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All Journal Jurnal Ilmu Pertanian Indonesia Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Telematika Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Indonesia Symposium on Computing Indonesian Journal on Computing (Indo-JC) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Komputer Terapan Indonesian Journal of Artificial Intelligence and Data Mining Prosiding Working Papers Series In Management Journal of Computer Science and Informatics Engineering (J-Cosine) The Asia Pacific Journal Of Management Studies TECHNO-SOCIO EKONOMIKA BERNAS: Jurnal Pengabdian Kepada Masyarakat Jurnal Abdimas Sang Buana MATHunesa: Jurnal Ilmiah Matematika Jurnal Kesehatan komunitas Indonesia eProceedings of Engineering
Siti Saadah
Telkom University
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Neuroscience Nursing Public Health Social Sciences Veterinary Other

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Deteksi Risiko Kredit dalam Peer-to-Peer Lending Menggunakan CatBoost Fadhlurrahman Akbar Nasution; Siti Saadah; Prasti Eko Yunanto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 5 (2023): October 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i5.5139

Abstract

P2P lending (Peer-to-peer lending) is widely used by private borrowers, small businesses, and MSMEs because P2P lending allows individuals and businesses to be able to lend money directly from lenders without the stringent requirements and criteria of traditional banks and financial institutions. However, P2P lending has a credit risk problem characterized by a high failure rate for borrowers to repay their loans. Therefore, a system was necessary to detect credit risk to minimize the risk of P2P lending. In this study, a system had been built using the CatBoost method; the dataset used was taken from the Bondora loan dataset. To measure the performance of the CatBoost algorithm, an evaluation matrix was performed using ROC (Receiver Operating Characteristics) curves and AUC (Area Under Curve) was performed. The experiment consists of three scenarios, of which the best result regards Scenario 2 with a data splitting of 90:10. It was caused by the result of AUC value 0.80329 compared to scenario 1 with a data split of 80:20 with the AUC value around 0.789583, and scenario 3 with a data split of 70:30 with the AUC value around 0.781066, respectively.
Peningkatan Pemahaman Masyarakat Terhadap Nilai Cagar Budaya Berbasis Wisata Tematik Google Maps di Purwakarta Ratri Wulandari; Vika Haristianti; Idhar Resmadi; Djoko Murdowo; Annisa Aditsania; Aida Andrianawati; Rendy Pandita B; Wibisono Tegar GP; Aniq Atiqi R; Siti Saadah
BERNAS: Jurnal Pengabdian Kepada Masyarakat Vol. 4 No. 1 (2023)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/jb.v4i1.4018

Abstract

Pada era Hindia Belanda, Kabupaten Purwakarta adalah ibukota Karesidenan Karawang, sehingga di Kabupaten Purwakarta terdapat kawasan pusat kota dengan alun-alun dan kelengkapan infrastruktur lainnya. Kelebihan ini belum disadari sebagai potensi oleh pemerintah daerah maupun masyarakat. Padahal, pemahaman terhadap potensi cagar budaya akan mendorong peningkatan Indeks Pembangunan Kebudayaan (IPK) daerah. Dari permasalahan tersebut, kegiatan pengabdian masyarakat ini menawarkan dua solusi yaitu, memberikan ilmu dan metode untuk peningkatan pemahaman masyarakat terhadap potensi cagar budaya daerah dan pengembangan peta wisata tematik berbasis Google Maps. Di dalamnya terdapat kegiatan terkait inventarisasi dan dokumentasi bangunan cagar budaya, termasuk pengetahuan teknologi untuk membangun media literasi cagar budaya. Metode yang digunakan melalui survey lapangan dan wawancara, penyusunan proposal, dan pencarian alternative solusi. Pada pelaksanaan kegiatan, metode yang digunakan adalah transfer pengetahuan melalui kegiatan workshop Adapun luaran kegiatan berupa infografis, peta tematik cagar budaya, dan website. Serta transfer pengetahuan dan metode kepada staf DISPORAPARBUD, dan masyarakat pecinta warisan budaya di bawah binaan DISPORAPARBUD Kabupaten.
Effect of Macroprudential Loan to Value (LTV) Policy using the Support Vector Regression (SVR) Approach Saadah, Siti; Purnomo, Muhammad Ridaffa
Telematika Vol 15, No 2: August (2022)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v15i2.1882

Abstract

Macroprudential policy has a goal to confine the risk and price from crises systemic, especially in managing financial stability amidst the COVID-19 pandemic. One of its instruments is Loan to Value (LTV). Ratio of LTV is a ratio between value of credit or cost that can gave from Bank Conventional or Syariah towards collateral value as property. This study aims in getting to know about its influence on citizen to take Kredit Kepemilikan Rumah (KPR). Based on the data from Central Bank Indonesia (BI) would be found about the increasing ratio of LTV yoy. The data set in this study derived from five bank with the data range being from 2014 to 2020. According to the characteristic data that will be used, thus one of the algorithm machine learning that is Support Vector Regression (SVR) was chosen as an approach to observe this trend. By using this method, the result indicated which bank that had been influenced by LTV ratio. Category of the bank who got impact are the bank that had the reverse influence between credit value of home ownership, they are Foreign Bank, Mixed Bank, Bank Persero, Bank Swasta, and Bank Perkreditan Rakyat.
Kmeans-SMOTE Integration for Handling Imbalance Data in Classifying Financial Distress Companies using SVM and Naïve Bayes Maulana, Didit Johar; Siti Saadah; Prasti Eko Yunanto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 1 (2024): February 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i1.5140

Abstract

Imbalanced data presents significant challenges in machine learning, leading to biased classification outcomes that favor the majority class. This issue is especially pronounced in the classification of financial distress, where data imbalance is common due to the scarcity of such instances in real-world datasets. This study aims to mitigate data imbalance in financial distress companies using the Kmeans-SMOTE method by combining Kmeans clustering and the synthetic minority oversampling technique (SMOTE). Various classification approaches, including Nave Bayes and support vector machine (SVM), are implemented on a Kaggle financial distress data set to evaluate the effectiveness of Kmeans-SMOTE. Experimental results show that SVM outperforms Nave Bayes with impressive accuracy (99.1%), f1-score (99.1%), area under precision recall (AUPRC) (99.1%), and geometric mean (Gmean) (98.1%). On the basis of these results, Kmeans-SMOTE can balance the data effectively, leading to a quite significant improvement in performance.
ANALISA PENGGUNAAN CONTENT VIDEO DAN LIVE STREAMING TIKTOK DALAM MEMPENGARUHI MINAT BELI GEN Z Siti Saadah; Zakiyya Tunnufus; Maesaroh; Mukti, Muhi
The Asia Pacific Journal Of Management Studies Vol 12 No 1 (2025)
Publisher : Universitas La Tansa Mashiro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55171/apjms.v12i1.1392

Abstract

The number of people interested in the TikTok application is increasing, and the majority of its users are Generation Z. This can be utilized by business owners to market their products. Thus, business owners must be more creative in increasing Gen Z's purchasing interest so that they are interested in the video and live streaming content used. This study aims to analyze the use of TikTok video and livestreaming content in influencing Gen Z's purchasing interest. The data used in this research is primary data obtained from the results of distributing questionnaires to 50 respondents. This study used a quantitative method with a purposive sampling technique. Data analysis used multiple linear regression analysis assisted by SPSS Software Version 20. In this study, several problems were found related to service quality and price, both of which have the potential to increase customer satisfaction. The results partially video content variable has no effect on purchase intention variable. The live streaming variable partially influences buying interest. Simultaneously having video content and live streaming results together influences buying interest of gen Z.
Co-Authors . andriyanto . Soeripto Abadi Abbsumarmanali Firyabi Sakhtiyani Ade Romadhony Ananda Affan Fattahila Andrianawati, Aida Anggit Nourislam Aniq Atiqi R Aniq Atiqi Rohmawati Annisa Aditsania Aulia Andi Mustika Dadah Jubaedah Dety Mulyanti Didin Saepudin Didit Adytia Djoko Murdowo E Handayani Ecky Prasetyo Nugroho Fadhlurrahman Akbar Nasution Fakhira Zahra Z Farah Afianti Fendi Irfan Amorokhman Gia Septiana Wulandari Haifa Salsabila Hasna Haifa Z Hendy Irawan I NYM Yoga Saputra Idhar Resmadi Jondri Jondri Kaenova Mahendra Auditama Larasati Larasati Maesaroh Mario Adventino Hamboerh Maulana, Didit Johar Muhammad Muttabi Hudaya Mukti, Muhi Neni Neni Prasti Eko Yunanto Purnomo, Muhammad Ridaffa Rahminiwati, Min Ratri Wulandari Redy Indrawan Rendy Pandita B Risyad Faisal Hadi Sri Maywati Tunnufus, Zakiyya Unang P. Vika Haristianti Vip Paramarta Wibisono Tegar GP