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All Journal TEKNIK INFORMATIKA Jurnal Simetris Prosiding SNATIF JURNAL MANAJEMEN (EDISI ELEKTRONIK) Shirkah: Journal of Economics and Business Simtek : Jurnal Sistem Informasi dan Teknik Komputer Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat TIN: TERAPAN INFORMATIKA NUSANTARA Infotech: Journal of Technology Information International Journal of Community Service Simpatik: Jurnal sistem Informasi dan Informatika Buletin Sistem Informasi dan Teknologi Islam Journal of Management and Digital Business Duta Abdimas: Jurnal Pengabdian Masyarakat Innovative: Journal Of Social Science Research SmartComp CSRID Jurnal Sosialita: Jurnal Kajian Sosial dan Pendidikan
Nurmalitasari Nurmalitasari
Prodi Magister Pendidikan Matematika Program Pascasarjana UNS
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Hybrid Logistic Super Newton Model for Predicting Small Sample Size Data Nurmalitasari, Nurmalitasari; Awang Long, Zalizah; Nurchim, Nurchim
JURNAL TEKNIK INFORMATIKA Vol. 18 No. 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v18i1.43929

Abstract

Logistic regression is a model commonly used for predicting data with large sample sizes. However, in real-world scenarios, many cases involve small datasets that need to be addressed using logistic regression. The aim of this research is to develop a hybrid logistic regression model to address issues with small sample sizes by combining the Newton Raphson and Super Cubic methods. This hybrid model is applied to predict student dropout at Universitas Duta Bangsa Surakarta. The performance of the hybrid model is evaluated using two main metrics: the convergence of the parameter approximation to measure the precision of parameter estimation, and the ROC curve to assess prediction accuracy. Experimental results show that the Hybrid Logistic Super Newton model outperforms the logistic regression Newton Raphson model, requiring only three iterations to converge, thus improving computational efficiency. Moreover, this model achieves higher accuracy, with an AUC of 0.8833. These findings suggest that the developed model has the potential to be applied in various fields, such as healthcare, finance, and others, offering an effective solution for accurate, real-time predictive analytics. Further research could focus on optimizing the model’s computational efficiency and exploring its application in other domains with small dataset challenges, such as healthcare and finance.
PERUBAHAN SOSIAL SEDULUR SIKEP DI DUKUH KARANGPACE DESA KLOPODUWUR KECAMATAN BANJAREJO KABUPATEN BLORA PADA ERA MODERN NURMALITASARI, NURMALITASARI
Jurnal Sosialita Vol. 16 No. 2 (2021): JURNAL SOSIALITA
Publisher : Program Magister Pendidikan IPS UPY

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Abstract

Penelitian ini bertujuan untuk mengetahui : 1) sejarah munculnya Sedulur Sikep di dukuh Karangpace; 2) Perubahan sosial Sedulur Sikep di dukuh Karangpace pada era modern; 3) Nilai-nilai kearifan lokal Sedulur Sikep untuk dijadikan literasi dalam pengembangan pembelajaran IPS di sekolah.Penelitian ini merupakan penelitian kualitatif. Subyek dalam penelitian ini adalah Sedulur Sikep yang tingal di dukuh Karangpace. Pengumpulan data dilakukan dengan wawancara, observasi, dan dokumen. Hasil penelitian ini menunjukkan: 1) Sedulur Sikep lahir dari sejarah seorang tokoh yaitu Samin Surosentiko yang mampu mengerakan massa untuk melawan kolonialisme Belanda. Dari gerakan ini masyarakat pengikut Samin semakin banyak dan meluas hingga ke berbagai daerah termasuk ke Jawa Timur. Masyarakat ini kemudian menyebut dirinya Sedulur Sikep. Artinya: Sikap menikah/ berumah tangga.2) terdapat perubahan sosial yang terjadi mencakup beberapa bidang yakni: Ilmu pengetahuan dan pendidikan, teknologi dan transportasi, agama dan kepercayaan, tradisi dan adat istiadat, dan moral ekonomi. 3) Nilai-nilai kearifan lokal dapat dijadikan salah satu literasi dalam pengembangan pembelajaran IPS di sekolah.Kata Kunci : Perubahan sosial, Sedulur Sikep, kearifan lokal, modernisasi.This study aims to find out: 1) the history of the emergence of Sedulur Sikep in the Karangpace hamlet; 2) Sedulur Sikep social change in the Karangpace hamlet in the modern era; 3) Sedulur Sikep local wisdom values in the Karangpace hamlet to be used as literacy in the development of social studies in schools. This research is a qualitative research. The subjects in this study were Sedulur Sikep who lived in the Karangpace hamlet. The data collections were carried out by interviews, observation and document. The results of this study indicate: 1) Sedulur Sikep was born from history of a figure namely Samin Surosentiko who was able to mobilize the masses to fight the Dutch colonialism. From this movement the followers of Samin became more numerous and extended to various regions including East Java. This community then call themself as Sedulur Sikep or Sikep Rabi. Meaning: The attitude of marriag, 2) There were social changes that occur in Sedulur Sikep which cover several fields, namely: Science and education, technology and transportation, religion and beliefs, traditions and customs, and economic morals. 3) The values of local wisdom can be used as literacy in the development of social studies learning in schools.Keywords: Social change, Sedulur Sikep, local wisdom, modernization.
Prediksi Churn Pelanggan Multinational Bank Menggunakan Algoritma Machine Learning Hidayat, Rifki; Syawaludin, M Ainur; Nurmalitasari, Nurmalitasari
Simpatik: Jurnal Sistem Informasi dan Informatika Vol. 4 No. 2 (2024): Desember 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/simpatik.v4i2.4595

Abstract

Dalam menghadapi persaingan pasar yang ketat, prediksi churn pelanggan menjadi penting bagi perusahaan perbankan untuk mempertahankan loyalitas pelanggan. Penelitian ini mengaplikasikan algoritma machine learning meliputi Naive Bayes, Decision Tree, dan Random Forest untuk prediksi churn pelanggan pada ABC Multinational Bank. Data yang digunakan adalah dataset publik yang diambil dari Kaggle yang mencakup informasi 10.000 nasabah bank. Proses penelitian melibatkan beberapa tahapan yaitu pengumpulan data, preprocessing, pemodelan, prediksi, dan evaluasi. Hasil evaluasi memperlihatkan bahwa model Random Forest memberikan performa terbaik dengan akurasi 85% dan AUC 0.83. Naive Bayes dan Decision Tree masing-masing memiliki akurasi 82% dan 77%. Kesimpulan menunjukkan bahwa Random Forest lebih unggul dalam memprediksi churn pelanggan dibandingkan dua algoritma lainnya, sehingga dapat digunakan untuk strategi pemasaran yang lebih efektif dalam industri perbankan.
From Zero Sales to Survival: Forecast-triggered Decision-making in Ecotourism MSMEs Purnomo, Singgih; Nurmalitasari, Nurmalitasari; Nurchim, Nurchim; Nugroho, Novemy Triyandari
Shirkah: Journal of Economics and Business Vol. 11 No. 1 (2026)
Publisher : Universitas Islam Negeri Raden Mas Said Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22515/shirkah.v11i1.1108

Abstract

Ecotourism micro, small, and medium-sized enterprises (MSMEs) often face highly volatile demand characterized by frequent zero-sales days, strong seasonality, and exposure to external shocks. In such conditions, sustainability depends less on forecast accuracy and more on timely, low-cost operational decisions. This study examines how forecast-triggered decision-making supports short-run viability under intermittent, zero-heavy demand. Using manually recorded daily sales data from ecotourism MSMEs in Tawangmangu, Indonesia, a two-stage approach is applied that separates sale occurrence from sales magnitude. First, a logistic model estimates the probability of a sale to generate early-warning signals. Second, conditional sales magnitude is predicted to indicate readiness levels rather than precise revenue targets. Instead of focusing on accuracy alone, the analysis evaluates decision usefulness through time-ordered backtesting, emphasizing avoidable operating days and early-warning lead time. The results show that sale-occurrence signals effectively guide daily operating decisions, while magnitude forecasts support proportional readiness. The framework identifies a substantial share of avoidable operating days and provides several days of advance warning before prolonged zero-sales periods. This enables earlier cost control and capacity adjustment. The study contributes by offering a practical, human-in-the-loop decision framework that links demand uncertainty with adaptive actions using simple, manually recorded data.
Co-Authors Adenta Sari, Nur Avia Al Mustofa, Muhammad Hafizh Alliya, Sania Qorrii Atina, Vihi Awang Long, Zalizah Dwi Hartanti Eko Purwanto Hasanah, Herliyani Imam Sujadi JOKO SUSANTO Miftakhul Jannah, Ulfarida Novemy Triyandari Nugroho Nugroho Arif Sudibyo Nugroho, Mohammad Yusuf Nurchim Nurchim Permatasari, Hanifah Pipin Widyaningsih Rifki Hidayat Sajad, Abdullah Sari, Nur Avia Adenta Setiawati, Neha Poetri Singgih Purnomo Syawaludin, M Ainur Taufik Hidayat Tri Atmojo Kusmayadi Tri Wulandari, Rahmawati Desi Utami, Maulinda Devi