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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 Fountain of Informatics Journal JPSE (Journal of Physical Science and Engineering) Jurnal Teknologi dan Sistem Komputer Journal of Information Technology and Computer Science RABIT: Jurnal Teknologi dan Sistem Informasi Univrab 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 METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi JUMANJI (Jurnal Masyarakat Informatika Unjani) Jurnal Telematika Mathvision : Jurnal Matematika Building of Informatics, Technology and Science Transformasi : Jurnal Pendidikan Matematika dan Matematika Specta Journal of Technology Jurnal Mnemonic Majalah Ilmiah Matematika dan Statistika (MIMS) Dinamika Informatika: Jurnal Ilmiah Teknologi Informasi Insyst : Journal of Intelligent System and Computation 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 Jurnal Informatika: Jurnal Pengembangan IT Sains Data Jurnal Studi Matematika dan Teknologi Journal Serambi Engineering (JSE) Indonesian Journal of Mathematics and Natural Sciences
Dian Candra Rini Novitasari
Universitas Islam Negeri Sunan Ampel
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Application Random Forest Method for Sentiment Analysis in Jamsostek Mobile Review Azmi, Tasya Auliya Ulul; Hakim, Luthfi; Novitasari, Dian Candra Rini; Utami, Wika Dianita Utami Dianita
Telematika Vol 20 No 1 (2023): Edisi Februari 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i1.8868

Abstract

Purpose: This study aims to monitor the service quality of JMO applications from time to time by classifying JMO user reviews into the class of positive, neutral, and negative sentiments.Design/methodology/approach : The method used in this study is the random forest classification method. Data processing in this study uses feature extraction, TF-IDF and labeling with the lexicon-based method.Findings/result: Based on the research results, it was found that the highest frequency of classification was the positive class with 17571 reviews compared to the neutral class with 8701 reviews and the negative class with 3876 reviews with an accuracy evaluation value of 93%, precision 88%, recall 93%, and f1-score 90%.Originality/value/state of the art:This study uses 150737 reviews that have been pre-processed using the random forest method and TF-IDF and lexicon-based feature extraction.
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.
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.
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.
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: Jurnal Matematika 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.
A STUDY ON THE APPLICABILITY OF TRAPEZOIDAL FUZZY AHP WITH FEATURE SELECTION: THE CASE OF SKSS SCHOLARSHIP RECIPIENTS AT BAZNAS EAST JAVA Syamil Waris Dien Muhammad; Abdulloh Hamid; Hani Khaulasari; Dian Candra Rini Novitasari; Moh Hafiyusholeh
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 3 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss3pp2027-2044

Abstract

The One Family One Graduate (SKSS) scholarship program, managed by BAZNAS East Java, aims to alleviate the financial burden of higher education for underprivileged communities. However, the absence of clearly defined weights for each selection criterion may lead to unfairness in the selection process. This study aims to determine the objective weights of each criterion and to rank prospective scholarship recipients using the Trapezoidal Fuzzy AHP approach. The data were obtained from 78 scholarship applicants for the 2024 SKSS period and from questionnaires completed by three expert respondents (expert judgment). Feature selection was conducted to identify the most relevant criteria, resulting in 13 selected variables are tuition fee per semester (K₁), father's latest education level (K₂), father's income (K₃), mother's latest education level (K₄), mother's income (K₅), house size (K₆), amount of family installments (K₇), number of parental dependents (K₈), income of working family members (K₉), type of transportation used to campus (K₁₀), distance from home to campus (K₁₁), monthly allowance (K₁₂), and monthly income if the student is working (K₁₃). The results show that the criterion with the highest weight is tuition fee per semester (0.139142), while the lowest is Type of transportation to campus (0.059970). The highest priority subject is Subject 74 (S_74) with a total weight of 0.7964, whereas Subject 23 (S_23) ranks lowest with a total weight of 0.7723. These findings are expected to enhance the objectivity and fairness of the SKSS scholarship selection process.
Co-Authors Abdulloh Hamid Abdulloh Hamid Abdulloh Hamid Achmad Fachril Yusuf Ababil Achmad Teguh Wibowo Achsan Afandi Adam Fahmi Khariri Adelia Rova Chumairo Adellia Juni Astine Adyanti, Deasy Ahmad Hanif Asyhar Ahmad Hidayatullah Ahmad Yusuf Ahmad Zoebad Foeady Ahmad Zoebad Foeady Airu Nahdloh Aisyah, Nora Aliya Octavia Ramadhani 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 Fanny Maulidya Faris Mushlihul Amin Farmita, Mayandah Febriana Eka Adkhaniyah Ferryan, Dhandy Ahmad Firmansjah, Muhammad Fitria, Nur Annisa Foeady, Ahmad Zoebad Galuh Andriani Ganeshar B.D. Prasanda Gita Purnamasari R Hani Khaulasari Hani Khaulasari Hani Khaulasari Hanimatim Mu'jizah Haq, Dina Zatusiva Ifadah, Corii Indriyani, Jiphie Gilia Irkhana Indaka Zulfa Ivone Lovenia Youvita Izza Dhinillah Jauharotul Inayah Jeneiro Maulana Jiphie Gilia Indrayani Kurniawan, Mohammad Lail Kusaeri Lubab, Ahmad Luluk Mahfiroh Lutfi Hakim 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 Maunah Setyawati Maunah Setyawati Moh. Hafiyusholeh Mohammad Rizal Abidin Monika Refiana Nurfadila Muhammad Azhar Muhammad Azhar MUHAMMAD FAHRUR ROZI Muhammad Fahrur Rozi Muhammad Syaifulloh Fattah Muhammad Thohir Musfiroh Musfiroh Musfiroh Musfiroh, Musfiroh Nabila Rahma Cahyani Nanang Widodo Nanang Widodo Nanang Widodo Nanang Widodo Nasroh Khudin Naufal Ridho Maliki Nimas Nabila Anggraeni Nisa Trianifa Novia Adibatus Shofah Noviati Maharani Sunariadi Noviati Maharani Sunariadi Nur Afifah Nur Hidayah Nurissaidah Ulinnuha Nurul Istiqomah Pramesti, Diah Devi Pramono, Wahyu Joko Puspitasari, Wahyu Tri Putri Oktavia, Nabiilah Putri Wulandari Putri, Evi Septya Putroue Keumala Intan Rachma Raudhatul Jannah 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 Setiawan, Fajar Shukor Sanim Mohd Fauzi 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 Syamil Waris Dien Muhammad Syifa Nasiratun Toyibah Syukron Abdul Aziz 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 Wahyu Ningtiyas Mergianti Wanda N.P. Sunaryo Wijaya, Indra Ariyanto Wika Dianita Utami Wika Dianita Utami Wika Dianita Utami Wika Dianita Utami Wisnawa, Gede Gangga Yana Vita Sari 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