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J-SAKTI (Jurnal Sains Komputer dan Informatika)
Published by Sekolah Tinggi Ilmu Komputer Tunas Bangsa
ISSN : 25489771     EISSN : 25497200     DOI : http://dx.doi.org/10.30645/j-sakti
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Energy
J-SAKTI adalah jurnal yang diterbitkan oleh LPPM STIKOM Tunas Bangsa yang berfokus di bidang Manajemen Informatika. Pengiriman artikel tidak dipungut biaya, kemudian artikel yang diterima akan diterbitkan secara online dan dapat diakses secara gratis. Topik dari J-SAKTI adalah sebagai berikut (namun tidak terbatas pada topik berikut) : Artificial Intelegence, Digital Signal Processing, Human Computer Interaction, IT Governance, Networking Technology, Optical Communication Technology, New Media Technology, Information Search Engine, Multimedia, Computer Vision, Information System, Business Intelligence, Information Retrieval, Intelligent System, Distributed Computing System, Mobile Processing, Computer Network Security, Natural Language Processing, Business Process, Cognitive Systems, Software Engineering, Programming Methodology and Paradigm, Data Engineering, Information Management, Knowledge Based Management System, Game Technology.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 64 Documents
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Search results for , issue "Vol 6, No 2 (2022): EDISI SEPTEMBER" : 64 Documents clear
Model Identifikasi Penyakit Pada Tumbuhan Padi Berbasiskan DenseNet Muhammad Pailus; Dhomas Hatta Fudholi; Syarif Hidayat
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.478

Abstract

Errors in identifying diseases in rice plants can cause the potential for crop failure to increase by 18-80%, according to data from the Indonesian Ministry of Agriculture. This could be due to the lack of expertise in agriculture when compared to the amount of land in Indonesia. Recent research in the field of deep learning using neural networks has achieved remarkable improvements. Research on the identification of plant diseases in rice plants, using the MobileNet, NasNet and SqueezeNet architecture that supports mobile devices has been carried out. The experimental results show that the proposed architecture can achieve an accuracy of 93.3%. Motivated by previous research, this research will use DenseNet architecture (Dense Convolutional Network) to detect diseases in rice plants. The dataset used is relatively small, between 100-200 photos for each disease. To cover the lack of dataset augmentation is done to the dataset. The final results obtained are quite satisfactory with an accuracy of 96% with a Weighted Average of 97%.
Sistem Informasi Sentra Pelayanan Kepolisian Terpadu (SPKT) Pada Polsek Lubuk Raja Meilyana Winda Perdana; Aminullah Imal Alfresi; Muhammad Irvan Ma’ruf
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.510

Abstract

The Lubuk Raja Police and the Resort Police have functions, one of which is the Integrated Police Service Center (SPKT) whose role is to provide public services in the form of reporting from the community. In receiving reports from the public as well as when processing data, the SPKT Lubuk Raja Police officers still do it manually, such as when the officers make reports still using Microsoft Office, this can result in the accumulation of report files and make typing repeated every time there is a report from the public. In addition, there is still a manual for giving the register number and the process of recording the reporting data. Then, through a study at the Lubuk Raja Police at the Integrated Police Service Center (SPKT), the author thought about designing and creating a website-based information system. The system development method that the author uses in this study is the Waterfall Model which includes the steps of analyzing system requirements for code writing system design, testing, implementation, and maintenance. The "Software" software used in the creation of an integrated police service center information system (SPKT), such as: XAMPP (a "localhost" web server), MySQL (a SQL database management), Sublime text (as an editor, where we write program code) ). The final point of this research is the creation of an integrated police center information system (SPKT) to replace reporting, processing, and recording data, which previously used manual methods. With this, it will make it easier for members of the police to provide services to the community in the OKU police area
Pemberian Beasiswa Kepada Mahasiswa dengan Metode Preference Selection Index (PSI) Juniar Hutagalung; Ahmad Fitri Boy; Hendra Jaya; Iskandar Zulkarnain
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.406

Abstract

Stikes Santa Elisabeth is an institution in the field of education, especially health. Stikes Santa Elisabeth has many students who come from various regions where many students have difficulty paying tuition due to economic problems. Therefore, many agencies or companies cooperate with Stikes Santa Elisabeth to provide assistance to underprivileged students such as love, single tuition fees (UKT), and the Eka Tjita Foundation. The provision of assistance certainly has rules that must be met by students. Because of the many rules or criteria that must be checked to determine which students will receive assistance, it can often result in the wrong choice as there is a limit to the number of recipients. To overcome these problems, a Decision Support System (DSS) is needed in determining the provision of assistance to students. By applying the PSI method, Stikes Santa Elisabeth can be considered to provide information about the requirements that must be met in receiving assistance. Thus helping Stikes Santa Elisabeth to determine the provision of assistance to students. This study aims to analyze the problems that occur in determining the priority of providing assistance to Stikes Santa Elisabeth students by applying the PSI method based on alternative data and predetermined criteria. Based on the ranking table above, the student who is most prioritized to get a scholarship is Irene Permatasari with a preference selection index value of 0.8765. So it can be concluded that the application of the PSI method results in a ranking so that it can help Stikes Santa Elisabeth to choose students who are the most prioritized in receiving scholarships.
Analisis Marketplace Shopee Untuk Memprediksi Penjualan dengan Algoritma Regresi Linier Yusuf Syakir; Teguh Iman Hermanto; Yudhi Raymond Ramadhan
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.501

Abstract

Many methods can be used to predict sales, one of which is the processing of sales data using the method of data mining with a linear regression algorithm. The data in this study used is data on sales of the Ariqa Collection Boutique in the Shopee marketplace starting from May 2020 to April 2022. By using a linear regression algorithm, the Ariqa Collection Boutique can predict sales estimates based on total visitors and total orders. The data mining method used is SEMMA (Sample, Explore, Modify, Model, Assess). With the Rapidminer Studio 9.10 tools the test results Mean Square Error (MSE) value is 5.172.628.212.404, Root Mean Square Error (RMSE) is 2.274.341, and Mean Absolute Percentage Error (MAPE) is 4.34%. Based on the MAPE value obtained, the accuracy of the linear regression algorithm in predicting sales of Ariqa Collection Boutique in the Shopee marketplace provides high accuracy
Analisis Sentimen Ulasan Terkait UNESCO Global Geopark Di Google Maps dengan Algoritma Naive Bayes Dian Siti Utami; Adhitia Erfina; M Mupaat
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.524

Abstract

Ciletuh Geopark is part of the UNESCO Global Geopark Network. This study will analyze a tourist review of the Ciletuh Pelabuhan Ratu Geopark based on reviews on Google Maps. The author believes that customer reviews should be taken into consideration because they allow travelers to share their experiences. Reviews from tourists who have visited geoparks are the most important thing because these reviews can be used as information to be used as data. Because the Naïve Bayesian Algorithm is thought to have a high enough level of accuracy to identify the Unesco Global Geopark (UGG) Ciletuh Pelabuhan Ratu tourist destination that is often frequented based on visitor ratings on Google Maps, then this study utilizes it. Successively the highest accuracy values from this study were Palangpang with an accuracy value of 98.61%, Cisolok Geyser tourist attraction 94.44%, Ujung Genteng tourist attraction 98.36%, Cikaso tourist attraction 98.36%, Citepus tourist attraction 97 ,22%, Puncak Manic attractions 96.92%, Sodong attractions 95.83%, Cipanarikan attractions 95.01%, Teletubis Hill attractions 94.48%, and finally Cimarinjung attractions 94.44%.
Penerapan Algoritma C.45 Untuk Menentukan Tingkat Kepuasan Pelanggan Kartu Telkomsel Prabayar Erma Delima Sikumbang; Fattya Ariani; Tiwi Handayani; Kresna Ramanda; Sulaeman Hadi Sukmana; Adi Supriyatna
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.492

Abstract

Telkomsel is an operator mobile phone company that provides services for mobile phone users. The mobile phone Operator creates a small SIM card for the customer by means of having to be inserted into each phone to get access to the service. One of the most used mobile operators and belongs to the largest category in Indonesia is Telkomsel. In This study implemented algorithm method C. 45 in deciding customer satisfaction against the use of prepaid Telkomsel cards. This type of research is to implement data mining concept by involving as many as 100 user data of prepaid Telkomsel card through the dissemination of questionnaires. There is an attribute in each variable that affects customer satisfaction including: price, promotion, product quality and service quality. Based on manual calculation results and with the help of the RapidMiner studio 9.7 software is known to be the root is a variable quality service with the highest gain value of 0.266396957 and results classification accuracy value of 0.9655 so that belongs to the classification category is very good
Analisis Penyaluran Produk Prekursor di PT Tri Sapta Jaya Palangka Raya pada Wilayah Kalimantan Tengah Eggia Kaferin; Magdalena A. Ineke Pakereng
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.483

Abstract

This research aims to examine the distribution of precursor products in Central Kalimantan. The method of this research is quantitative. This research used a descriptive analysis approach. Technique of data collection is used with documentation. The data analysis used a quantitative descriptive, which aims to describe or depict an object through data collected that have been arranged into simple form. The results of this research reveals that the distribution of the precursor products in 14 regions is normal which helps the firm to distribute the products directly towards the precursor in medics. The highest area or region is Palangka Raya with 4267.5 products and the lowest is Pulang Pisau with 3 products in a period of eight months. The direct distribution applied as the firm's effort to optimize the available resources to satisfy the consumer and retailer in Central Kalimantan
Analysis of The Influence of Service Quality and Relationship Quality on Customer Satisfaction Aprilia Fitri Karimah; Vita Ratnasari
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.515

Abstract

PT. PLN (Persero) is one of the State-Owned Enterprises (BUMN) which aims to provide and serve customer needs for electric power. To improve efficiency, service quality, and electricity supply, PT. PLN (Persero) has transformed into four main focuses, namely Lean, Green, Innovative, and Customer Focused. At the point of Customer Focus, PT. PLN (Persero) especially UP3 Kendari has implemented a web-based system to manage complaints and reports of disturbances. The high level of public complaints, demanded PT. PLN (Persero) to improve services that have been provided to the community. It aims to build a good image in society. In this study, a theoretical model and 3 hypotheses were proposed to be tested using the SEM method. This study uses primary data by using data questionnaires to 150 customers. The results of the SEM analysis show that the service quality variable with a value of 0,832 is significantly and positively related to customer satisfaction. Otherwise, the relationship quality with a value of 0.030 has no significant effect on customer satisfaction. The relationship quality variable has an indirect effect on customer satisfaction through service quality of 0.739. To increase customer satisfaction, PLN needs to improve the quality of customer relationships.
Penerapan Cloud Computing Dalam Aplikasi Panggil Teknisi Berbasis Android Menggunakan Google Cloud Platform Dinda Lusita Fristiani Anissa; Ria Andryani
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.533

Abstract

In the development of technology that can facilitate all activities carried out by humans, especially for electronic goods such as cellphones, TVs, computers, and laptops, does not always function properly. Sometimes these electronic devices often experience problems or damage so that users try to repair them but are constrained by the lack of information about the right place and technician to fix the problem. Therefore, an online service that can fix these problems is created in the form of a Technician Call Application. In the design and manufacture of this application, Cloud Computing technology is applied. One of the cloud computing service providers is Google Cloud Platform (GCP). Application creation is made easy thanks to the use of Google App Engine Services as a Platform as a Service. In addition, Cloud Firestore is also implemented as a NoSQL database for applications to store and sync data. With the application of cloud computing, cloud computing is considered suitable to be implemented easily, such as storage services, applications, and more
Text Mining untuk Sentimen Analisis dengan Metode Naïve Bayes, SMOTE, N-Gram dan AdaBoost Pada Twitter CommuterLine Andreyana Pratama Putra; Yuda Pratama; Eka Kharisma Krisnadi; Indah Purnamasari; Dedi Dwi Saputra
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.506

Abstract

In the current era, the development of information technology and social media is growing rapidly so that it can provide updated information and various kinds of public opinion. Many internet users in Indonesia use social media for various purposes, such as seeking information and expressing opinions through social media. One of the social media that is widely used by internet users in Indonesia is Twitter. Twitter users can provide information in the form of comments, criticisms, or suggestions for Comutterline services more quickly and easily. Sentiment analysis can help provide an overview of public perception by grouping opinions into positive and negative categories for Commuterline services. Conducting sentiment analysis based on comments or Tweets from the community on Twitter Commuterline to determine the performance of the Naïve Bayes Classifier algorithm, Synthetic Minority Over-sampling Technique (SMOTE), AdaBoost, and N-Gram so that machine learning implementation can help identify public opinion conveyed through Twitter automatically into positive and negative categories. The use of the Naïve Bayes Classifier, Synthetic Minority Over-sampling Technique (SMOTE), AdaBoost, and N-Gram methods which are considered better to generate predictions on tweets sent by CommuterLine users

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