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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) 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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Pengelompokan Hasil Perkebunan di Indonesia Menggunakan Fuzzy C-Means Aisyah, Nora; Sukarni, Adinda Ika; Sari, Dian Candra Rini Novita
CESS (Journal of Computer Engineering, System and Science) Vol. 9 No. 2 (2024): July 2024
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v9i2.50682

Abstract

Perkebunan merupakan subsektor yang dapat meningkatkan kesejahteraan masyarakat dan juga menambah kekayaan negara indonesia (devisa). Hasil perkebunan dikelompokkan guna mengetahui daerah di Indonesia yang memiliki hasil perkebunan yang kurang baik atau termasuk daerah kurang produktif sehingga dapat dilakukan pembenahan strategi atau pengolahan perkebunan di Indonesia. Pengelompokan atau klasifikasi dilakukan dengan menggunakan metode fuzzy c means dengan data hasil perkebunan kelapa, kelapa sawit, kopi, kakao, karet di Indonesia tahun 2018, 2019, 2020. Penentuan jumlah cluster atau klasifikasi pada fuzzy c-means dilakukan menggunakan uji silhouette index, hal ini dilakukan agar mendapat cluster optimal. Hasil uji silhouette index didapat jumlah cluster optimal yakni 4 cluster, didapatkan daerah yang memiliki hasil perkebunan yang produktif paling tinggi terdapat pada provinsi Riau dan Kalimantan Tengah.
Cluster Analysis of Environmental Pollution in Indonesia Using Complete Linkage Method with Elbow Optimization Damayanti, Adelia; Utami, Wika Dianita; Novitasari, Dian Candra Rini; Intan, Putroue Keumala; Kurniawan, Mohammad Lail
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 7, No 2 (2023): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v7i2.12961

Abstract

The issue of environmental contamination remains unsolved. The problem continues to have a substantial detrimental impact. This research aimed to identify provinces in Indonesia with high or low levels of environmental pollution so that the government may offer treatment to provinces with high levels of pollution and seek a significant reduction in the incidence of environmental pollution in Indonesia. Clustering is required to identify provinces with high and low pollution levels using the complete linkage method because this method can provide tight clusters and is less impacted by outliers. The analysis of the complete linkage method with Elbow optimization revealed two optimal clusters, namely high and low clusters. The high cluster consists of three provinces: Central Java, West Java, and East Java. The low cluster consists of 31 provinces. This research used a Silhouette Coefficient validity test. The value of the Silhouette Coefficient is 0.75. The value indicates that the data object is in the correct cluster and that the cluster structure is relatively strong.
Perbandingan Reduksi Fitur pada Klasifikasi Coronary Artery Disease menggunakan Metode RNN Sari, Yana Vita; Fanani, Aris; Novitasari, Dian Candra Rini
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol. 16 No. 2 (2025): JURNAL SIMETRIS VOLUME 16 NO 2 TAHUN 2025
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/simet.v16i2.12328

Abstract

Coronary Artery Disease (CAD) merupakan kondisi ketika arteri coroner mengalami penyempitan atau penyumbatan yang dapat menjadi pemicu penyakit kardiovaskular dan berujung pada kematian. Oleh karena itu, perlu adanya penanganan yang tepat oleh tenaga medis yang diawali dengan proses diagnosis CAD untuk menilai kesehatan dan kondisi arteri. Diagnosis CAD dapat dilakukan berdasarkan klasifikasi menggunakan metode Recurrent Neural Network (RNN). RNN memiliki kemampuan untuk mempertahankan dan menggunakan informasi sebelumnya dalam pengambilan keputusan. Pada penelitian ini terdapat 30 fitur sehingga dilakukan reduksi fitur untuk meningkatkan kinerja model RNN. Tujuan dari penelitian ini untuk memperoleh model optimal dan mengetahui kefefektifan metode PCA dan ReliefF untuk reduksi fitur pada sistem klasifikasi. Uji coba dilakukan dengan uji coba pembagian data, learning rate, dan node hidden. Model optimum diperoleh pada k-fold 10, node hidden 200, dan learning rate 0.01 pada penggunaan metode ReliefF dengan fitur yang relevan sebanyak 26 diperoleh akurasi 88.42%, sensitivitas 90.82%, dan spesifisitas 86.09%.
The Effectiveness of Canva-Based Learning in Improving Students’ Visual Literacy Fitria, Nur Annisa; Hamid, Abdulloh; Novitasari, Dian Candra Rini; Indriyani, Jiphie Gilia
Intiqad: Jurnal Agama dan Pendidikan Islam Vol 17, No 2 (2025)
Publisher : UMSU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/25820

Abstract

This study aims to measure the effectiveness of Canva-based learning in improving visual literacy among students, given the importance of the ability to interpret, understand, and communicate meaning through visual elements in the digital age. This study used a pre-experimental method with a One Group Pre-test Post-test design, which was conducted at SDN Bejijong 2 Trowulan Mojokerto in May with 32 fifth-grade students as research subjects. Data were collected through pre-tests and post-tests using the Canva application to measure the improvement in students' visual literacy, with 11 indicators according to Avgerinou. Data analysis was performed using SPSS, with the results of the Paired Sample T -Test showed a significant increase in the post-test average score (49.16) compared to the pre-test (37.13), with a difference of 12.03 points and a significance value of 0.000 (p 0.05), which clearly proves that Canva is effective in improving students' visual literacy.
THE GENERALIZED SPACE-TIME ARIMA (GSTARIMA) MODEL FOR PREDICTING NITROGEN MONOXIDE TO MITIGATE EID AL- FITR AIR POLLUTION IN SURABAYA Khaulasari, Hani; Rini Novitasari, Dian Candra; Setyawati, Maunah; Maulana, Jeneiro; Mohd Fauzi, Shukor Sanim
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 1 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss1pp0069-0086

Abstract

Air quality is a crucial factor due to its significant impact on environmental sustainability and public health. One of the major pollutants affecting air quality is Nitrogen Monoxide (NO), especially during periods of increased human mobility such as Eid al-Fitr. Monitoring and predicting NO levels are essential for early mitigation efforts. This study aims to evaluate the performance of the Generalized Space-Time Autoregressive Integrated Moving Average (GSTARIMA) model with three types of spatial weighting schemes and compare it with other forecasting methods, namely ARIMA, VARIMA, and Support Vector Regression (SVR), in predicting NO concentrations in Surabaya for April 2024. The data used in this study consist of daily NO concentration measurements obtained from the Surabaya City Environment Agency’s monitoring stations located at SPKU Tandes, SPKU Wonorejo, and SPKU Kebonsari, covering the period from January 2023 to March 2024. The GSTARIMA model was selected for its capability to capture both spatial and temporal dependencies across monitoring locations. As an extension of the ARIMA model, GSTARIMA incorporates spatial weight matrices to model spatial heterogeneity. Parameter estimation was conducted using the Ordinary Least Squares (OLS) method. The results indicate that the GSTARIMA model with Inverse Distance Weighting (IDW) and order (3,1,0)₁ in the first spatial order yields the most accurate predictions, outperforming ARIMA, VARIMA, and SVR models. The model produced the lowest Symmetric Mean Absolute Percentage Error (sMAPE) of 0.93% and Root Mean Square Error (RMSE) of 5.32. A notable spike in NO concentrations was observed between April 23 and 25, 2024, coinciding with the post-Eid al-Fitr return flow, indicating a surge in population mobility.
OPTIMIZATION OF ARIMA RESIDUALS USING LSTM IN STOCK PRICE PREDICTION OF PT MEDCO ENERGI INTERNASIONAL TBK Ababil, Achmad Fachril Yusuf; Hamid, Abdulloh; Khaulasari, Hani; Novitasari, Dian Candra Rini; Utami, Wika Dianita
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss2pp1405-1420

Abstract

The capital market plays an important role in the economy by providing a means for companies to obtain capital and as a place to invest. Stocks are one of the popular investment instruments because their potential profits are attractive to investors. The stocks used in this study are PT Medco Energi Internasional Tbk (MEDC) shares. The purpose of this study is to obtain the optimal ARIMA-LSTM residual optimization model, how much the accuracy, and to predict Medco stock prices for the next 8-month period. The data used starts from January 4, 2021, to October 31, 2024, was obtained from the yahoofinance.com website. The ARIMA model, which is known to be effective in handling linear data, will be combined with LSTM. The use of residuals in the LSTM model can help LSTM capture patterns in the entire stock data so as to increase prediction accuracy. The research results obtained are the optimal ARIMA-LSTM optimization model, namely, ARIMA ([5,9],1,[5,9,11]) and LSTM with the best hyperparameter, namely, hidden layer 64, batch size 16, and learning rate 0.01. The accuracy of the ARIMA-LSTM optimization model is classified as very accurate, with a MAPE value of 0.3%. Medco Energi’s stock price for the next 8-month period is predicted to increase from IDR1312 to IDR1430 or an increase of 9%.
Identifikasi Kualitas Pelayanan Kesehatan di Jawa Timur Menggunakan Metode Fuzzy C-Means Cahyani, Nabila Rahma; Novitasari, Dian Candra Rini; Azhar, Muhammad
JTERA (Jurnal Teknologi Rekayasa) Vol 10, No 2: Desember 2025
Publisher : Politeknik Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31544/jtera.v10.i2.2025.217-226

Abstract

Ketimpangan distribusi pelayanan kesehatan di Jawa Timur menjadi salah satu tantangan dalam upaya pemerataan akses dan kualitas layanan kesehatan. Penelitian ini bertujuan menggunakan pendekatan Fuzzy C-Means (FCM) untuk menentukan kualitas pelayanan kesehatan di 38 kabupaten dan kota di Jawa Timur. Variabel data yang digunakan meliputi kepadatan penduduk, tenaga kesehatan, dan fasilitas kesehatan di tahun 2024. Sebelum proses klasterisasi, dilakukan analisis korelasi untuk menyederhanakan variabel melalui penggabungan kelompok variabel yang saling berkorelasi tinggi. Hasil klasterisasi FCM menunjukkan bahwa wilayah di Jawa Timur terbagi menjadi tiga klaster, yaitu klaster dengan kualitas pelayanan sangat memadai, cukup memadai, dan kurang memadai. Nilai 0,725 diperoleh melalui evaluasi menggunakan Silhouette Coefficient, yang menunjukkan bahwa struktur klaster yang dihasilkan memiliki kualitas yang tergolong baik. Hasil pemetaan menunjukkan bahwa sebagian besar wilayah berada dalam kategori cukup memadai, namun masih terdapat beberapa wilayah yang memerlukan perhatian lebih dalam pemerataan tenaga dan fasilitas kesehatan. Penelitian ini diharapkan menjadi dasar pertimbangan kebijakan pemerataan pelayanan kesehatan di Jawa Timur melalui program Jatim Sehat.
Pemodelan Run Up Tsunami Selat Sunda Menggunakan Smoothed Particle Hydrodynamics (SPH) Ananda Nur Izza; Desy Nur Fitriani; Thalia Anindya Ardine; Dian Candra Rini Novitasari
UJMC (Unisda Journal of Mathematics and Computer Science) Vol 11 No 2 (2025): Unisda Journal of Mathematics and Computer Science
Publisher : Mathematics Department, Faculty of Sciences and Technology Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/ujmc.v11i2.11435

Abstract

The tsunami that occurred in the Sunda Strait in December 2018 caused extensive damage in the coastal areas of Banten and Lampung. This event was triggered by the collapse of Mount Anak Krakatau, which suddenly displaced water masses without being preceded by a tectonic earthquake, so its generation mechanism differs from that of a typical tsunami. In this study, the Smoothed Particle Hydrodynamics (SPH) method was used, utilizing Sunda Strait bathymetry data to construct a simulation domain, while the tsunami source was represented by fluid deformation around Mount Anak Krakatau. This study aimed to model the propagation and run-up of the tsunami to understand the distribution of the resulting wave energy. The simulation results showed that the tsunami waves tended to propagate northeast and southeast, with a high energy concentration towards the coasts of Banten and Lampung. Although limitations in particle resolution and numerical parameters made run-up values ​​less accurate, the SPH method was able to qualitatively describe the fluid dynamics at the wave generation and propagation stages. This approach shows potential as a tool for studying the characteristics of non-tectonic tsunamis and supporting disaster mitigation efforts in coastal areas.
Prediction of Tides in the Gisik Cemandi Coastal Area Using the Support Vector Regression (SVR) Method Dewi Sukmawati, Chandra; Novitasari, Dian Candra Rini; Dewi, Ratna Cintya
Journal of Information Technology and Computer Science Vol. 10 No. 3: Desember 2025
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.2025103790

Abstract

This study was conducted to predict tidal fluctuations in the coastal area of Gisik Cemandi Village, Sidoarjo, using the Support Vector Regression (SVR) method. The dataset consisted of  time series records of sea level height for the period of March . The prediction process was implemented by testing three SVR kernel types, namely linear, polynomial, and Gaussian Radial Basis Function (RBF), along with variations of the parameters Cost , Gamma , and epsilon . Based on the evaluation using Mean Absolute Percentage Error ( MAPE), the Linear kernel demonstrated the best predictive performance with the lowest MAPE value of  under a  train-test split. The prediction results with the Linear kernel closely matched the actual data, indicating the model’s accuracy and reliability in capturing the linear patterns of tidal data. This model can be utilized as a supporting tool for tidal prediction to aid coastal activities such as navigation and fisheries.
Prediction of Wastewater Treatment Revenue Based on Volume and Number of Transactions Using the Long Short-Term Memory (LSTM) Method Maulana, Aashif Amiruddin; Khaulasari, Hani; Novitasari, Dian Candra Rini; Pramono, Wahyu Joko
Journal of Information Technology and Computer Science Vol. 10 No. 3: Desember 2025
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.2025103806

Abstract

This study aims to develop a prediction model for the total Revenue value of the operational activities of the Keputih Surabaya Sewage Sludge Treatment Plant (IPLT) using the Long Short-Term Memory (LSTM) method. The data used is daily data on total transactions and total Revenue from January 2022 to April 2025. Data normalization using the Min-Max method and outlier detection and handling using the IQR and median imputation techniques are examples of preprocessing steps. The model input structure is formed by utilizing Partial Autocorrelation Function (PACF) analysis to ascertain the number of lags. In this study, 405 model combinations are tested with different parameters, including activation function, number of Epochs, learning rate, and ratios of training and testing data. According to the findings, the model that has the optimal parameters a training and testing data ratio of 80:20, 50 Epochs, a learning rate of 0.002, a Tanh activation function, and 100 neurons can produce predictions for total Revenue with a Mean Absolute Percentage Error (MAPE) of 18.18%. The revenue for the following six months was then forecast using this model; the highest revenue forecast was IDR 3,740,085.00, while the lowest was IDR 1,966,628.25. According to these results, LSTM can accurately forecast time series-based income fluctuations and may find use in the waste management industry's financial decision-making and strategic planning processes.
Co-Authors Ababil, Achmad Fachril Yusuf Abdulloh Hamid Abdulloh Hamid Achmad Teguh Wibowo Adam Fahmi Khariri Adyanti, Deasy Afandi, Achsan Ahmad Hanif Asyhar Ahmad Hidayatullah Ahmad Zoebad Foeady Ahmad Zoebad Foeady 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 Cahyani, Nabila Rahma Chalawatul Ais Damayanti, Adelia Deasy Adyanti Desy Nur Fitriani Dewi Sukmawati, Chandra Dewi, Chandra Dewi, Ratna Cintya Dian Krisnawati Dianita Utami, Wika Dilla Dwi Kartika Diva Ayu Safitri Nur Maghfiroh Elen Riswana Safila Putri Fahriza Novianti Fajar Setiawan FAJAR SETIAWAN Fajar Setiawan Fajar Setiawan Fajar Setiawan Fanani, Aris 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 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 Nahdloh, Airu 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 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 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 Yusuf, Ahmad Yuyun Monita Yuyun Monita Zahroh, Khofifah Auliyatuz Zulfa, Elok Indana