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All Journal Imajiner: Jurnal Matematika dan Pendidikan Matematika 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
Tessy Octavia Mukhti
Universitas Negeri Padang
Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Mathematics Physics Social Sciences Other

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Data Analysis and Visualization Training on Microsoft Excel Using Artificial Intelligence At SMA N 1 Ampek Angkek Kabupaten Agam Tessy Octavia Mukhti; Fadhilah Fitri; Devni Prima Sari
Pelita Eksakta Vol 6 No 2 (2023): Pelita Eksakta, Vol. 6, No. 2
Publisher : Fakultas MIPA Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/pelitaeksakta/vol6-iss2/212

Abstract

Based on observations and discussions with several teachers at SMA N 1 Ampek Angkek Kabupaten Agam, problems were found in describing and analyzing the significance of the development of students' abilities. The next problem which is no less important is the difficulty of measuring the effectiveness of the teaching materials used in the classroom. To improve the quality of learning, teachers are required to optimize the learning process by making students actively involved and making learning more interesting for them. To overcome this problem, data analysis and visualization training was carried out in Microsoft Excel using artificial intelligence at SMA N 1 Ampek Angkek Kabupaten Agam.
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 1 (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.
Application of Area Sampling Frame for Digitizing Household Data in Talawi Mudiak to Support Sustainable Development Goals 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.
Pengelompokan Pengguna Spotify Berdasarkan Data Tipe Campuran Menggunakan Algoritma K-Prototype Luthfiyah, Andini Diva; Mukhti, Tessy Octavia
Imajiner: Jurnal Matematika dan Pendidikan Matematika Vol 8, No 3 (2026): Imajiner: Jurnal Matematika dan Pendidikan Matematika
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/imajiner.v8i3.27264

Abstract

Competition in streaming music services requires a better understanding of user behavior and churn tendencies. This study aims to segment Spotify users and analyze churn patterns based on demographic characteristics and service usage behavior using the K-Prototypes method on mixed-type data. The optimal number of Cluster was determined using the Elbow method, while the churn variable was used to evaluate the clustering results. The analysis shows that three user cluster were formed with distinct characteristics. The first cluster represents younger premium users with relatively high usage intensity, the second cluster represents student users with the highest churn proportion, and the third cluster represents free users with high ad exposure but the lowest churn proportion. These findings indicate that the K-Prototypes method is effective in grouping Spotify users and provides useful information for understanding user behavior and churn tendencies.
Random Forest Algorithm Implementation for Air Quality Classification in DKI Jakarta Based on ISPU Khairanisa Salsabila; Tessy Octavia Mukhti
UNP Journal of Statistics and Data Science Vol. 4 No. 2 (2026): 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/vol4-iss2/474

Abstract

Air quality is an essential factor that has a direct impact on human health. High concentrations of air pollutants have the potential to cause various health impacts, across short-term and long-term horizons. This study aims to classify air quality in DKI Jakarta using the Air Pollution Standard Index (ISPU) data via the random forest algorithm. The dataset covers a timeframe from 2021 to 2025 and includes air pollutant parameters, namely PM10 and PM2.5 particulate matter, carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), dan ozone (O3). The research method employs a supervised learning approach, in which the data are stratified and evakuated through the implementation of K-Fold Cross Validation (k = 10) to ensure objective and stable model performance. Model performance was measured using Accuracy, Precision, Recall, and F1-Score metrics, along with Confusion Matrix and Feature Importance analyses. It can be seen from the results that the Random Forest model can classify air quality categories with excellent performance, reaching 100% Accuracy on training data and 98.44% on testing data. The Confusion Matrix analysis indicates that most data in each air quality are correctly classified. Furthermore, the Feature Importance analysis reveals PM2.5 that is most influential parameter in determining air quality categories. Therefore, this study indicates that the Random Forest algorithm proves effective for air quality classificati and can function as a decision-support tool for air pollution control and management in DKI Jakarta.
Co-Authors Adinda Putri Adrianingsih, Narita Y. Afifah Nabilah Aisyah Novriani Andini Diva Luthfiyah anice kartika Annisa Ramadhani Azizah Apriyerni Berliana Nofriadi Bimbim Oktaviandi Bunga Miftahul Barokah Bunga Nafandra Devni Prima Sari Dhio Ervandi Dicha Putri Yeni Dina Fitria Dina Fitria, Dina Dinda Putri Adilla Dodi Vionanda Dodi Vionanda Dony Permana Ervi Dayana Putri Fadhilah Fitri Fadhilah Fitri Fajri Juli Rahman Nur Zendrato Fathina Nafisa Fauzan Al Hamdani Siregar Fauzan Al-Hamdani Siregar Fauzan Arrahman Fauzan Gustiandra Fenni Kurnia Mutiya Figo Rahmatullah Fitri Hayati Fitri Fitri, Fadhilah Herlena Purnama Sari Khairani, Putri Rahmatun Khairanisa Salsabila Luthfiyah, Andini Diva Muhammad Arief Rivano Nikma Hasanah Nonong Amalita Nurul Mulya Nurul Mulya Syahwa Olga Afrilly Putri Olivin Adelia Huqmi Padafani, Lekison Permana, Dony Putri fajriyanti nur Rahmadani Rahmat Kurniawan Rahmatul Annisa Rahmika Alya Reihan Dani Eka Saputra Rizki Akbar Rudi Anggara Salma, Admi Sari Agustin Sari, Nilam N. Sari, Widia Kemala Sepniza Nasywa Septrina Kiki Arisandi Septrina Kiki Arisandi Siti Nurhaliza Sonia Ardhi Sri Wahyuni Suci Rahmadani Suliswati, Yeni Syafriandi Syafriandi Syafriandi Syafriandi Syifa Miftahurrahmi Taslim, Fauziah Vinna Sulvia Wafiq Alya Aufa Yenni Kurniawati Yoli Marda Novi Yonggi Septa Pramadia Yonggi Yusra, Zulmi Yusra Zamahsary Martha Zilrahmi, Zilrahmi Zulfadly Harman Harahap