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Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi)
Published by Ikatan Ahli Informatika Indonesia
ISSN : -     EISSN : 25973584     DOI : -
Core Subject : Science,
Computer Science & IT
Seminar Nasional Sistem Informasi dan Teknologi (SISFOTEK) merupakan ajang pertemuan ilmiah, sarana diskusi dan publikasi hasil penelitian maupun penerapan teknologi terkini dari para praktisi, peneliti, akademisi dan umum di bidang sistem informasi dan teknologi dalam artian luas.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 472 Documents
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Penerapan Customer Relationship Management (CRM) pada Sistem Informasi Penjualan Bucket Berbasis Web di Toko Hadinafa Galery Nila Indasari; Seni Asria; Muhammad Fauzi Razak; Nurmadina Hs
Prosiding SISFOTEK Vol 7 No 1 (2023): SISFOTEK VII 2023
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

A web-based bucket sales information system with the implementation of Customer Relationship Management (CRM) is urgently needed in selling buckets at the Hadinafa Gallery store. This study aims to: (1) Build a web-based bucket sales information system by implementing Customer Relationship Management (CRM) at the Hadinafa Gallery store, (2) Implement a web-based bucket sales information system by implementing Customer Relationship Management (CRM) at te Hadinafa Gallery store. System activity design uses UML (Unified Modelling Language) which consists of 4: Use case diagram, Sequence diagram, Activity diagram, and Class diagrams. The programming languages used are PHP (PHP Hypertext Processor), MySQL, and Codeigniter4. Data collection was carried out in 3 ways, namely observation, interviews and library techniques. The results of this research are to make it easier for store owners to manage sales report data, customer data, and product data and help customers get bucket information without coming directly to the store.
Evaluasi Kinerja Dosen dengan Pendekatan Metode AHP dan BORDA Muh. Nurtanzis Sutoyo; Nur Ihsan; Basrawi, Basrawi; Agus Nasir
Prosiding SISFOTEK Vol 7 No 1 (2023): SISFOTEK VII 2023
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

This research aims to investigate the evaluation of faculty performance by utilizing a combined approach of the Analytic Hierarchy Process (AHP) and the Borda Method. The primary objective of this study is to develop a more structured, objective, and inclusive evaluation framework for assessing faculty performance. The AHP method is employed to address the complexity of determining the weights of evaluation criteria and sub-criteria, while the Borda Method provides a platform for various stakeholders to express their assessments in a participatory manner. This study is conducted using a qualitative research approach. Data is collected through surveys administered to students, colleagues, and administrators to provide evaluations of faculty performance based on predetermined criteria. The research results indicate that the combined approach of AHP and Borda is capable of offering a more accurate and holistic depiction of faculty performance. The AHP method assists in reducing subjectivity in weight determination, while the Borda Method facilitates the inclusion of opinions from various stakeholders.
Prediksi Kelulusan Pegawai Pemerintah Dengan Perjanjian Kerja Guru Menggunakan Metode Naive Bayes Basirung Umaternate; Imam T. Umagapi; Yuyun, Yuyun; Hazriani, Hazriani
Prosiding SISFOTEK Vol 7 No 1 (2023): SISFOTEK VII 2023
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Recruitment and selection of ASN PNS and PPPK candidates to date has quite a high number of enthusiasts, and the selection process using the Computer Assisted Test (CAT) is the main requirement for passing the PNS or PPPK selection. Therefore, the researcher made this research using pre-existing data or called training data. Researchers used the Naïve Bayes method with 9 mutually independent attributes to determine graduation. Researchers also used Microsoft Excel and Weka supporting applications to test the accuracy of the Naïve Bayes method. Tests were carried out with 212 datasets consisting of 170 training data/training data and 42 test data/testing. The results of the Accuracy, Recall, and Precesion tests determine the graduation of Government Employees with Work Agreements (PPPK) for Teachers in Morotai Island Regency, 100% Accuracy, 100% Precision, 100% Recall, and the Area Under ROC (AUC) value is 1, which means 100% below The curve shows that the performance of the Naïve Bayes algorithm in capitalizing the classification of graduation data for Government Employees with Employment Agreements (PPPK) for Teachers in Puau Morotai Regency is very good.
Sistem Pendukung Keputusan Kelayakan Pengajuan Kredit Tunai Berdasarkan Agunan dengan Metode Electre Najirah Umar; Suwatri Jura; Jefry Samuel
Prosiding SISFOTEK Vol 7 No 1 (2023): SISFOTEK VII 2023
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

This study aims to implement a decision support system on the feasibility of requesting a cash loan against collateral using the Electre method. The research methodology uses the Waterfall system development model, Research in the context focuses on efforts or actions aimed at improving the quality and performance of an organization. Data collection techniques in system design include documentation, observation, compiling questionnaires, and conducting interviews. The system processes data from the results of surveys of interested parties conducted by experts. The assessment results are processed electrically to obtain solvency results. Research results show that the decision support system on the feasibility of applying for a cash loan based on collateral using the Electre method can help companies determine the provision of credit to customers . Using this method effectively increases accuracy, efficiency and risk management in the credit decision-making process. This system brings huge benefits to financial services, customers and the entire banking industry.
Implementasi Klasifikasi Naive Bayes Dalam Memprediksi Lama Studi Mahasiswa Muhammad Fuad; Muhammad Arfah Wahlil; Hazriani, Hazriani; Yuyun, Yuyun
Prosiding SISFOTEK Vol 7 No 1 (2023): SISFOTEK VII 2023
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Under normal conditions, undergraduate or undergraduate students from a university can complete their studies for 4 years or 8 semesters. In fact, many students complete their study period of more than 4 years. It is known that in the academic year 20XX/20XX there were 161 people who were accepted as students. Of the 161 people admitted, 100 people have completed their study period of about 4 years and the remaining 61 people have completed their studies for 5 years. Based on the problems above, this research implements a classification that can help the university predict the length of study of students who are currently studying in various study programs at the University. The method that the author presents in the classification for predicting the length of a student's study period is the Naive Bayes Algorithm. By using the Java-based Rapid Miner tool to classify graduation data. Then the implementation of data mining which is divided into 136 data training data and 25 data testing data with naive Bayes managed to obtain an accuracy rate of 82% which is also a relatively good parameter.
Implementasi Algoritma Profile Matching Untuk Kelayakan Ujian Pada Universitas Handayani Makassar Andi Alamsyah; Najirah Umar; M Adnan Nur
Prosiding SISFOTEK Vol 7 No 1 (2023): SISFOTEK VII 2023
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The 1945 Constitution guarantees equal education for all Indonesian citizens, but 12 years of compulsory education is still not enough to cope with the increasing demands of the labor market. This makes it difficult for the younger generation to find jobs that match their expectations. Handayani University Makassar plays a role in helping to overcome these problems. Currently, the process of determining college eligibility is still manual and complicated. This research proposes a solution using technology through profile matching on web applications. This method determines test eligibility based on predetermined attribute weights. This helps students assess their potential before registering for the exam. The application of profile matching algorithm will also help universities identify students who are likely to pass the exam. This will speed up decision-making and improve student progression and learning outcomes. This research aims to predict students' exam eligibility using the profile match method. So that it is expected to help students achieve maximum passing standards and complete their studies on time. The application of the profile match algorithm is also expected to overcome the problem of slow decision making, help identify outstanding students, and improve student development and learning outcomes. Therefore, this research is titled "Implementation of profile comparison algorithm to assess exam eligibility".
Perancangan Aplikasi Mobile E-Voting Dengan Framework Flutter Untuk Pemilihan Ketua BEM Universitas Esa Unggul Kampus Tangerang Muhamad Magfur; Nizirwan Anwar
Prosiding SISFOTEK Vol 7 No 1 (2023): SISFOTEK VII 2023
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

In this research, accompanied by rapid technological advancements, the event of selecting the Student Executive Board (BEM) Chairman faces numerous challenges that can hinder its smooth execution. These challenges include manual voting processes, time-consuming vote counting, inadequate audit trails for voting results, and the added complexity of the Covid-19 pandemic, which has made it difficult to find solutions for conducting the elections. The researcher aims to develop a mobile E-voting application to minimize these obstacles and reduce the time and excessive paper expenditure in the execution of the Student Executive Board (BEM) Chairman elections at Esa Unggul Tangerang Campus. The design of this application utilizes the Extreme Programming (XP) methodology and employs the Dart programming language with the Flutter framework. To ensure the smooth operation of the application, a storage medium, commonly referred to as a database, is necessary. The database used in this research is called Firebase, which is a storage service created by Google that simplifies the researcher's task in developing the Mobile E-voting application. This research highlights the importance of using E-voting in elections, with the potential to expedite the process, reduce costs, enhance efficiency, and improve transparency.
Perancangan Aplikasi Mobile Android Dalam Program Mitigasi Bencana (Studi Kasus Disaster Management Center Dompet Dhuafa) Aulia Agustina Anjani; Meivi Kartikasari; Chaulina Alfianti Oktavia
Prosiding SISFOTEK Vol 7 No 1 (2023): SISFOTEK VII 2023
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Disasters are a series of events caused by natural and non-natural factors that result in environmental damage, loss of property, and psychological impacts. Natural disasters include earthquakes, tsunamis, volcanic eruptions, floods, droughts, and landslides, necessitating disaster mitigation efforts to minimize their effects. One such effort is the Disaster Management Center at Dompet Dhuafa, serving as the frontline in disaster response. During disaster management, Dompet Dhuafa's Disaster Management Center faces challenges such as a lack of public awareness about disaster-prone areas, a shortage of volunteer resources for disaster response, and reliance on manual reporting systems. The goal of this research is to develop an application that streamlines the reporting process for the Disaster Management Center at Dompet Dhuafa. Problem analysis in this study utilizes a fishbone diagram to identify issues, and system design employs UML diagrams, including use cases, activity diagrams, and sequence diagrams. The outcome of this research is an application that facilitates public access to information about disaster-prone areas and disaster reporting. Additionally, the application aids volunteers in reporting their activities while in the field. Black box testing is used to evaluate the application.
Klasifikasi Status Gizi Balita Menggunakan Algoritma K-Nearest Neighbor (KNN) Hafsah. HS; Nurul Azmi; Hazriani, Hazriani; Yuyun, Yuyun
Prosiding SISFOTEK Vol 7 No 1 (2023): SISFOTEK VII 2023
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Nutrition is an important component contained in food which includes carbohydrates, protein, vitamins, minerals, fat and water which are needed by the body for growth, development and maintenance which are used directly by the body to repair body tissue. Nutritional needs are an important factor in the growth and development of children, especially children aged under five years (toddlers), because what happens in the first five years determines their growth and development year after year. To achieve good growth and development, strong nutrition is needed. Assessment of the nutritional status of toddlers can be determined through human body measurements known as anthropometry. The reference standards for toddler nutritional status are Body Weight according to Age (WW/U) which describes the child's relative weight for age, Body Weight according to Height (WW/TB) which describes whether the child's weight is in accordance with his height growth and Height according to Age (TB/U) describes a child's height growth based on age. The method used to determine the nutritional status of toddlers is the KNN method, which is to find the closest distance between the evaluated data and a number of K neighbors closest to the test data. Toddler nutrition data uses 4 classifications, namely insufficient, normal, poor and more. The amount of data used in this research was 170 data with a data composition of 90% consisting of 150 training data and 10% testing data totaling 20 data. Data that is normalized using Z-Score gets an accuracy of 95%, class precision of 98.08% and class recall of 93.75%, data normalized using the min-max technique gets an accuracy of 85%, class precision of 95.00% and class recall of 79.17%, Meanwhile, KNN modeling without normalization produces an accuracy of 80%, precision of 82.4% and a class recall value of 75%.
Implementasi Algoritma K-Means dan Moora dalam Penentuan Prioritas Work Order PT Telkom Akses Divisi CCAN Diky Wahyudi B; Mirfan, Mirfan; Syamsu Alam
Prosiding SISFOTEK Vol 7 No 1 (2023): SISFOTEK VII 2023
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

PT Telkom Akses is a company engaged in the construction of development and manage service network infrastructure with every movement of the field team controlled using work orders commonly known as work orders. CCAN Assurance operations still determine priorities manually so that the risk of meeting targets is quite low. This research aims to design a system by implementing the K-MEANS and MOORA algorithms to overcome the problem of meeting the targets of each work order. The method used in this research is K-MEANS to group orders into 2 priority clusters, then MOORA will rank orders in the cluster. The K-MEANS method groups work orders into 2 priority clusters (critical links and normal links) and MOORA will rank work orders from each cluster so that the Makassar CCAN division can carry out order processing systematically where orders that enter the critical link with the highest rank become the top priority. by testing the system with division members with an assessment questionnaire, the results obtained were 87% satisfaction with the use of the new system.

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