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All Journal International Journal of Evaluation and Research in Education (IJERE) ComEngApp : Computer Engineering and Applications Journal Indonesian Journal of Electronics and Instrumentation Systems IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Ilmu Komputer dan Informasi Jurnal Ilmiah Informatika Komputer Jurnal Simetris Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) Intiqad: Jurnal Agama dan Pendidikan Islam Telematika : Jurnal Informatika dan Teknologi Informasi Scientific Journal of Informatics CESS (Journal of Computer Engineering, System and Science) Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Jurnal Fourier InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Proceeding of the Electrical Engineering Computer Science and Informatics JPSE (Journal of Physical Science and Engineering) Jurnal Teknologi dan Sistem Komputer Journal of Information Technology and Computer Science Jurnal Informatika INTEGER: Journal of Information Technology Jurnal Matematika: MANTIK JURNAL MEDIA INFORMATIKA BUDIDARMA Desimal: Jurnal Matematika JTERA (Jurnal Teknologi Rekayasa) BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING Unisda Journal of Mathematics and Computer Science (UJMC) JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Informatika Universitas Pamulang JUMANJI (Jurnal Masyarakat Informatika Unjani) Jurnal Telematika Mathvision : Jurnal Matematika Building of Informatics, Technology and Science Transformasi : Jurnal Pendidikan Matematika dan Matematika Jurnal Mnemonic Majalah Ilmiah Matematika dan Statistika (MIMS) Dinamika Informatika: Jurnal Ilmiah Teknologi Informasi JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Sains dan Teknologi INTERNATIONAL JOURNAL OF MECHANICAL COMPUTATIONAL AND MANUFACTURING RESEARCH Papanda Journal of Mathematics and Sciences Research Sains Data Jurnal Studi Matematika dan Teknologi Journal Serambi Engineering (JSE)
Sari, Dian Candra Rini Novita
Universitas Islam Negeri Sunan Ampel Surabaya
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Application of Support Vector Regression (SVR) for Revenue Prediction Based on Total Transactions and Total Waste Volume Maliki, Naufal Ridho; Khaulasari, Hani; Novitasari, Dian Candra Rini; Pramono, Wahyu Joko
Desimal Vol. 9 No. 1 (2026): Desimal
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v9i1.29190

Abstract

Reliable revenue forecasting is critical for ensuring the financial sustainability of urban sanitation infrastructure, particularly in publicly managed fecal sludge treatment systems where demand fluctuates and operational planning depends on daily service variability. However, revenue patterns in such systems are typically nonlinear, volatile, and influenced by interrelated operational factors, limiting the effectiveness of conventional linear forecasting approaches. This study develops a data-driven predictive framework using Support Vector Regression (SVR) to model daily retribution revenue at the Keputih Fecal Sludge Treatment Plant (IPLT Keputih), Surabaya. The dataset comprises 1,213 daily observations from January 2022 to April 2025, incorporating total transactions and total sludge volume as predictor variables and total revenue as the response variable. Three kernel configurations—Linear, Polynomial, and Radial Basis Function (RBF)—were systematically evaluated following Min–Max normalization and chronological training–testing separation. Model performance was assessed using Mean Absolute Percentage Error (MAPE). The results demonstrate that the SVR model with the RBF kernel achieved the highest predictive accuracy, yielding a MAPE of 17.17%, outperforming the Linear and Polynomial kernels in capturing nonlinear revenue dynamics. Forecast projections further reveal cyclical seasonal tendencies with direct implications for operational scheduling and short-term budget allocation. By integrating machine learning–based forecasting into public sanitation revenue modeling, this study contributes to advancing data-driven financial planning strategies for sustainable urban service management.
Analisis Sentimen Pengguna Aplikasi X Terhadap Pelaksanaan Makan Bergizi Gratis Menggunakan Metode Adaptive Neuro-Fuzzy Inference System Mergianti, Wahyu Ningtiyas; Khudin, Nasroh; Afandi, Achsan; Shofah, Novia Adibatus; Novitasari, Dian Candra Rini
Sains Data Jurnal Studi Matematika dan Teknologi Vol 4, No 1: January - June 2026
Publisher : Sekolah Tinggi Agama Islam Nurul Islam Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52620/sainsdata.v4i1.339

Abstract

Program Makan Bergizi Gratis (MBG) menimbulkan beragam sentimen positif dan negatif di media sosial yang mencerminkan perbedaan persepsi publik terhadap pelaksanaannya. Penelitian ini bertujuan menganalisis sentimen masyarakat menggunakan metode Adaptive Neuro-Fuzzy Inference System (ANFIS) agar perbedaan sentimen positif dan negatif dapat diidentifikasi secara lebih jelas dan terukur. Data penelitian berupa 3520 tweet hasil crawling dengan beberapa kata kunci. Dataset melalui empat tahap persiapan dan dilakukan pembobotan menggunakan TF-IDF. Penelitian ini menguji kinerja ANFIS menggunakan validasi silang K-Fold dengan variasi learning rate (0.001, 0.01, 0.1, 0.2) dan 4 optimasi yakni sgd, adam, RMSProp, Adagrad. Hasil pengujian menunjukkan model uji terbaik menghasilkan akurasi sebesar 56.55%, sensitivitas 19.73%, presisi 38.06%, dan f1-score 25.98% dengan kombinasi parameter learning rate sebesar 0.01 dan optimizer Adam. Hasil evaluasi menggunakan confussion matrix menunjukkan bahwa sentimen positif terhadap pelaksanaan program MBG masih rendah, sehingga diperlukan evaluasi dan perbaikan pada aspek implementasian program.
Pemodelan banjir pluvial perkotaan berbasis SWMM untuk strategi mitigasi di kawasan Ciledug seskoal, Jakarta Selatan Chandra dewi; Dian Krisnawati; Airu Nahdloh; Dian Candra Rini Novitasari
Papanda Journal of Mathematics and Science Research Vol. 5 No. 1 (2026): Volume 5 Nomor 1 Maret 2026
Publisher : Papanda Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56916/pjmsr.v5i1.3064

Abstract

Urban pluvial flooding is one of the most frequent hydrometeorological disasters in densely populated areas and is a serious problem for many cities around the world. This flooding is triggered by high rainfall intensity, represented by the Intensity Duration Frequency (IDF) curve, as well as limited drainage network capacity due to inadequate channel size, hydraulic roughness, sedimentation, and waste accumulation. To address these issues, this study applies an integrated modeling method between SWMM and a 2D hydrodynamic model using rainfall data derived from Intensity Duration Frequency (IDF) analysis based on historical rainfall records from BMKG during the period 2014-2024, DEM/topography, land use, drainage channel characteristics, and actual inundation observations in the Ciledug Seskoal area, South Jakarta. This study aims to analyze the characteristics of pluvial flooding in the study area and evaluate the performance of the SWMM–2D model in simulating surface runoff and flooding processes. The calibration results show that the model is able to capture inflow patterns and hydrographs that are consistent with the observation data. Model validation demonstrated moderate agreement between simulated and observed inundation depths, with a correlation coefficient of r = 0.79 (R² = 0.63). The distribution of flooding depth indicated that most of the affected areas experienced flooding of more than 60 cm, signifying a significant level of risk. The novelty of this study lies in the integration of SWMM and a 2D hydrodynamic model validated with actual inundation data in a dense urban setting, which improves the accuracy of pluvial flood simulation compared to conventional methods. Overall, the integrated SWMM-2D model proved effective in predicting urban pluvial flood characteristics and can be used as a scientific basis for formulating flood mitigation strategies in densely populated residential areas
Perbandingan Ekstraksi Fitur pada Klasifikas Kanker Payudara Implan Menggunakan ELM Zumrotul Muallifah; Dian Candra Rini Novitasari
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol. 17 No. 1 (2026): JURNAL SIMETRIS VOLUME 17 NO 1 TAHUN 2026
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/simet.v17i1.14951

Abstract

Kanker payudara merupakan penyakit tidak menular dengan 18 juta kasus baru dilaporkan pada tahun 2018. Di Indonesia, kanker payudara lebih banyak ditemukan pada perempuan dan menjadi penyebab kematian utama. Kurangnya program skrining dan rendahnya inisiatif masyarakat untuk deteksi dini berkontribusi terhadap tingginya angka kematian akibat kanker di negara berkembang. Salah satu metode deteksi dini adalah mamografi. Namun, citra mammogram yang dihasilkan oleh mesin mamografi memiliki keterbatasan pada situasi tertentu, seperti mendeteksi kanker payudara pada pasien dengan implan payudara. Oleh karena itu, diperlukannya kecerdasan buatan sebagai alat pendukung keputusan untuk deteksi dini kanker payudara. Proses pengolahan data dengan kecerdasan buatan tersebut dapat meliputi beberapa langkah yaitu, augmentasi data, CLAHE, median filtering, ekstraksi fitur menggunakan transformasi Wavelet, dan klasifikasi menggunakan Extreme Learning Machine (ELM). Penelitian ini melibatkan empat kelas kanker yaitu, kanker positif, kanker negatif, kanker implan negatif, dan kanker implan positif. Tujuan dari penelitian ini adalah untuk memperoleh model optimal dalam mengidentifikasi kanker pada implan payudara dengan kecerdasan buatan. Model optimal yang dicapai dalam penelitian ini pada DB 2 Level 1 dengan K-Fold 10 dan 50 hidden node yang menghasilkan akurasi sebesar 80%, sensitivitas 80%, dan spesifisitas 93,33%.
Landslide Modeling with the Savage-Hutter Approach Using the Finite Volume Method Brilian Prilindaputra; Syifa Nasiratun Toyibah; Dinda Rima Rachcita Putri; Dian Candra Rini Novitasari
International Journal of Mechanical Computational and Manufacturing Research Vol. 14 No. 4 (2026): February: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/computational.v14i4.285

Abstract

Landslides are one of the most frequent disasters in Indonesia and have a major impact on the environment and society. This study focuses on modeling the dynamics of landslides in Peniraman Hill, West Kalimantan, using the Savage-Hutter (SH) model solved through the finite volume method (FVM) and the Harten-Lax-van Leer flux scheme. (HLL), supported by the Courant–Friedrichs–Lewy (CFL) method to maintain stable conditions. This study aims to apply the model to real conditions and assess the effectiveness of the numerical approach in describing the movement of land masses. Simulations were conducted on Slopes 1 and 3 which are at risk of landslides due to their soil stability, with three variations of the soil friction angle  to see how changes in these parameters affect the flow mechanism and sliding distance. The results show that the soil friction angle  is a factor that influences landslide behavior. Decreasing the value  makes the landslide move faster and cover a wider area in all parts of the topography. The initial maximum velocity of Slope 1 ranges from ~12–17 m/s with a range of around ~18 meters, while on Slope 3 it reaches ~20–27 m/s with a range of up to ~23.5 meters. Slope 3 consistently produces faster movement and longer sliding distance. Overall, the combination of the SH model with the FVM method and the HLL scheme controlled by CFL conditions has proven to be effective, stable, and capable of representing landslide dynamics. The research results can be an important basis for risk analysis and disaster mitigation strategy planning in the environment around Peniraman Hill to establish exclusion zones and design high load-bearing structures in the potential landslide reach area of ~23.5 meters
Prediksi Potensi Daya Listrik PLTGL-OWC di Selat Makassar Menggunakan Metode Gradient Boosted Tree-Regression (GBT) Adellia Juni Astine; Dian Candra Rini Novitasari; Ratna Cintya Dewi
INSOLOGI: Jurnal Sains dan Teknologi Vol. 5 No. 2 (2026): April 2026
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v5i2.7917

Abstract

The increasing demand for electricity continuously emphasizes the importance of developing renewable energy sources. Indonesia, as a country consisting of many islands, has significant potential to utilize energy from ocean waves, one of which is by using Oscillating Water Column (OWC) technology that can convert wave energy into electrical energy. The purpose of this study is to estimate the electrical energy generated by the OWC type Ocean Wave Power Plant (PLTGL) in the Makassar Strait using the Gradient Boosted Tree Regression (GBT) method. Two approach schemes are used in this study, but the focus of the discussion is on the first scheme, namely the indirect approach. In this approach, predictions are first made on four main variables, namely significant wave variables (Hsig), maximum wave height (Hmax), wave period (wave period), and wind speed (wind speed). The results of the main variable predictions are then used to calculate the electrical power generated by the PLTGL-OWC. The maximum power is estimated to be 23,926 Watts on January 3, 2025 at 12:00, and the minimum power is 3,256 Watts on January 7, 2025 at 19:00. This approach is effective for predicting the power output of ocean wave generators in the Makassar Strait.
Co-Authors Ababil, Achmad Fachril Yusuf Abdulloh Hamid Abdulloh Hamid Achmad Teguh Wibowo Adam Fahmi Khariri Adellia Juni Astine Adyanti, Deasy Afandi, Achsan Ahmad Hanif Asyhar Ahmad Hidayatullah Ahmad Yusuf Ahmad Zoebad Foeady Ahmad Zoebad Foeady Airu Nahdloh Aisyah, Nora Alvin Nuralif Ramadanti Amin, Faris Mushlihul Ananda Nur Izza Arifin, Ahmad Zaenal Aris Fanani Ariyanto Wijaya, Indra Ariyanto, Dimas Azmi, Tasya Auliya Ulul Brilian Prilindaputra Cahyani, Nabila Rahma Chalawatul Ais Chandra dewi Damayanti, Adelia Deasy Adyanti Desy Nur Fitriani Dewi Sukmawati, Chandra Dewi, Ratna Cintya Dian Krisnawati Dianita Utami, Wika Dilla Dwi Kartika Dinda Rima Rachcita Putri Diva Ayu Safitri Nur Maghfiroh Elen Riswana Safila Putri Fahriza Novianti Fajar Setiawan FAJAR SETIAWAN Fajar Setiawan Fajar Setiawan Fajar Setiawan Faris Mushlihul Amin Farmita, Mayandah Ferryan, Dhandy Ahmad Firmansjah, Muhammad Fitria, Nur Annisa Foeady, Ahmad Zoebad Galuh Andriani Ganeshar B.D. Prasanda Gita Purnamasari R Hani Khaulasari Hanimatim Mu'jizah Haq, Dina Zatusiva Ifadah, Corii Indriyani, Jiphie Gilia Irkhana Indaka Zulfa Jauharotul Inayah Khudin, Nasroh Kurniawan, Mohammad Lail Kusaeri Lubab, Ahmad Luluk Mahfiroh Lutfi Hakim Lutfi Hakim Lutfi Hakim Luthfi Hakim Luthfi Hakim M. Hasan Bisri Maliki, Naufal Ridho Mardiyah, Ilmiatul Masruroh Kusman, Umi Maulana, Aashif Amiruddin Maulana, Achmad Resnu Maulana, Jeneiro Mergianti, Wahyu Ningtiyas Moh. Hafiyusholeh Mohammad Rizal Abidin Mohd Fauzi, Shukor Sanim Monika Refiana Nurfadila Muhammad Azhar MUHAMMAD FAHRUR ROZI Muhammad Fahrur Rozi Muhammad Syaifulloh Fattah Muhammad Thohir Musfiroh Musfiroh, Musfiroh Nanang Widodo Nanang Widodo Nanang Widodo Nanang Widodo Nisa Trianifa Novia Adibatus Shofah Noviati Maharani Sunariadi Noviati Maharani Sunariadi Nur Afifah Nur Hidayah Nurissaidah Ulinnuha Pramesti, Diah Devi Pramono, Wahyu Joko Puspitasari, Wahyu Tri Putri Wulandari Putri, Evi Septya Putroue Keumala Intan Rafika Veriani Ramadanti, Alvin Nuralif Ratna Cintya Dewi Ratnasari, Cristanti Dwi Rifa Atul Hasanah RIFA ATUL HASANAH Rozi, Muhammad Fahrur Rozzy, Fahrul Safira, Icha Dwi Sani, Puteri Permata Sari, Firda Yunita Sari, Ghaluh Indah Permata Sari, Yana Vita Setiawan, Fajar Setyawati, Maunah Siti Nur Aisah Siti Nur Fadilah Siti Nur Fadilah Siti Ria Riqmawatin Sukarni, Adinda Ika Sulistiya Nengse Sulistiyawati, Dewi Suwanto Suwanto Suwanto Suwanto Swindiarto, Victory T. Pambudi Syifa Nasiratun Toyibah Tasya Auliya Ulul Azmi Thalia Anindya Ardine Unix Izyah Arfianti USWATUN KHASANAH Utami, Tri Mar'ati Nur Utami, Wika Dianita Utami Dianita Veriani, Rafika Vina Fitriyana Wanda N.P. Sunaryo Wijaya, Indra Ariyanto Wika Dianita Utami Wika Dianita Utami Wika Dianita Utami Wika Dianita Utami Wisnawa, Gede Gangga Yasirah Rezqita Aisyah Yasmin Yuliati, Dian Yuliawanti, Felia Dria Yuni Hariningsih Yuniar Farida Yuyun Monita Yuyun Monita Zahroh, Khofifah Auliyatuz Zulfa, Elok Indana Zumrotul Muallifah