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All Journal Pelita Eksakta Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Mosharafa: Jurnal Pendidikan Matematika Leibniz: Jurnal Matematika UNP Journal of Statistics and Data Science Mathematical Journal of Modelling and Forecasting
Mukhti, Tessy Octavia
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Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Mathematics Physics Social Sciences Other

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Metode Density Based Spatial Clustering of Applications with Noise (DBSCAN) dalam Mengelompokkan Provinsi di Indonesia Berdasarkan Kasus Kriminalitas Tahun 2022 Miftahurrahmi, Syifa; Zilrahmi; Amalita, Nonong; Mukhti, Tessy Octavia
UNP Journal of Statistics and Data Science Vol. 2 No. 3 (2024): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol2-iss3/203

Abstract

Based on Central Statistics Agency 2023 data, in 2022 there was a significant increase in the number of crime cases in Indonesia compared to 2021, from 239,481 cases to 372,965 cases. The increase in the number of criminal acts occurred along with community activities that began to loosen up after the Covid-19 pandemic. The types of crimes that occur in Indonesia themselves vary, ranging from murder, theft, drug-related crimes, and others. This research will cluster provinces in Indonesia based on crime cases with certain types of crimes in 2022 using the Density Based Spatial Clustering of Applications with Noise (DBSCAN) method. The results of the study are expected to help the government and police in an effort to deal with crime in Indonesia. Clustering using the DBSCAN method produces 2 clusters with a silhouette coefficient value of 0,68. The resulting cluster is cluster 0 with noise category consisting of 5 provinces with a high number of crime cases, while cluster 1 consists of 29 provinces with a low number of crime cases.
Classification of Determining Factors for Eligibility of Extreme Poverty Social Assistance Recipients in Dumai City for 2024 Using CHAID Pajrini, Nurul Hasni; Fitria, Dina; Mukhti, Tessy Octavia
UNP Journal of Statistics and Data Science Vol. 3 No. 1 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss1/354

Abstract

Poverty is one of the goals of the Sustainable Development Goals (SDGs). Poverty is a condition in which an individual falls below the standard minimum value of basic needs, both food and non-food. One of the efforts by the Indonesian government to alleviate poverty is through fulfilling needs in various sectors. Although the distribution of social assistance has been successfully implemented, there are still issues in determining beneficiaries who are not properly targeted. Therefore, it is necessary to identify the significant factors influencing the eligibility of social assistance recipients. The application of the CHAID method in classifying the determining factors for eligibility of extreme poverty social assistance recipients in Dumai City for 2024 shows that the significant factors influencing the eligibility status of extreme poverty social assistance recipients in Dumai City for 2024 are house size and neighbors' testimonies. The classification model's accuracy in determining the eligibility factors for extreme poverty social assistance recipients in Dumai City for 2024 is 87.70%.
ANALISIS KEMISKINAN DI INDONESIA MENGGUNAKAN LOCAL INDICATOR OF SPATIAL ASSOCIATION DAN SPATIAL ERROR MODEL Khairani, Putri Rahmatun; Kurniawati, Yenni; Amalita, Nonong; Mukhti, Tessy Octavia
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 6 No. 1 (2025): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v6i1.966

Abstract

Poverty in Indonesia remains a significant socio-economic challenge with notable regional disparities. The eastern provinces, particularly Papua, Maluku, and East Nusa Tenggara, experience persistently high poverty rates, suggesting a strong spatial influence. This study examines the spatial distribution of poverty using the Local Indicators of Spatial Association and the Spatial Error Model with 2024 data from the Indonesian Central Statistics Agency (BPS) for 38 provinces. The analysis employs a K-Nearest Neighbors weighting matrix (k = 10) for spatial dependencies. The LISA results identify High-High poverty clusters in Papua, Maluku, and East Nusa Tenggara. In contrast, Low-Low clusters are concentrated in Java and Bali, indicating a strong spatial pattern (Moran’s I = 0.4448). SEM findings reveal that the Gini index (β = 29.97) and population density (β = 0.016) significantly influence poverty, whereas inflation and total population do not. The model explains 76.1% of poverty variance (R² = 0.760966), highlighting its superiority over traditional regression models. These findings underscore the need for spatially adaptive policies to address poverty effectively. Policymakers should prioritize equitable economic development, regional investment, and infrastructure improvements, particularly in high-poverty clusters. Integrating spatial econometric models with KNN provides deeper insights into interregional disparities, supporting more precise and inclusive development strategies
Enhancing Technology-Based Learning through Wordwall Application: A Case Study at SMAN 1 Ampek Angkek Mukhti, Tessy Octavia; Fitri, Fadhilah; Sari, Widia Kemala
Pelita Eksakta Vol 8 No 01 (2025): Pelita Eksakta, Vol. 8, No. 1
Publisher : Fakultas MIPA Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/pelitaeksakta/vol8-iss01/260

Abstract

The explosive growth of technology necessitates educators staying current with the latest innovations, especially for technology-based learning in the sciences. However, at SMA Negeri 1 Ampek Angkek, it was discovered that several teachers have varying levels of technological proficiency, face resource constraints, and struggle to develop interactive learning materials. As a result, students often lose interest in learning. To solve this problem, a training session on using the Wordwall application, a web-based educational tool that includes interactive tools like puzzles, flashcards, and quizzes, was held. The workshop aimed to help teachers create more interactive and interesting teaching methods, as well as improve their ability to use educational technology. As a result, the training session improved the quality of teaching at SMA Negeri 1 Ampek Angkek, making the classroom atmosphere more dynamic and interesting for students.
Comparison of the Fuzzy Time Series Chen Model and the Heuristic Model in Forecasting the Number of International Tourists in West Sumatra Rizki Akbar; Fitri, Fadhilah; Vionanda, Dodi; Mukhti, Tessy Octavia
Mathematical Journal of Modelling and Forecasting Vol. 2 No. 1 (2024): June 2024
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/mjmf.v2i1.20

Abstract

The Fuzzy Time Series Chen and Heuristic are two forecasting methods based on fuzzy logic used to predict values in time series. The FTS Chen and Heuristic models have almost identical forecasting processes, but the main difference lies in how they develop fuzzy logical relationships. The FTS Chen model uses Fuzzy Logical Relationship Groups obtained from the results of Fuzzy Logical Relationships for the forecasting process. On the other hand, the FTS Heuristic model uses Fuzzy Logical Relationships directly in the forecasting process. Fuzzy Logical Relationships are a collection of fuzzy logical relationships used to connect values in time series. By using Fuzzy Logical Relationships, the Heuristic model can predict values in time series more accurately and effectively. The forecasting is done to plan the development of tourism infrastructure, determine service needs, and optimize tourism promotion. The data shows that the number of foreign tourists visiting West Sumatra has continued to grow from 2006 to 2023. The comparison of the accuracy of the forecasting results of FTS Chen and Heuristic models for foreign tourists in West Sumatra yielded a MAPE of 0.241% for FTS model Chen and 0.194% for FTS model Heuristic. This indicates that the best forecasting model for foreign tourists is the Heuristic model due to its lower MAPE value.
Implementasi Metode Naïve Bayes dengan Random Oversampling pada Klasifikasi Keluarga Berisiko Stunting Suliswati, Yeni; Mukhti, Tessy Octavia; Syafriandi, Syafriandi; Salma, Admi
Leibniz: Jurnal Matematika Vol. 5 No. 02 (2025): Leibniz: Jurnal Matematika
Publisher : Program Studi Matematika - Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas San Pedro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59632/leibniz.v5i02.610

Abstract

Stunting masih menjadi salah satu masalah kesehatan serius yang memiliki dampak jangka panjang terhadap tumbuh kembang dan kognitif anak. Keluarga memiliki peran penting dalam mencegah terjadinya stunting, sehingga identifikasi dini keluarga yang berisiko melahirkan anak stunting menjadi langkah awal dalam upaya pencegahan. Penelitian ini bertujuan untuk mengklasifikasikan keluarga berisiko stunting menggunakan metode Naïve Bayes serta mengevaluasi pengaruh teknik Random Oversampling (ROS) terhadap performa model pada data tidak seimbang. Data pada penelitian ini terdiri dari 7 variabel independen dan 1 variabel dependen yang bersumber dari Perwakilan Badan Kependudukan dan Keluarga Berencana Nasional (BKKBN) Sumatera Barat. Hasil evaluasi menunjukkan bahwa model Naïve Bayes memiliki akurasi sebesar 92,46% dan sensitivitas 100% serta spesifisitas 69,14% yang menunjukkan kelemahan dalam mengidentifikasi keluarga berisiko. Metode ROS-Naïve Bayes menunjukkan peningkatan performa model dimana diperoleh akurasi sebesar 99,87%, sensitivitas 99,83%, dan spesifisitas 100%. Hal ini menunjukkan bahwa implementasi Naïve Bayes dengan ROS efektif dalam mengatasi ketidakseimbangan data dan meningkatkan performa model. Faktor utama yang memengaruhi risiko stunting meliputi keikutsertaan KB modern, sanitasi, usia ibu dan jumlah anak.
Factors Influencing Mathematics Learning in Students in the Alor Islands Region Adrianingsih, Narita Y.; Sari, Nilam N.; Padafani, Lekison; Mukhti, Tessy Octavia
Mosharafa: Jurnal Pendidikan Matematika Vol. 13 No. 1 (2024): January
Publisher : Department of Mathematics Education Program IPI Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31980/mosharafa.v13i1.1974

Abstract

Mathematics is a fundamental skill for all individuals, making it essential for every child to achieve proficiency. Several factors influence mathematics learning achievement, which can be categorized into internal and external factors. This study aims to identify the factors affecting mathematics achievement among junior high school students in the Teluk Mutiara District of Alor. The research employed a multiple linear regression analysis method. Data were collected through questionnaires completed by 7th-grade students from junior high schools in the district. The results indicated that factors such as the mother's educational background, the father's occupation, the amount of time allocated for studying mathematics, and the students' interest in learning mathematics significantly influenced their mathematics achievement. Matematika sangat penting bagi setiap orang, oleh karena itu setiap anak harus menguasai matematika. Dalam pembelajaran matematika, terdapat beberapa faktor yang mempengaruhi prestasi belajar matematika yaitu faktor internal dan faktor eksternal. Penelitian ini bertujuan untuk mengetahui faktor-faktor apa saja yang mempengaruhi prestasi belajar matematika pada siswa SMP di Kecamatan Teluk Mutiara Alor. Penelitian ini menggunakan metode analisis regresi linier berganda. Metode pengumpulan data yang digunakan adalah dengan cara mengisi angket yang diisi oleh siswa SMP di Kecamatan Teluk Mutiara. Subjek penelitian adalah anak SMP kelas 7 di Kecamatan Teluk Mutiara Alor. Hasil penelitian menunjukkan bahwa faktor-faktor yang mempengaruhi prestasi belajar matematika pada siswa SMP di Kecamatan Teluk Mutiara Alor adalah pendidikan ibu, pekerjaan ayah, waktu belajar matematika, dan minat belajar matematika.
Digitalization Data of Talawi Mudiak Syafriandi, Syafriandi; Fitria, Dina; Amalita, Nonong; Kurniawati, Yenni; Permana, Dony; Fitri, Fadhilah; Martha, Zamahsary; Mukhti, Tessy Octavia
Pelita Eksakta Vol 8 No 2 (2025): Pelita Eksakta, Vol. 8, No. 2
Publisher : Fakultas MIPA Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/pelitaeksakta/vol8-iss2/293

Abstract

Desa Talawi Mudiak menghadapi tantangan dalam pengelolaan data kependudukan. Meskipun mereka telah menyusun RPJMD 2022-2027 yang mengacu pada SDG's, pendataan yang dilakukan masih terbatas pada aspek kependudukan dan demografi. Padahal, pemutkhiran data harus mencakup 17 pilar SDg's agar dapat digunakan sebagai dasar dalam perencanaan pembangunan desa. Selain itu, keterbatasan akses internet dan kurangnya pemanfaatan teknologi informasi juga menjadi kendala pengembangan sistem informasi desa yang lebih komprehensif. Program Studi S1 Statistika hadir dalam menjembatani pencapaian beberapa pilar itu melalui pemutakhiran data hingga dilitalisasinya. Kegiatan diawali dengan pengumpulan data awal, perhitungan kerangka sampling, pelaksanaan survei, dan pemrosesan data pasca survei hingga diperoleh suatu kesimpulan yang dapat digunakan untuk pembangunan desa. Kegiatan melibatkan banyak pihak, mulai dari dosen program studi, perangkat desa, mahasiswa, dan masyarakat. Hasil yang diperoleh berupa data yang mutakhir dan sebuah buku berisikan kondisi Desa Talawi Mudiak tahun 2025.
Improving the Competence of Elementary School Teachers in Child-Friendly Sexual Education through a Statistics Based Workshops and Effective Practices Mukhti, Tessy Octavia; Yusra, Zulmi Yusra; Sari, Widia Kemala; Taslim, Fauziah
Pelita Eksakta Vol 8 No 2 (2025): Pelita Eksakta, Vol. 8, No. 2
Publisher : Fakultas MIPA Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/pelitaeksakta/vol8-iss2/294

Abstract

Sexual violence against children is a serious issue requiring comprehensive prevention efforts. Data from the Ministry of Women’s Empowerment and Child Protection indicate an increase in cases from 2020 to 2024, highlighting the urgency of sexual education at the elementary school level. However, teachers in Gugus 2, Kecamatan VI Koto, Kabupaten Agam face limited access to updated training and resources on sensitive topics such as sexuality. This community service activity aimed to enhance teachers’ knowledge, attitudes, and readiness in delivering child-friendly sexual education. The program was implemented in five stages: socialization, observation with interviews, material provision, technology application, and evaluation. Results showed improved teacher understanding and skills in teaching sexual education through a phased approach introducing body privacy, recognizing dangers, and developing self-protection. The integration of digital media, such as Canva-based infographics and interactive coding, further supported learning effectiveness. Evaluation indicated increased teacher comprehension across all topics.
Stratified Cox Regression Approach to Identifying Prognostic Factors for Survival in Breast Cancer Patients Ervandi, Dhio; Novriani, Aisyah; Luthfiyah, Andini Diva; Siregar, Fauzan Al Hamdani; Mukhti, Tessy Octavia
UNP Journal of Statistics and Data Science Vol. 3 No. 4 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss4/418

Abstract

The most common type of cancer that affects women is Breast cancer. In 2022, 2.3 million women were diagnosed with breast cancer, and 670,000 deaths were recorded globally. By 2040, it is estimated that breast cancer will increase by 40%, reaching 3 million annually with the number of deaths increasing by 50% to 1 million in 2020. This highlights breast cancer as a serious threat to world health. This study utilized secondary data from METABRIC or the Molecular Taxonomy of Breast Cancer International Consortium obtained from the website www.kaggle.com/datasets/raghadalharbi/breast-cancer-gene-expression-profiles-metabric/data. The independent variables analyzed were, Age at Diagnosis (X­­1), Surgery Type (X­­2), Chemotherapy (X­­3), Hormone Therapy (X­­4), Tumor Size (X­­5), Radio Therapy (X­­6), Pam50. The dependent variables were Survival Time (Overall Survival Month) and Patient Status. In this study, we used the Stratified Cox model to predict the predictor variables of survival time. The total number of patients used was 18886, with 1080 censored patients and 788 uncensored patients. The Stratified Cox model without interaction revealed that the patients who underwent breast-conserving surgery had a 1.35 times higher risk of death compared to those who underwent mastectomy. Patients who received chemotherapy had a 2.01 times higher risk of death than those who did not, while patients who did hormone therapy had a 1.83 times higher risk of death than those who did not undergo this therapy.
Co-Authors Adrianingsih, Narita Y. Dina Fitria, Dina Dodi Vionanda Ervandi, Dhio Fitri, Fadhilah Khairani, Putri Rahmatun Luthfiyah, Andini Diva Miftahurrahmi, Syifa Nonong Amalita Novriani, Aisyah Padafani, Lekison Pajrini, Nurul Hasni Permana, Dony Rizki Akbar Salma, Admi Sari, Nilam N. Sari, Widia Kemala Siregar, Fauzan Al Hamdani Suliswati, Yeni Syafriandi Syafriandi Taslim, Fauziah Yenni Kurniawati Yusra, Zulmi Yusra Zamahsary Martha Zilrahmi, Zilrahmi