Article Per Year (5 Year)
p-Index From 2021 - 2026
1.879
P-Index
This Author published in this journals
All Journal Pythagoras: Jurnal Matematika dan Pendidikan Matematika Jurnal Sains dan Seni ITS IPTEK The Journal of Engineering Indonesian Journal of Applied Informatics Eksakta : Berkala Ilmiah Bidang MIPA Devotion: Journal of Research and Community Service Media Bina Ilmiah Sewagati Kesmas: Jurnal Kesehatan Masyarakat Nasional (National Public Health Journal)
Destri Susilaningrum
Departemen Statistika Bisnis, Fakultas Vokasi Institut Teknologi Sepuluh Nopember
Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences Other

Published : 25 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 25 Documents
Search

 1   2   3 
Pelatihan Aplikasi Dashboard RAB Desa sebagai Peningkatan Kapabilitas dalam Pengelolaan Keuangan Desa di Kecamatan Jetis Kabupaten Ponorogo Jawa Timur Hibatullah, Fausania; Susilaningrum, Destri; Ulama, Brodjol Sutijo Suprih; Habibi, Mochammad Reza; Kusrini, Dwi Endah; Dewi, Mukti Ratna
Sewagati Vol 8 No 2 (2024)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j26139960.v8i2.951

Abstract

Pentingnya Pengabdian kepada Masyarakat (PPM) dalam lingkup perguruan tinggi, termasuk di dalamnya dosen Departemen Statistika Bisnis Fakultas Vokasi ITS, termanifestasi dalam kolaborasi PPM tahun ini dengan Pemerintahan Kecamatan Jetis, Kabupaten Ponorogo, Jawa Timur. Kolaborasi ini bertujuan untuk meningkatkan efisiensi dalam Pengelolaan Monografi Pedesaan, khususnya dalam perhitungan Rancangan Anggaran Belanja Desa (RABDESes). Dalam penjajagan awal, Kecamatan Jetis mengidentifikasi kebutuhan mendesak akan program yang dapat mempermudah penghitungan RABDESes, yang selama ini dilakukan secara manual. Proses manual ini sering mengakibatkan kesalahan dalam perhitungan akhir RAB karena keterbatasan waktu untuk mengisi berbagai komponen pembelanjaan. Oleh karena itu, tim PPM dari Departemen Statistika Bisnis Fakultas Vokasi ITS, bersama dengan mahasiswa KKN, berkolaborasi untuk menciptakan Dashboard RABDESes menggunakan fasilitas yang disediakan oleh program Excel. Selain menciptakan alat ini, tim PPM juga memberikan pelatihan kepada staf kelurahan/desa yang terlibat langsung dalam urusan RABDESes. Tujuannya adalah memastikan pemahaman yang baik tentang penggunaan Dashboard tersebut, sehingga dapat mengurangi kesalahan dan meningkatkan efisiensi dalam proses pengelolaan RABDESes. Melalui inisiatif ini, PPM turut berperan dalam mendukung pembangunan dan pengelolaan keuangan di tingkat pedesaan.
Pelatihan Dashboard Monografi untuk Peningkatan Efisiensi Penyusunan RAB Tahunan Desa Bagi Staf Kelurahan di Kecamatan Wonosari, Wonoasri Kabupaten Madiun Santoso, Noviyanti; Suprih Ulama, Brodjol Sutijo; Kusrini, Dwi Endah; Susilaningrum, Destri; Dewi, Mukti Ratna; Hibatullah , Fausania; Habibi, Mochammad Reza; Nafis, Mochammad Abdillah
Sewagati Vol 9 No 4 (2025)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j26139960.v9i4.2477

Abstract

Penyusunan Rencana Anggaran Belanja (RAB) tahunan desa merupakan langkah krusial dalam pengelolaan keuangan yang transparan, akuntabel, dan efektif. Namun, proses ini seringkali menghadapi kendala berupa kurangnya efisiensi dalam pengumpulan dan analisis data monografi desa. Pelatihan Dashboard Monografi ini bertujuan untuk meningkatkan kapasitas staf kelurahan di Kecamatan Wonosari, Wonoasri, Kabupaten Madiun, dalam menyusun RAB tahunan secara lebih efisien dan akurat. Pelatihan yang dilaksanakan mencakup pengenalan aplikasi berbasis Excel yang dirancang khusus untuk penyusunan RAB infrastruktur desa, termasuk estimasi anggaran jalan paving. Metode kegiatan melibatkan ceramah, diskusi, praktik langsung, dan pendampingan untuk memastikan pemahaman peserta terhadap materi. Hasil evaluasi menunjukkan peningkatan signifikan dalam efisiensi dan akurasi penyusunan RAB desa. Pelatihan ini berhasil memberikan solusi digital berbasis data kepada staf kelurahan, sehingga mendukung proses perencanaan anggaran yang lebih efektif dan tepat sasaran. Keberhasilan kegiatan ini menunjukkan pentingnya pelatihan berkelanjutan, pendampingan teknis, dan evaluasi berkala untuk memastikan keberlanjutan manfaat dari aplikasi yang diimplementasikan.
The Analysis of Factors Affecting Stage Level of Breast Cancer Patients at RSUD DR. SOETOMO Surabaya Susilaningrum, Destri; Azizah, Nur; Salamah, Mutiah; Ratna D, Mukti
Devotion : Journal of Research and Community Service Vol. 3 No. 3 (2022): Devotion: Journal of Research and Community Service
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/dev.v3i3.102

Abstract

Breast cancer is the cancer with the largest number in the world, and ranks as the fifth largest cause of death, which is 6.9% of the total 9,958,133 million cases of cancer deaths. Breast cancer is one of the main killers of women in the world and in Indonesia. Breast and cervical cancer dominate cancer cases in East Java. Throughout 2019, RSUD Dr. Soetomo Surabaya received 167,000 cancer patients, and the highest case was breast cancer. The high number of breast cancer sufferers makes this disease requires special attention. The cancer staging or staging system is based on whether the cancer has spread from the breast to other parts of the body. Cancer stage is divided into two categories, namely early stage (stages 0 to III A) and late stage (stages III B to IV). This study will examine the factors that affect the level of cancer stage in breast cancer patients at RSUD Dr. Soetomo Surabaya in 2019. Using the binary logistic regression analysis method, it was found that the factors that significantly influence the stage of breast cancer are Grade and Obesity with a classification correctness level of 82.5%.
Mapping for Tracking Sexually Transmitted Infections by Subdistricts in Surabaya, Indonesia Susilaningrum, Destri; Ulama, Brodjol Sutijo Suprih; Hibatullah, Fausania; Anjani, Diandra Soja
Kesmas Vol. 19, No. 2
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The 2014 shutdown localization of prostitution in Surabaya City, East Java Province, Indonesia, has given rise to an illegal prostitution industry, resulting in the spread of uncontrolled sexually transmitted infections (STIs). Mapping needs to be done to track the spread of the disease. This study used secondary data on STIs in 2020 from the Surabaya City Health Office. By using biplot analysis, this study sought to offer a detailed understanding of the distribution and dynamics of STI cases in different parts of Surabaya. The early-stage syphilis was found in Tegalsari and Krembangan Subdistricts; then, gonorrheal urethritis was found in Tandes, Karang Pilang, and Pabean Cantian Subdistricts. Meanwhile, gonorrhea was typically found in Tandes, Gunung Anyar, Sawahan, and Karang Pilang Subdistricts. On the other hand, Tegalsari, Krembangan, and Pabean Cantian Subdistricts also had cases of advanced syphilis. This study enables relevant parties, specifically the Surabaya City Health Office, to monitor the method's rapid spread and respond to each case according to the predominant type of STI.
A Hybrid Model to Enhance The Performance of Classifier in Financial Distress Prediction Dewi, Mukti Ratna; Susilaningrum, Destri
IJAI (Indonesian Journal of Applied Informatics) Vol 9, No 1 (2024)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijai.v9i1.94725

Abstract

Accurately predicting financial distress is a critical issue in financial decision-making. Financial distress must be detected as early as possible as an important determining factor in decision-making for internal companies and financial institutions related to financing or loan decisions. Various studies on financial distress prediction in Indonesia have been carried out, ranging from traditional statistical approaches to machine learning. However, the performance of the two methods is still not optimal. Therefore, this study tries to develop machine learning techniques by combining cluster analysis and classification in a hybrid model to improve the prediction model’s performance. The case study adopted in this study is the prediction of financial distress in non-financial companies listed on the IDX from 2018-2021 by combining k-means clustering and Support Vector Machine. The analysis results show that the hybrid classifier has an accuracy value of 92.7%, which is higher than the accuracy of the single classifier, which is 88.6%.
Co-Authors Agustiani, Elly Albertus Eka Putra Haryanto Anjani, Diandra Soja Aridinanti Riza Ayu Alchusna Atiqa Rahmawati Binar Ulfadari Brodjol Sutijo Suprih Ulama Cindy Meilany Fitri Andriani Citra Elok Megahardiyani Daniar Kusumaning Ayu Dimas L.R. Dwi Endah Kusrini Emilda, Dwi Putri Fibrillian Z.L. Habibi, Mochammad Reza Hibatullah , Fausania Hibatullah, Fausania I Gusti Agung Komang Diafari Djuni Hartawan Indra Nur Fauzi Irma Harlianingtyas Maries Lailatul Izza Muhammad Sjahid Akbar Mukti Ratna Dewi Mutiah Salamah Nafis, Mochammad Abdillah Nita Cahyani Nur Azizah Nur Azizah Ratna D, Mukti Rika Susanti Riza Ayu Alchusna Santoso, Noviyanti Siti Maghfirotul Ulyah Suhartono Suhartono Suhartono Suhartono Suhartono Suhartono Suntoro Suntoro Suprih Ulama, Brodjol Sutijo Thania Muhammad Vidi Vianney C.M.Tanggo Vinny Merlinda Hardiana Windia Cinde Prameswari Yosiana Saputri