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All Journal E-Dimas: Jurnal Pengabdian kepada Masyarakat Jurnal SOLMA BAREKENG: Jurnal Ilmu Matematika dan Terapan J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Journal of Dedicators Community JURIKOM (Jurnal Riset Komputer) Variance : Journal of Statistics and Its Applications Vygotsky: Jurnal Pendidikan Matematika dan Matematika EDUTEC : Journal of Education And Technology jurnal ilmiah hospitality Discovery : Jurnal Ilmu Pengetahuan Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Jurnal Statistika dan Aplikasinya Journal of Mathematics Education and Science Mafaza : Jurnal Pengabdian Masyarakat Digital Transformation Technology (Digitech) Jurnal Statistika dan Komputasi (STATKOM) AL-UMRON: Jurnal Pengabdian kepada Masyarakat Jurnal Informatika Polinema (JIP)

Kartini, Alif Yuanita

Universitas Nadhatul Ulama Sunan Giri

Author-ID : 1207968

Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Regresi Data Panel Untuk Pemodelan Jumlah Penderita Tuberculosis di Kabupaten Bojonegoro Alif Yuanita Kartini; Nita Cahyani; Nilna Himawati
Jurnal Statistika dan Aplikasinya Vol 6 No 2 (2022): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.06212

Tuberculosis is a type of infectious disease that is contagious and causes death. In Bojonegoro district, the number of tuberculosis patients is quite high, reaching 3,401 patients in 2019. The DOTS strategy has been used, but it is not optimal in reducing the incidence of tuberculosis. Therefore, research is needed to determine the faktors that significantly cause the incidence of tuberculosis and predict the incidence of tuberculosis for some time to come. The incidence of tuberculosis is not only influenced by the faktors causing tuberculosis but is also influenced by a certain period of time. So that in this study the panel data regression method will be used to model the number of tuberculosis patients in Bojonegoro district in 2018-2020. The variables used are the number of tuberculosis sufferers (Y), the number of stunting cases (X1), the number of trained health workers (X2), the number of proper sanitation (X3), the number of PHBS households (X4), and the number of productive age population ( X5). Based on the analysis results show that the best estimation model is using the Fixed Effect Model (FEM) approach. The variables that significantly affect the number of tuberculosis sufferers in Bojonegoro district in 2018-2020 are the number of stunting cases (X1), the number of proper sanitation (X3) and the number of productive age population (X5) with a coefficient of determination of 71%.

Analisis Kepuasan Pengguna Jasa Petugas Parkir Dinas Perhubungan Bojonegoro Menggunakan Regresi Logistik Ordinal M Teguh Deddy Winarko; Alif Yuanita Kartini
Jurnal Statistika dan Komputasi Vol. 1 No. 1 (2022): Jurnal Statistika dan Komputasi
Publisher : Universitas Nahdlatul Ulama Sunan Giri

Latar Belakang: Tidak semua petugas parkir Dinas Perhubungan Kabupaten Bojonegoro melaksanakan kerjanya baik dan sesuai dengan standard operational procedure (SOP). Bentuk pembekalan dan sosialisasi oleh dinas terkait sudah diberikan, namun pengguna layanan jasa parkir merasa kurang puas. Untuk menganalisis masalah ini, diterapkan pemodelan regresi logistik ordinal untuk menilai kepuasan pelanggan. Tujuan: Mengetahui tingkat kepuasan dan faktor-faktor yang secara signifikan berpengaruh terhadap tingkat kepuasan pengguna jasa petugas parkir Dinas Perhubungan Kabupaten Bojonegoro. Metode: Metode Penelitian yang digunakan adalah metode kuantitatif berupa analisis regresi logistik ordinal. Digunakan accidental sampling dengan mengambil sampel dari responden yang kebetulan memakai jasa parkir petugas Dinas Perhubungan Kabupaten Bojonegoro. Variabel dependen adalah tingkat kepuasan pengguna jasa petugas parkir yang berskala ordinal dan variabel-variabel independen meliputi tangibles, reliability, responsiveness, emphaty dan assurance. Hasil: Kepuasan pengguna terhadap pelayanan petugas parkir terbesar adalah 35% cukup puas dan terbesar kedua 29% kurang puas. Dari hasil odds ratio, semakin besar tangibles, responsiveness, dan emphaty petugas parkir masing-masing memiliki peluang 2,0719; 5,9793; dan 9,0802 kali lebih besar daripada variabel lainnya terhadap tingkat kepuasaan pengguna petugas parkir. Kesimpulan: Mayoritas pengguna pelayanan petugas parkir kurang puas dan cukup puas. Penerapan regresi logistik ordinal memberikan pengetahuan bahwa tangibles, responsiveness, dan emphaty petugas parkir mempengaruhi kepuasan pengguna.

Penerapan Metode Regresi Linier Berganda Pada Kasus Balita Gizi Buruk Di Kabupaten Bojonegoro Miftahul Janah; Alif Yuanita Kartini
Jurnal Statistika dan Komputasi Vol. 1 No. 2 (2022): Jurnal Statistika dan Komputasi
Publisher : Universitas Nahdlatul Ulama Sunan Giri

Latar Belakang: Balita merupakan kelompok paling rentan terhadap masalah gizi apabila ditinjau dari sudut masalah kesehatan dan gizi, dimana balita mengalami siklus pertumbuhan dan perkembangan yang relatif pesat. Salah satu metode untuk menentukan faktor-faktor yang signifikan berpengaruh terhadap terjadinya kasus gizi buruk adalah metode Regresi Linear Berganda. Tujuan: Mendapatkan statistik deskriptif untuk kasus balita gizi buruk beserta variabel prediktornya di kabupaten Bojonegoro tahun 2020, dan mengetahui variabel apa saja yang dianggap signifikan mempengaruhi terjadinya kasus gizi buruk di kabupaten Bojonegoro menggunakan metode Regresi Linier Berganda. Metode: Diberikan metode kuantitatif dengan statistik deskriptif, pen gujian asumsi klasik, dan pengujian parameter Regresi Linear Berganda untuk Persentase Kejadian Balita yang mengalami gizi buruk di kabupaten Bojonegoro. Hasil: Karakteristik kejadian balita gizi buruk di kabupaten Bojonegoro untuk persentase kejadian balita gizi buruk per kecamatan terrendah sebesar 1,03% dan tertinggi 7,22%. Diperoleh variable-variabel yang signifikan memberikan pengaruh negative terhadap Persentase Kejadian Balita yang mengalami gizi buruk Per Kecamatan, yaitu Persentase Balita Ditimbang Empat Kali atau Lebih dalam Enam Bulan Terakhir sebesar -2,117, dan Persentase Balita Kurus Mendapatkan Makanan Tambahan sebesar -0,438. Akurasi model regresi diperoleh R-Square sebesar 74,3%. Kesimpulan: Variabel yang berpengaruh signifikan terhadap kejadian balita yang mengalami gizi buruk adalah Persentase Balita Ditimbang Empat Kali atau Lebih dalam Enam Bulan Terakhir, dan Persentase Balita Kurus Mendapatkan Makanan Tambahan.

PELATIHAN PEMBUATAN SALEP LIDAH BUAYA SEBAGAI ALTERNATIF PENGHILANG BEKAS LUKA Alif Yuanita Kartini; Dinda Intan Pramesti; Puji Aning Nur Nadhifah; Bintari Anggi Dwi Sugiarti
Al-Umron : Jurnal Pengabdian Kepada Masyarakat Vol. 3 No. 1 (2022): AL-UMRON : Jurnal Pengabdian kepada Masyarakat
Publisher : LEMBAGA PENELITIAN DAN PENGABDIAN KEPADA MASYARAKAT (LPPM) UNIVERSITAS NAHDLATUL ULAMA SUNAN GIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36840/alumron.v3i1.576

The incidence of injuries in Indonesia is increasing from year to year. The wound will leave a scar and will fade over a long period of time. There are many kinds of drugs offered in the market to speed up the healing of scars, but they are sold at high prices. This makes it difficult for people with middle to lower social status to get it. Aloe vera is one of the plants that can increase the production of collagen in the body. Aloe vera is also easy to get. From this situation, there is a high market opportunity for wound healing drugs at affordable prices. Therefore, training is needed to make scar removal ointment with aloe vera as the basic ingredient. This activity aims to empower students, especially students from the Pharmacy Study Program to make an ointment with aloe vera as an alternative to scar removal. This activity begins with knowledge exploration, socialization and delivery of materials, practice of making ointments with aloe vera as basic ingredients, packaging, promotions and ends with an evaluation of activities. The end result of this activity is a scar-removing ointment with aloe vera-based ingredients, which is then called the salibu ointment.

Application of Agglomerative Hierarchical Clustering Method for Grouping Non-Cash Food Assistance Recipients in Ngambon Bojonegoro Alif Yuanita Kartini; Abdul Manaf Jamiluddin
J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 16 No 1 (2023): Jurnal Ilmiah Teori dan Aplikasi Statistika
Publisher : Faculty of Science and Technology, Univ. PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/jstat.vol16.no1.a6122

One of the sub-districts in Bojonegoro that received non-cash food assistance was Ngambon sub-district. The non-cash food assistance provided in Ngambon sub-district has not been on target. This is because underprivileged people do not get assistance, while people who can afford it actually get non-cash food assistance. So, research is needed with the aim that non-cash food assistance provided by the government can be distributed according to procedures. The method used in this study is agglomerative hieralchical clustering to group recipients of non-cash food assistance from the people of Ngambon Bojonegoro. The variables used were 12 indicators of non-cash food assistance set by the Bojonegoro district Social Office. The data used were 131 recipients of non-cash food assistance spread across five villages in Ngambion sub-district. Grouping results with the single linkage method are less relevant. Meanwhile, with the average linkage and complate linkage methods, five clusters were obtained, and with ward linkage, three clusters were obtained. Based on the elbow rule, it was found that ward linkage is the best grouping method, with cluster 1 totaling 57 people, cluster 2 totaling 53 people and cluster 3 totaling 21 people.

PENERAPAN MULTIVARIATE ADAPTIVE REGRESSION SPLINES UNTUK ANALISIS FAKTOR YANG MEMPENGARUHI KELAYAKAN NASABAH YANG MENGAJUKAN PEMBIAYAAN Alif Yuanita Kartini; Devy Wulandari
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 3 (2023): 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.v4i3.410

Not all customers who apply for financing will be accepted by the bank. This is to avoid risks that often occur in the financing process, namely bad financing. One way to avoid this risk is to find out the factors that affect the eligibility of customers who apply for financing using the MARS method. This research was conducted at BSI Bojonegoro branch office using data on customers who applied for financing from January to March 2023, namely 75 customers. The response variables used are binary with categories of customers who do not get financing and customers who get financing. While the predictor variables used are BI checking (X1), job background (X2), type of financing (X3), number of dependents (X4), working period (X5), income (X6), plafond (X7), margin (X8) and DSR (X9). Based on the analysis, it was found that the factors had a significant influence on the eligibility of customers applying for financing were DSR which contributed 100%, income 48%, employment background 45%, margin 42%, plafond 26% and BI checking 17%. Furthermore, the MARS model obtained is used to classify eligible and unfit customers with an accuracy rate of 92%. From this research, it is expected to minimize customers who are stuck in making payments and minimize financing risks at BSI Bojonegoro branch office

Algorima K-Means dalam Clustering Produk Skincare untuk Menentukan Strategi Pemasaran Barata, Mula; Ayuni, Intan Sri; Kartini, Alif Yuanita; Alawi, Zakki
Jurnal Informatika Polinema Vol. 10 No. 3 (2024): Vol. 10 No. 3 (2024)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v10i3.5167

Penelitian ini fokus pada pengembangan strategi pemasaran dalam industri kosmetik yang semakin kompetitif. Menggunakan pendekatan data mining dengan algoritma K-Means, penelitian ini bertujuan untuk mengidentifikasi produk-produk terlaris, sedang, dan rendah dalam penjualan. Metode ini memungkinkan pengelompokan produk berdasarkan pola penjualan, memfasilitasi pengambilan keputusan yang efektif dalam meningkatkan laba perusahaan. Dengan menganalisis data penjualan dan mengklasifikasikan produk ke dalam kluster yang sesuai, strategi pemasaran yang lebih cermat dapat dirancang. Hasil yang didapatkan dari perhitungan cluster dari 693 data penjualan skincare yaitu: 392 data termasuk penjualan rendah dan tergolong cluster 1, 13 data termasuk penjualan sedang dan tergolong cluster 2,288 data termasuk penjualan terlaris dan tergolong cluster 3. Hasil penelitian ini dapat memberikan wawasan berharga bagi perusahaan kosmetik dalam mengoptimalkan strategi pemasaran guna mencapai target penjualan dan mengurangi penumpukan stok. Dengan menerapkan Algoritma K-Means pada data penjualan produk kosmetik, perusahaan dapat mengidentifikasi produk yang memiliki kinerja penjualan tinggi, sedang, dan rendah. Langkah ini memungkinkan pengelompokan produk berdasarkan pola penjualan, memudahkan penentuan strategi pemasaran yang sesuai. Berdasarkan hasil cluster yang didapatkan maka ditentukan strategi pemasaran untuk tindak lanjut semua produk mulai dari produk terlaris, fokus pemasaran dapat diperkuat untuk mempertahankan dan meningkatkan penjualan. Untuk produk penjualan sedang, strategi dapat diarahkan untuk meningkatkan popularitas dan meningkatkan penjualan. Sedangkan untuk produk penjualan rendah, perlu dilakukan analisis lebih lanjut untuk mengidentifikasi penyebab rendahnya penjualan dan mengambil tindakan korektif, seperti penyempurnaan produk atau strategi pemasaran yang lebih efektif.

PELATIHAN DAN PENDAMPINGAN PELATIHAN DAN PENDAMPINGAN PENULISAN KARYA TULISAN ILMIAH BAGI GURU SMK NEGERI PURWOSARI BOJONEGORO: PELATIHAN DAN PENDAMPINGAN PENULISAN KARYA TULISAN ILMIAH BAGI GURU SMK NEGERI PURWOSARI BOJONEGORO Mahmudah, Nur; Kartini, Alif Yuanita
Al-Umron : Jurnal Pengabdian Kepada Masyarakat Vol. 5 No. 2 (2024): AL-UMRON : Jurnal Pengabdian kepada Masyarakat
Publisher : LEMBAGA PENELITIAN DAN PENGABDIAN KEPADA MASYARAKAT (LPPM) UNIVERSITAS NAHDLATUL ULAMA SUNAN GIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/alumron.v5i2.3407

A scientific paper is a written report containing a presentation of the results of research that has been carried out by a team in accordance with scientific rules and ethics. The ability to write scientific papers for teachers is a professional requirement in career development in teaching and learning. Teachers are required to fulfill the requirements for writing scientific papers in order to be promoted, but this becomes an obstacle due to their low ability and being asked to write in the teacher's environment. Writing scientific papers is an activity related to knowledge and skills in teaching and learning so it is necessary to provide comprehensive, effective and productive training and assistance in writing scientific papers for State Vocational School Teachers in Purwosari. This activity aims to increase the development of teachers' interest in writing in various fields of study. Based on Community Service activities held on 12-13 July 2023 which were attended by 19 teachers consisting of 12 female teachers and 7 male teachers. The results of the PKM activities for Vocational School Teachers in Purwosari can increase knowledge, insight and skills in writing scientific papers and can publish articles independently to meet the professional demands of teaching and learning activities. This activity uses participatory and discussion methods in exploring the writing of scientific papers through training and mentoring in this activity

Implementasi Machine Learning Model sebagai Sistem Prediksi Penyakit Breast Cancer Cahyani, Nita; Irsyada, Rahmat; Kartini, Alif Yuanita
Digital Transformation Technology Vol. 4 No. 2 (2024): Periode September 2024
Publisher : Information Technology and Science(ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/digitech.v4i2.5209

Breast Cancer atau Kanker payudara adalah penyakit yang paling umum ditemukan pada wanita di seluruh dunia. Setiap perkembangan untuk prediksi dan diagnosis penyakit kanker merupakan modal penting untuk hidup sehat. Sehingga, akurasi tinggi dalam prediksi kanker penting untuk memperbarui aspek pengobatan dan standar kelangsungan hidup pasien. Teknik Machine Learning (ML) merupakan aplikasi dari Artificial Intelligence (AI) yang dapat memberikan kontribusi besar pada proses prediksi dan diagnosis dini kanker payudara, dan telah terbukti sebagai teknik yang kuat. Dalam penelitian ini, diterapkan algoritma Machine Learning yaitu metode single: Support Vector Machine (SVM), Random Forest, Logistic Regression, dan K-Nearest Neighbors (KNN) dan metode ensemble yaitu SMOTE-Boosting dan SMOTE-Bagging pada dataset Breast Cancer di Bojonegoro. Tujuan dari penelitian ini Mendaptakan ketepatan klasifikasi atau prediksi breast cancer khususnya studi kasus di Bojonegoro dengan tingkat kinerja yang lebih baik. Nilai akurasi yang terbaik pada metode single yaitu model Random Forest (RF) sebesar 95,65% untuk data testing, 100% untuk data training sedangkan untuk metode ensembel SMOTE-Boosting Random Forest (RF) sebesar 100% untuk data testing, 100% untuk data training dan SMOTE-Bagging RF sebesar 97% untuk data training dan 100% untuk data testing. Sehingga SMOTE-Boosting RF dapat dijadikan analisis prediksi yang terbaik dalam penelitian ini. Hasil ini dapat digunakan di masa depan untuk memprediksi penyakit lainnya.

IMPLEMENTATION OF MIXED GEOGRAPHICALLY WEIGHTED REGRESSION MODEL TO ANALYZE SOCIAL ASSISTANCE BUDGET IN EAST JAVA Utami, Putri; Nurdiansyah, Denny; Kartini, Alif Yuanita
Jurnal Statistika dan Aplikasinya Vol. 8 No. 2 (2024): Jurnal Statistika dan Aplikasinya
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.08204

Background - Social assistance (BANSOS) is aid provided by the government to low-income communities in the form of money, goods, or services. Understanding the allocation and influencing factors of social assistance in East Java is crucial for effective distribution. Mixed Geographically Weighted Regression (MGWR) combines global and local regression models to address spatial variability in the data. Purpose – This study aims to develop an MGWR model with a fixed kernel weighting function for the social assistance budget in East Java for 2022. The specific objectives are to identify factors affecting the budget and determine the best model that represents these global and local relationships. Methodology – The study employs the Mixed Geographically Weighted Regression (MGWR) method with a fixed Gaussian kernel to analyze social assistance budget data and economic factors in East Java for 2022. Models OLS, GWR, and MGWR are applied and evaluated using the Akaike Information Criterion (AIC) to identify the best-performing model. Findings – The MGWR model with a fixed Gaussian kernel is the best for the social assistance budget in East Java, yielding a lower AIC compared to OLS and GWR models. The globally influential factor in this model is economic growth (

Co-Authors Abdul Manaf Jamiluddin Afiana, Ifa Ahmad Tauchid Ali Hamdan Arifat, Muhammad Ayuni, Intan Sri Barata, Mula Bintari Anggi Dwi Sugiarti Deby Fakhriyana, Deby Denny Nurdiansyah Desinta, Yessi Farisa Devy Wulandari Dewi Niswatul Fithriyah Dinda Intan Pramesti Edi Setyanto Fidiya, Karisma Risma Firdaus, Saida Zahrotul Hamidatun Nihayah Huda, Tisa Dwi Julianti Ifa Afiana Irsyada, Rahmat Jauhar Vikri, Muhammad Jauhara Rana Budiani, Jauhara Rana Khoirina, Jami’atul Khoirul Wafa Laelatul Nur Ummah Lathifah, Nur Aisyatul M Teguh Deddy Winarko Miftahul Janah Miftahul Janah, Miftahul Moch Nur Faizin Mochamad Nizar Palefi Ma’ady Muhammad Ishlahuddin Nilna Himawati Ningtiyas, Putri Ayu Nita Cahyani Nur Mahmudah Priadana, Benny Widya Puji Aning Nur Nadhifah Putri Utami, Putri Saeful Anwar Sri Rahayu Sufiandi, Enrico Wafa, Khoirul Winarko, M Teguh Deddy Yogi Prana Izza Yuliana, Ummi Agustin Yunita Dwi Setyoningsih Yunita Dwi Setyoningsih Zakki Alawi

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