Article Per Year (5 Year)
p-Index From 2021 - 2026
6.718
P-Index
This Author published in this journals
All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI SITEKIN: Jurnal Sains, Teknologi dan Industri Jurnal Teknologi Informasi dan Ilmu Komputer AGRIMOR Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer JOIV : International Journal on Informatics Visualization SemanTIK : Teknik Informasi Jurnal Abdimas BSI: Jurnal Pengabdian Kepada Masyarakat Faktor Exacta Abdimas Talenta : Jurnal Pengabdian Kepada Masyarakat JMM (Jurnal Masyarakat Mandiri) JTAM (Jurnal Teori dan Aplikasi Matematika) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Martabe : Jurnal Pengabdian Kepada Masyarakat KOMPUTIKA - Jurnal Sistem Komputer Mathvision : Jurnal Matematika GERVASI: Jurnal Pengabdian kepada Masyarakat Zonasi: Jurnal Sistem Informasi Range : Jurnal Pendidikan Matematika Jurnal Pengabdian kepada Masyarakat Nusantara Journal of Research in Mathematics Trends and Technology Jurnal Diferensial Journal Of Information And Technology Unimor (JITU) PROFICIO: Jurnal Pengabdian Masyarakat Jurnal Penelitian Inovatif AKM: Aksi Kepada Masyarakat Jurnal Sisfotek Global Jurnal Algoritma Prosiding Seminar Nasional Official Statistics IC Tech: Majalah Ilmiah Sanskara Ekonomi dan Kewirausahaan Parameter: Jurnal Matematika, Statistika dan Terapannya Kreativasi: Journal of Community Empowerment PADIMAS: Jurnal Pengabdian Masyarakat Journal of Mathematics, Computation and Statistics (JMATHCOS) Indonesian Journal of Statistics and Its Applications IC Tech: Majalah Ilmiah Media Pendidikan Matematika
Chrisinta, Debora
Program Studi Teknologi Informasi, Universitas Timor, Indonesia
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

Published : 50 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 50 Documents
Search

 1   2   3   4   5 
A Structural Equation Modelling Approach for College Students Financial Literacy Simarmata, Justin Eduardo; Chrisinta , Debora
Journal of Research in Mathematics Trends and Technology Vol. 4 No. 2 (2022): Journal of Research in Mathematics Trends and Technology (JoRMTT)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jormtt.v4i2.15849

Abstract

This research explores the dynamics of financial literacy among students in shaping future financial well-being. Using Structural Equation Modeling (SEM), it aims to uncover the relationship between financial literacy and students' interest in learning about finance. The data is derived from responses to a questionnaire from 200 students. The research reveals a path coefficient of 0.97 between financial literacy and literacy interest, indicating a strong positive relationship. This implies that 97% of the variation in financial literacy can be explained by literacy interest. Overall, the SEM model demonstrates a significant fit, providing valuable insights for enhancing financial literacy among college students.
Comparative Study of Support Vector Machine and Naive Bayes for Sentiment Analysis on Lecturer Performance Chrisinta, Debora; Simarmata, Justin Eduardo
Journal of Research in Mathematics Trends and Technology Vol. 5 No. 1 (2023): Journal of Research in Mathematics Trends and Technology (JoRMTT)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jormtt.v5i1.15864

Abstract

This study addresses the challenge of sentiment analysis within the Information Technology study program at Universitas Timor, aiming to compare the performance of Support Vector Machines (SVM) and Naive Bayes (NB) through 100 iterations. The dataset, comprising 21 instances of negative sentiment and 18 instances of positive sentiment, is analyzed using both methods, with accuracy and Area Under the ROC Curve (AUC) serving as key metrics. The sample size consists of 39 instances, and the results indicate significant variability in both accuracy and AUC, emphasizing the sensitivity of the models to dataset characteristics and random initialization. On average, SVM outperforms NB, with an accuracy of 0.5846 compared to 0.5075 and an AUC of 0.5916 compared to 0.4607.
Implementation of K-Means Clustering to Human Development Indicators in East Nusa Tenggara Simarmata, Justin Eduardo; Chrisinta, Debora; Purnomo, Miko
Journal of Research in Mathematics Trends and Technology Vol. 6 No. 2 (2024): Journal of Research in Mathematics Trends and Technology (JoRMTT)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jormtt.v6i2.17066

Abstract

K-Means has been adopted to group various cases related to the quality of humanresources and economic growth. This study aims to apply K-Means to thecharacteristics based on selected Human Development Index (HDI) indicators,namely the average length of schooling, the expectation of length of schooling andlife expectancy in Province of East Nusa Tenggara. The optimal cluster obtainedis 6 clusters. The cluster with the highest average value of all variables is in cluster1 which is Kupang City area. Meanwhile, condition cluster 6 provides the smallestlife expectancy value compared to other clusters. The smallest average variable ofschool length is in cluster 2. The regions that provide the smallest numberexpectation of length of schooling is in cluster 5.
Implementation of RShiny in Developing Interactive Learning Media for Analysis of Variance (ANOVA) Simarmata, Justin Eduardo; Chrisinta, Debora; Purnomo, Miko
Journal of Research in Mathematics Trends and Technology Vol. 7 No. 1 (2025): Journal of Research in Mathematics Trends and Technology (JoRMTT)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jormtt.v7i1.20167

Abstract

Effective learning is significantly influenced by the methods and media used in the teaching and learning process. However, many students still struggle to understand mathematical concepts due to the limited availability of interactive learning media. Therefore, this study aims to develop and evaluate the effectiveness of a technology-based interactive learning application designed to enhance students' understanding. The development of this application follows several stages, including needs analysis, design, implementation, testing, and evaluation. The application offers various features, such as interactive materials, practice exercises, and visual simulations, to facilitate better comprehension of concepts. The data used in this study consists of pretest and posttest results from 30 students who were given a series of basic questions, including calculating the mean, standard deviation, and performing simple statistical tests. Analysis using the Paired t-Test indicates a significant increase in posttest scores compared to pretest scores (p-value = 3.522e-08). Data visualization in the form of boxplots and line charts also demonstrates a trend of improved student performance after using the application. Thus, this study confirms that the developed interactive application is effective in enhancing student learning outcomes.
OPTIMASI JARAK TERPENDEK UNTUK MENCAPAI WISATA SUPER PRIORITAS INDONESIA DENGAN MENGGUNAKAN PENDEKATAN TRAVELING SALESMAN PROBLEM Purnomo, Miko; Simarmata, Justin Eduardo; Chrisinta, Debora
MathVisioN Vol 7 No 1 (2025): Maret 2025
Publisher : Prodi Matematika FMIPA Unirow Tuban

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55719/mv.v7i1.1478

Abstract

Sektor pariwisata sekarang ini menjadi salah satu hal yang sedang ditingkatkan oleh pemerintah Indonesia. Berbagai upaya telah dilakukan oleh pemerintah untuk meningkatkan persentasi pada sektor tersebut. Salah satu upaya pemerintah dalam meningkatkannya adalah dengan menjadikan beberapa destinasi di Indonesia menjadi Bali baru yang diharapkan bisa memberikan dampak pada pertumbuhan jumlah wisatawan. Untuk itu pemerintah menjadikan lima daerah di Indonesia sebagai wisata super prioritas yang diharapakan mampu meningkatkan sektor pariwisata di Indonesia. Kelima daerah tersebut adalah Danau Toba, Borobudur, Mandalika, Labuan Bajo dan Likupang. Dengan wilayah Indonesia yang sangat luas, tentu optimisasi jarak akan menjadi pertimbangan bagi para wisatawan. Selain jarak yang pendek, tentu akan berimbas pada waktu dan biaya yang akan dihabiskan untuk mencapai kelima wisata super prioritas ini. Pendekatan Matematis dengan Traveling Salesman Problem diharapkan mampu memecahkan solusi untuk mendapatkan rute optimal dalam penelitian ini. Dengan menggunakan aplikasi Solver yang terdapat pada fitur add-in pada Microsoft Excel dan Phyton telah mendapatkan rute optimal. Dengan titik keberangkatan awal adalah Jakarta sebagai provisi yang terletaknya Bandara Internasional Soekarno Hatta. Semulanya jarak total yang ditempuh adalah 11.848 km sampai kembali ke Jakarta, menjadi 10.823 km dengan rutenya adalah Jakarta – Danau Toba- Borobudur – Mandalika -Labuan Bajo – Likupang -Jakarta. Dengan jarak terpendek yang didapatkan, maka rute ini bisa menjadi pilihan untuk mencapai seluruh wisata super prioritas secara optimal.
EVALUASI KINERJA METODE CLUSTER ENSEMBLE DAN LATENT CLASS CLUSTERING PADA PEUBAH CAMPURAN Debora Chrisinta; I Made Sumertajaya; Indahwati Indahwati
Indonesian Journal of Statistics and Applications Vol 4 No 3 (2020)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v4i3.630

Abstract

Most of the traditional clustering algorithms are designed to focus either on numeric data or on categorical data. The collected data in the real-world often contain both numeric and categorical attributes. It is difficult for applying traditional clustering algorithms directly to these kinds of data. So, the paper aims to show the best method based on the cluster ensemble and latent class clustering approach for mixed data. Cluster ensemble is a method to combine different clustering results from two sub-datasets: the categorical and numerical variables. Then, clustering algorithms are designed for numerical and categorical datasets that are employed to produce corresponding clusters. On the other side, latent class clustering is a model-based clustering used for any type of data. The numbers of clusters base on the estimation of the probability model used. The best clustering method recommends LCC, which provides higher accuracy and the smallest standard deviation ratio. However, both LCC and cluster ensemble methods produce evaluation values that are not much different as the application method used potential village data in Bengkulu Province for clustering.
The Effect of Improving Human Resources for Student Interest in Selecting University on Food Security and Health: Structural Equation Modeling (SEM) Justin Eduardo Simarmata; Ferdinandus Mone; Debora Chrisinta; Winda Ade Fitriya B
RANGE: Jurnal Pendidikan Matematika Vol. 6 No. 1 (2024): Range Juli 2024
Publisher : Pendidikan Matematika UNIMOR

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32938/jpm.v6i1.6308

Abstract

The selection of State Universities by students has a significant impact on improving the quality of human resources, so it can also affect the improvement of food security and health. This study aims to understand the extent of students' interest in selecting university which contributes to improving human resources and can indirectly affect food security and health. This study uses the Structural Equation Modeling (SEM) method to analyze the interaction between latent variables. Data was collected through questionnaires from high school students on the Indonesia-Timor Leste border. The data used in this study include students' interest in selecting university (Y), education and knowledge (X1), skills and abilities (X2), food security (X3), and health (X4). The results showed that students' interest in selecting university had a significant correlation with improving human resources through education by 90% (X1) and 84% (X2). The impact of this increase in human resources is also seen in the improvement of food security and public health which provides a correlation of 98% (X3) and 81% (X4).
IMPLEMENTASI ALGORITMA CLUSTERING UNTUK PENGELOMPOKAN MAHASISWA BERDASARKAN RESPON TERHADAP METODE PEMBELAJARAN BAHASA INGGRIS KOMPUTER Simarmata, Justin Eduardo; Aprianti, Iis; Chrisinta , Debora; Purnomo, Miko
IC Tech: Majalah Ilmiah Vol 20 No 1 (2025): IC Tech: Majalah Ilmiah Volume XX No. 1 April 2025
Publisher : P3M Institut Widya Pratama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47775/ictech.v20i1.332

Abstract

Permasalahan yang dihadapi dalam proses pembelajaran Bahasa Inggris adalah rendahnya minat dan motivasi belajar mahasiswa yang dipengaruhi oleh persepsi mahasiswa terhadap metode pembelajaran yang digunakan, khususnya media video. Perbedaan persepsi ini dapat menyebabkan ketidakefektifan dalam penyampaian materi serta pencapaian hasil belajar yang tidak merata. Penelitian ini bertujuan untuk mengelompokkan mahasiswa berdasarkan respon mahasiswa terhadap media video dalam pembelajaran Bahasa Inggris, sehingga dapat diketahui karakteristik masing-masing kelompok dan strategi pembelajaran yang sesuai. Metode yang digunakan adalah analisis klaster dengan pendekatan Hierarchical Agglomerative Clustering menggunakan metode Ward. Data diperoleh dari kuesioner yang mencakup enam variabel, kemudian dilakukan pra-pemrosesan meliputi pembersihan data dan transformasi data kategorik menjadi numerik. Hasil analisis menunjukkan terbentuknya tiga klaster mahasiswa dengan distribusi yang relatif merata, di mana setiap klaster memiliki karakteristik persepsi dan motivasi belajar yang berbeda. Klaster pertama didominasi oleh sikap netral, klaster kedua menunjukkan respon positif terhadap video pembelajaran, dan klaster ketiga memperlihatkan preferensi terhadap video dengan konten percakapan. Hasil penelitian menunjukkan bahwa pengajar dapat menyesuaikan strategi dan konten pembelajaran dengan karakteristik masing-masing kelompok untuk meningkatkan efektivitas dan keterlibatan mahasiswa.
Prediction of Telkomsel 4G LTE Card Sales using The K-Nearest Neighbor Algorithm Martins, Alfiana Fontes; Rema, Yasinta Oktaviana Legu; Chrisinta, Debora; Matute, Alejandro Jr. V.; Seran, Krisantus Jumarto Tey
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 9 No. 1 (2025)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v9i1.1476

Abstract

Accurate sales prediction is a critical challenge in business decision-making, as factors such as data imbalance, outliers, and overfitting may compromise the reliability of predictive models. This study aims to develop a precise model for predicting card sales using the K-Nearest Neighbor (KNN) algorithm and to offer recommendations for improving prediction quality by addressing issues related to data imbalance and overfitting. The KNN algorithm is applied to analyze a card sales dataset, with preprocessing steps that include detecting missing values, handling outliers, and converting the target attribute into a categorical format. The optimal value of k is identified using the elbow method to determine the model's best accuracy. Findings indicate that the KNN model with k = 1 achieves 100% accuracy, though it shows signs of overfitting, which may hinder its generalizability to new data. Handling outliers and transforming data contributed to improving the model's performance. However, to enhance robustness, further testing with different k values and the use of cross-validation are recommended. Moreover, balancing the dataset and incorporating external variables such as promotional activities or market trends could support more reliable future predictions.
Structural Equation Modeling: The Influence of School Environment on Students' Interest in Selecting State University Simarmata, Justin Eduardo; Mone, Ferdinandus; Chrisinta, Debora
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 2 (2024): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i2.19921

Abstract

Despite prior research on student interest in colleges, this study focuses specifically on how the school environment, including individual factors, friends, and teachers, influences students' interest in attending a state university. Understanding these influences can help improve educational systems to better guide students towards higher education. This study aims to determine the influence of the school environment on students' interest in selecting a state university. This research employs a quantitative approach, utilizing structural equation modeling to analyze the relationships between variables. This study examines how a school environment, captured by twelve indicators across individual, friend, and teacher influences, impacts students' interest in state universities. Therefore, data retrieval based on questionnaires is designed accordingly based on latent variables. The sample in this study were 474 high school and vocational school students on the Indonesia-Timor Leste border, which is precisely located in Timor Tengah Utara Regency. The results showed that the school environment that came from individuals, partners, and teachers had a major influence on students' interest in choosing State University. Based on the analysis of structural equations, it was found that individual environments had a direct influence of 98%, partner environments had an indirect influence of 90%, and teachers also indirectly affected 71%. This study contributes to the field by quantifying the distinct influences of individual, peer, and teacher aspects of the school environment on students' interest in attending state universities. This knowledge can inform the development of targeted interventions to improve educational guidance and support student decision-making.
Co-Authors Abi, Roberto afandi, iswan Afdhal Chatra Perdana Agustinus Palmarius Tae Abi Agustinus Yoseph Leu Aldianus Bria Anastasia Kadek Dety Lestari Baldemor, Milagros R. Baso, Budiman Benu, Luky Wandika Bete, Hendrika Binsasi, Eva Bone, Dominifridus Chamdi, Achmad Nur Christofel John Bernhard Sendow Dian Grace Ludji Erlina, Nia Fallo, Kristoforus Febrya Christin Handayani Buan Fetronela Rambu Bobu Fransiskus Yulius Dhewa Kadju Gelu, Leonard Peter Gelu, Leonard Peter Gerhard-Wilhelm Weber Handayani, Rika Hevi Herlina Ullu Hijriani, Lailin Hutubessy, Aditya I Made Sumertajaya Ida Bagus Putu Mardana Iis Aprianti Indahwati Indra Budaya, Indra Januario Resky A. Sekab Jaya Santoso Josua Sahala Juventianus Kenjam Kabut, Stefanus LUDGARDIS LEDHENG Made Santo Gitakarma Manalu, Adelya I Maneno, Regolinda Manhitu, Emerensiana Okan Margareta Mamuit Ninu Maria Metriana Seran Maria Naimnule Marselinus Banu Martins, Alfiana Fontes Matute, Alejandro Jr. V. Mau, Paskalia Yunita Melkisedik Bukifan Miko Purnomo mone, ferdinandus Naimnule, Maria Naisau, Angela Cristina Ni Wayan Sukerti Pakaenoni, Lusilia Dos Santos Patricia Gertrudis Manek Peter Gelu, Leonard Purba, Switamy Angnitha Risald Simarmata, Justin Eduardo Siprianus Septian Manek Switamy Angnitha Purba Tavares, Ricson Tey Seran, Krisantus Jumarto Tulus Martua Sihombing Ture Simamora Veithzal Rivai Zainal Venantius Oskar Nahak Winda Ade Fitriya B Wua Laja, Yosepha Patricia Yasinta O.L Rema Yohanes Jefrianus Kehi Yoseph Pius Kurniawan Kelen