to group regencies/municipalities in Java Island based on indicators of inclusive growth. These indicators refer to McKinley (2010) in a journal published by the Asian Development Bank (ADB). The cluster methods used to represent each hierarchical and partitioning are the Agglomerative Nesting (AGNES) and K-Means methods. The results of this study show that there are 3 clusters based on the AGNES method and 4 clusters based on the K-Means method. Clusters with good inclusive growth characteristics are dominated by municipality areas based on the K-Means method. Meanwhile, the clusters with low inclusive growth characteristics are dominated by regencies/municipalities on Madura Island based on the K-Means and AGNES methods. The comparison of the appropriate methods in this study based on the silhouette value is the AGNES method.

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