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Central Actor Identification of Crime Group using Semantic Social Network Analysis Tahalea, Sylvert Prian; SN, Azhari
Indonesian Journal of Information Systems Vol 2, No 1 (2019): Agustus 2019
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

The Police as law enforcers who authorize in terms of social protection are expected to do both the prevention and investigation efforts also the settlement of criminal cases that occurred in the society. This research can help police to identify the main actor faster and leads to solving crime-cases. The use of overall centrality is very helpful in determining the main actors from other centrality measures. The purpose of this research is to identify the central actor of crimes done by several people. Semantic Social Network Analysis is used to perform central actor identification using five centrality measurements, such as degree centrality, betweenness centrality, closeness centrality, eigenvector centrality, and overall centrality. As for the relationship between actors, this research used social relation such as friendship, colleague, family, date or lover, and acquaintances. The relationship between actors is measured by first four centrality measures then accumulated by overall centrality to determine the main actor. The result showed 80.39% accuracy from 102 criminal cases collected with at least 3 actors involved in each case.

Analisis Sistem Informasi Eksekutif menggunakan User Experience Questionnaire (UEQ) Putra, I Nyoman Tri Anindia; Kartini, Ketut Sepdyana; Aditama, Putu Wirayudi; Tahalea, Sylvert Prian
International Journal of Natural Science and Engineering Vol 5, No 1 (2021)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/ijnse.v5i1.29289

To increase user satisfaction with information systems requires analysis and testing of the system. The User Experience Questionaire (UEQ) is a tool used to measure the level of user satisfaction with a system through a questionnaire. This study focuses on the analysis of executive information systems at STMIK STIKOM Indonesia in order to improve information systems, especially in system design. The six rating scales that will be sought in this study include attractiveness, perspicuity, efficiency, dependability, stimulation, and novelty. Based on the test results using the UEQ method, the executive information system STMIK STIKOM Indonesia obtained Good results.

Implementation DeLone & McLean IS Success Model for Research and Community Service Management Information System Evaluation Awang Hendrianto Pratomo; Riza Prapascatama Agusdin; Sylvert Prian Tahalea; Nur Heri Cahyana
Techno LPPM Vol 7, No 2 (2021)
Publisher : Universitas Pembangunan Nasional Veteran Yogayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

SRIKANDI is an information system managed by LPPM that manages research and lecturer service within the UPN "Veteran" Yogyakarta. SRKANDI in its implementation has never been evaluated, therefore in this reserach SRIKANDI was evaluated. The evaluation was carried out using the DeLone & McLean IS Success Model with 150 data obtained from distributing questionnaires to lecturers who had used SRIKANDI. The approach used in this research is quantitative by using regression analysis to test the twelve hypotheses that exist with the successful implementation of SRIKANDI as an information system.

Pengembangan Sistem Penelusuran Alumni berbasis cross-platform dengan Framework Ionic Sylvert Prian Tahalea; Bambang Yuwono; Wilis Kaswidjanti
Seminar Nasional Informatika (SEMNASIF) Vol 1, No 1 (2020): Peran Digital Society dalam Pemulihan Pasca Pandemi
Publisher : Jurusan Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar

AbstractTracer study is important in improving the quality of education in higher education. Feedback from alumni regarding college experience and ability gained during college becomes a parameter to measure how successful a curriculum is run. In addition, the workplace is also a reference to success. The higher the level of the company where the work can show the capacity of alumni in competing in the world of work by capitalizing on the knowledge gained from the college coupled with the ability to adapt and develop themselves. This research aims to make it easier for alumni to assist universities in the alumni search process which will then be the basis for improving and developing the educational curriculum of the study program.Tracer study systems developed using the Ionic, Angular JS, and NodeJS frameworks. System development uses rapid application development (RAD) method to enable faster system development and prioritize alumni comfort as users. The use of the Ionic framework allows applications to be accessed from various platforms such as the web, android, and iOS.The development of a tracer study system using the Ionic framework allows users to use applications based on a platform that is convenient to use. This tracer study system is able to present alumni information as well as facilitate the management of majors in the management of alumni data.Keywords : ionic, cross-platform, tracer studyTracer study penting dalam meningkatkan kualitas pendidikan di perguruan tinggi. Umpan balik dari alumni mengenai pengalaman dan kemampuan perguruan tinggi yang diperoleh selama kuliah menjadi parameter untuk mengukur seberapa sukses kurikulum dijalankan. Selain itu, tempat kerja juga menjadi acuan keberhasilan. Semakin tinggi tingkat perusahaan dapat menunjukkan kapasitas alumni dalam bersaing di dunia kerja dengan memanfaatkan ilmu yang diperoleh dari perguruan tinggi ditambah dengan kemampuan beradaptasi dan pengembangan diri. Penelitian ini bertujuan untuk mempermudah para alumni membantu perguruan tinggi dalam proses pencarian alumni yang kemudian akan menjadi dasar untuk meningkatkan dan mengembangkan kurikulum pendidikan program studi.Sistem tracer study dikembangkan menggunakan kerangka kerja Ionic, Angular JS, dan NodeJS. Pengembangan sistem menggunakan metode rapid application development (RAD) untuk memungkinkan pengembangan sistem yang lebih cepat dan mengutamakan kenyamanan alumni sebagai pengguna. Penggunaan kerangka kerja Ionic memungkinkan aplikasi diakses dari berbagai platform seperti web, android, dan iOS. Pengembangan sistem tracer study menggunakan kerangka kerja Ionic memungkinkan pengguna untuk menggunakan aplikasi berdasarkan platform yang nyaman digunakan. Sistem pencarian alumni mampu menyajikan informasi alumni sekaligus mempermudah pengelolaan jurusan dalam pengelolaan data alumni.Kata Kunci : ionic, cross-platform, tracer study

Central Actor Identification of Crime Group using Semantic Social Network Analysis Sylvert Prian Tahalea; Azhari SN
Indonesian Journal of Information Systems Vol. 2 No. 1 (2019): Agustus 2019
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v2i1.2354

The Police as law enforcers who authorize in terms of social protection are expected to do both the prevention and investigation efforts also the settlement of criminal cases that occurred in the society. This research can help police to identify the main actor faster and leads to solving crime-cases. The use of overall centrality is very helpful in determining the main actors from other centrality measures. The purpose of this research is to identify the central actor of crimes done by several people. Semantic Social Network Analysis is used to perform central actor identification using five centrality measurements, such as degree centrality, betweenness centrality, closeness centrality, eigenvector centrality, and overall centrality. As for the relationship between actors, this research used social relation such as friendship, colleague, family, date or lover, and acquaintances. The relationship between actors is measured by first four centrality measures then accumulated by overall centrality to determine the main actor. The result showed 80.39% accuracy from 102 criminal cases collected with at least 3 actors involved in each case.

K-MEANS AND ELBOW METHOD FOR CLUSTER ANALYSIS OF ELEMENTARY SCHOOL DATA Vynska Amalia Permadi; Sylvert Prian Tahalea; Riza Prapascatama Agusdin
PROGRES PENDIDIKAN Vol. 4 No. 1 (2023): January 2023
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/prospek.v4i1.328

This research was conducted to find the groups of elementary schools in the Special Capital Region of Jakarta, also known as DKI Jakarta. Elementary school data were selected because it is the first stage of formal education in Indonesia. This research used K-means clustering with the elbow method to determine optimal cluster numbers. The optimal cluster number is three with Cluster 2 having the most members, followed by Cluster 1 and Cluster 0. The data distribution of Cluster 2 shows that the second-most student body and public schools located in East and West Jakarta have an adequate student-to-teacher ratio based on Article 17 of Government Regulation 74, 2008.

Penerapan Aturan Asosiasi untuk Rule Mining pada Piala Dunia FIFA 2022 Sylvert Prian Tahalea; Vynska Amalia Permadi
Progresif: Jurnal Ilmiah Komputer Vol 19, No 1: Februari 2023
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v19i1.1063

Football strategy comes from learning and evaluation of previous matche, but there are only a few research that conducted to explore the synergies between players. This research was conducted to implement the data mining method; and association’s rule in the sports data case study. Football is already embracing new technology as part of its ecosystem. This research used a data mining method to explore and analyze the passing route of a football team in the biggest football tournament, FIFA World Cup 2022, held in Qatar. The data was collected from the Sports References website and preprocessed before being mined. An association rule is constructed using an apriori algorithm by creating the item sets, calculating the support and confidence value, and defining the rules. The results showed the formation of 3 association rules with a confidence limit of 95%. Rule mining using an apriori association provides the possibility of an antecedent and consequent combination, which is a combination of the order in which the ball moves from the first player to the third player until the occurrence of a goal.Keywords: Association rule; Data mining; A priori algorithm; Soccer AbstrakPengembangan strategi sepak bola dilakukan dengan melakukan evaluasi dari pertandingan yang telah dilakukan sebelumnya, akan tetapi belum banyak penelitian yang dilakukan untuk melakukan evaluasi terhadap sinergi antar pemain pada suatu permainan. Penelitian ini dilakukan dengan tujuan untuk mengimplementasikan metode data mining pada bidang olahraga, salah satunya sepak bola, yang telah menggunakan teknologi sebagai bagian dari ekosistem permainan. Metode data mining digunakan untuk mengeksplorasi dan menganalisis operan pada tim sepak bola pada perhelatan turnamen Piala Dunia FIFA 2022 yang dilaksanakan di Qatar. Data yang dikumpulkan dari website Sport References dikenakan prapemrosesan data sebelum diolah. Penerapan aturan asosiasi dengan algoritme Apriori dilakukan dalam beberapa langkah, seperti pembentukan itemset, perhitungan nilai support dan confidence, hingga penentuan aturan atau rule. Hasil penelitian menunjukan pembentukan 3 aturan asosiasi dengan batasan confidence 95%. Rule mining menggunakan algoritme asosiasi Apriori memberikan kemungkinan kombinasi antecedent dan consequent yang merupakan kombinasi urutan perpindahan bola dari pemain pertama hingga pemain ketiga sampai dengan terjadinya goal.Kata kunci: Aturan asosiasi; Data mining; Algoritme Apriori; Sepak bola

Optimising the Fashion E-Commerce Journey: A Data-Driven Approach to Customer Retention Fadhila, Hasna Luthfiana; Permadi, Vynska Amalia; Tahalea, Sylvert Prian
Knowledge Engineering and Data Science Vol 7, No 1 (2024)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um018v7i12024p58-70

A fashion e-commerce company offers a wide range of products from domestic and international brands that are popular with young people. However, there has been an increase in non-organically acquired customers, many of whom do not return to make repeat purchases. This has led to a higher customer churn rate, with a significant proportion of non-organically sourced customers failing to become repeat purchasers. Consequently, a churn analysis and prediction model were developed to address this issue. This paper employs the Recency, Frequency, and Monetary (RFM) framework for churn analysis and prediction. The framework is underpinned by three key dimensions: last purchase recency, purchase frequency, and total transaction value. Seven machine learning algorithms were evaluated to identify the optimal approach. Following a comparative analysis of these models, Random Forest emerged as the superior algorithm, demonstrating an accuracy of 0.99, precision of 0.97, recall of 0.99, ROC AUC of 0.98, and F1-score of 0.97. Consequently, this model will be utilized for churn prediction. Based on the analysis and modelling, several recommendations are offered to enhance customer retention for the fashion e-commerce platform. In addition to predicting churn, this paper provides insights into potential refinements to the churn prediction model, such as real-time monitoring, personalized customer experiences, analysis of customer feedback, and lifetime value analysis.

Analisis Sistem Informasi Eksekutif Menggunakan User Experience Questionnaire (UEQ) Putra, I Nyoman Tri Anindia; Kartini, Ketut Sepdyana; Aditama, Putu Wirayudi; Tahalea, Sylvert Prian
International Journal of Natural Science and Engineering Vol. 5 No. 1 (2021): April
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Sistem informasi eksekutif merupakan salah satu sistem yang digunakan untuk menganalisa masalah yang ada dalam suatu organisasi, serta memfasilitasi kebutuhan informasi yang berkaitan dengan pemenuhan tujuan organisasi. Namun pada penggunaan SIE belum terdapat analisi kajian yang membahas mengenai tingkat kepuasan user terhadap sistem yang digunakan. Sehingga tujuan dari penelitian ini adalah untuk memberbaiki sistem yang ada serta meningkatkan kepuasan user terhadap sistem informasi. Penelitia ini menggunakan jenis penelitian deskriptif dengan jumlah populasi sebanyak 28 orang. Teknik sampling yang digunakan dalam penelitian ini adalah teknik teknik sampling jenuh, yakni menggunakan seluruh populasi sebagai sampel penelitian. Metode pengumpulan data dalam penelitian ini yang digunakan dalam penelitian ini yakni metode dilakukan dengan menggunakan metode User Experience Questionaire (UEQ), dengan tahapan pengumpulan data yang terdiri dari tahapan merancang konsep dan kajian pustaka, identifikasi masalah, pengumpulan data, analisis data dan menarik kesimpulan. Hasil dalam penelitian ini menunjukkan bahwa analisis hasil pengujian sistem informasi eksekutif dengan menggunakan metode User Experience Questionnaire memperoleh dua parameter yang dengan nilai Above Average yaitu stimulasi dan kebaruan, sehingga perlu dilakukan pengembangan penyegaran user interface terhadap sistem informasi eksekutif tersebut.

Implementation DeLone & McLean IS Success Model for Research and Community Service Management Information System Evaluation Pratomo, Awang Hendrianto; Agusdin, Riza Prapascatama; Tahalea, Sylvert Prian; Cahyana, Nur Heri
Journal TECHNO Vol. 7 No. 2 (2021): November
Publisher : Universitas Pembangunan Nasional Veteran Yogayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/journal techno.v7i2.6298

SRIKANDI is an information system managed by LPPM that manages research and lecturer service within the UPN "Veteran" Yogyakarta. SRKANDI in its implementation has never been evaluated, therefore in this reserach SRIKANDI was evaluated. The evaluation was carried out using the DeLone & McLean IS Success Model with 150 data obtained from distributing questionnaires to lecturers who had used SRIKANDI. The approach used in this research is quantitative by using regression analysis to test the twelve hypotheses that exist with the successful implementation of SRIKANDI as an information system.

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