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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 Jurnal Informatika INTEGER: Journal of Information Technology Jurnal Matematika: MANTIK JURNAL MEDIA INFORMATIKA BUDIDARMA BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING 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) Serambi Engineering

Sari, Dian Candra Rini Novita

Universitas Islam Negeri Sunan Ampel Surabaya

Author-ID : 1971240

Religion Arts Humanities Astronomy Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Transportation

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Leukaemia Identification based on Texture Analysis of Microscopic Peripheral Blood Images using Feed-Forward Neural Network Puspitasari, Wahyu Tri; Haq, Dina Zatusiva; Novitasari, Dian Candra Rini
Computer Engineering and Applications Journal (ComEngApp) Vol. 11 No. 3 (2022)
Publisher : Universitas Sriwijaya

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

Leukaemia is very dangerous because it includes liquid tumour that it cannot be seen physically and is difficult to detect. Alternative detection of Leukaemia using microscopy can be processed using a computing system. Leukemia disease can be detected by microscopic examination. Microscopic test results can be processed using machine learning for classification systems. The classification system can be obtained using Feed-Forward Neural Network. Extreme Learning Machine (ELM) is a neural network that has a feedforward structure with a single hidden layer. ELM chooses the input weight and hidden neuron bias at random to minimize training time based on the Moore Penrose Pseudoinverse theory. The classification of Leukaemia is based on microscopic peripheral blood images using ELM. The classification stages consist of pre-processing, feature extraction using GLRLM, and classification using ELM. This system is used to classify Leukaemia into three classes, that is acute lymphoblastic Leukaemia, chronic lymphoblastic Leukaemia, and not Leukaemia. The best results were obtained in ten hidden nodes with an accuracy of 100%, a precision of 100%, a withdrawal of 100%.

Forecasting Sea Surface Salinity in the Eastern Madura Strait Using a 1D Convolutional Neural Network Rozzy, Fahrul; Novitasari, Dian Candra Rini; Yuliati, Dian; Sani, Puteri Permata
Telematika Vol 21 No 1 (2024): Edisi Pertama 2024
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v21i1.8959

Tujuan: Penelitian ini bertujuan untuk memprediksi salinitas permukaan air laut pada perairan Selat Madura bagian Timur menggunakan 1D CNN dan menguji daripada performa model arsitektur 1D CNN yang dibuat. Berdasarkan hasil prediksi yang diperoleh, diharapkan mampu memberi informasi ke masyarakat terkait kondisi salinitas permukaan Selat Madura bagian Timur beberapa hari ke depan.Perancangan/metode/pendekatan: Hal pertama yang perlu dilakukan adalah memprediksi tiap parameter sebelum memprediksi salinitas permukaan. Penelitian ini menggunakan metode 1D CNN, dengan parameter kecepatan arus eastward, arus northward dengan 3 kedalaman berbeda, dan salinitas pada 2 kedalaman berbeda.Hasil: Berdasarkan penelitian ini diperoleh model 1D CNN mampu memprediksi salinitas dengan sangat baik, dengan MAPE sebesar 2.86% pada nilai dropout 0.8 dan batchsize 64. Adapun hasil prediksi untuk 6 hari ke depan, dari 17 Januari 2023 pukul 19.00 hingga 23 Januari 2023 pukul 07.00 dengan rentang waktu per 12 jam adalah mengalami penurunan dengan angka terendah menyentuh 33.313 PSU.Keaslian/ state of the art: Pada penelitian ini menggunakan parameter prediksi, metode, dan diperoleh hasil yang berbeda dengan penelitian sebelumnya.

Breast Cancer Classification Based on Mammogram Images Using CNN Method with NASNet Mobile Model Pramesti, Diah Devi; Farida, Yuniar; Novitasari, Dian Candra Rini; Wibowo, Achmad Teguh
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 19, No 3 (2025): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.98187

In Indonesia, the type of cancer that contributes to the highest death rate is breast cancer, so there is a great need for early examination, clinical examination, and screening, which includes mammography. Mammography is currently the most effective method for detecting early-stage breast cancer. This study aims to classify breast cancer cells based on mammogram images. The method used in this research is CNN (Convolutional Neural Network) with the NASNet Mobile model for classifying three classes: normal, benign, and malignant. The CNN method can learn various input attributes powerfully so that CNN can obtain more detailed data characteristics and has better detection capabilities. This research obtained the most optimal model based on the percentage of accuracy, sensitivity, and specificity values of 99.67%, 98.78%, and 99.35%, respectively. This research can be used to help radiologists as considerations in making breast cancer diagnosis decisions.

PENERAPAN METODE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) UNTUK PREDIKSI BILANGAN SUNSPOT Yuliawanti, Felia Dria; Novitasari, Dian C. Rini; Widodo, Nanang; Hamid, Abdulloh; Utami, Wika Dianita
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 15 No 3 (2021): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Peristiwa magnetik pada matahari ditandai dengan salah satu tanda yaitu munculnya sunspot atau bintik matahari. Sunspot terletak di fotosfer matahari yang memiliki warna lebih gelap dari pancaran sekitarnya. Tujuan dari penelitian ini adalah untuk memprediksi bilangan sunspot dengan menggunakan metode ARIMA. Metode ARIMA dilakukan dengan melihat plot ACF dan PACF untuk mendapatkan model yang akan digunakan dalam prediksi. Penelitian ini menggunakan data bilangan sunspot yang dimulai dari bulan Januari tahun 1987 hingga bulan Desember 2019 sebanyak 396 data. Dari data tersebut didapatkan 4 model ARIMA yaitu ARIMA(3,1,2), ARIMA(3,1,1), ARIMA(2,1,2), ARIMA(2,1,1). Dari keempat model tersebut, model terbaik yang digunakan untuk prediksi yaitu ARIMA(2,1,2) dengan nilai AIC sebesar -884,87.

ANALISIS PREDIKSI JUMLAH PENDUDUK DI KOTA PASURUAN MENGGUNAKAN METODE ARIMA Mardiyah, Ilmiatul; Dianita Utami, Wika; Rini Novitasari, Dian Candra; Hafiyusholeh, Moh.; Sulistiyawati, Dewi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 15 No 3 (2021): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Laju pertumbuhan penduduk di Kota Pasuruan pada tahun 2019 sebesar 0.68% dengan jumlah penduduk 200.422 jiwa. Tingginya pertumbuhan penduduk dapat mempengaruhi kepadatan penduduk. Penelitian ini bertujuan untuk memprediksi pertumbuhan penduduk Kota Pasuruan menggunakan metode ARIMA (Autoregressive Integrated Moving Average). Metode ARIMA adalah cara prediksi data deret waktu yang memiliki tiga model, yaitu AR (Autoregressive), MA (Moving Average), ARMA (Autoregressive Moving Average). Metode ini memiliki parameter (p,d,q) dapat diketahuidari plot ACF dan PACF untuk memastikan model yang akan digunakan untuk prediksi. Dalam penelitian ini data yang digunakan merupakan data penduduk Kota Pasuruan tahun 1983 sampai tahun 2019 sejumlah 37 data. Dari data tersebut didapatkan ARIMA model (1,1,1) dengan jumlah penduduk Kota Pasuruan pada tahun 2020 adalah 203.221 jiwa, didapatkan nilai MSE 10542507.06 dan MAPE 1.52%.

OPTIMIZATION OF TUG SERVICES IN TANJUNG PERAK PORT USING ASSIGNMENT MODEL BASED ON FORECASTING RESULTS OF TUG SERVICES Ramadanti, Alvin Nuralif; Novitasari, Dian C. Rini; Wijaya, Indra Ariyanto; Swindiarto, Victory T. Pambudi; Utami, Wika Dianita
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 1 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Optimizing adequate tugboat services is very much needed to support the operational improvement of the Tanjung Perak port. This study uses the triple exponential smoothing method to predict the number of tug service requests in 2021 and the assignment model to determine the optimal level of operating tugboats. The data used in this study is data on demand for tugboat services for small, medium, and large vessels from 2019 to 2020. Forecasting results show that the highest demand for small boat services is 4551 and 3235. The highest demand for medium vessel services is 479 and the lowest is 365. Meanwhile, for the highest demand for large ship services 61 and the lowest 40. The assignment results show the optimization of Tanjung Perak port by operating 13 tugboats every day.

Prediksi Besar Daya Listrik dari Gelombang Laut Sawu Menggunakan Bidirectional Long Short-Term Memory (Bi-LSTM) Safira, Icha Dwi; Novitasari, Dian Candra Rini; Ulinnuha, Nurissaidah; Setiawan, Fajar
Jurnal Telematika Vol. 20 No. 1 (2025)
Publisher : Yayasan Petra Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61769/telematika.v20i1.742

Several islands in East Nusa Tenggara Province (NTT) are underdeveloped areas with insufficient electrification. Therefore, renewable energy power plants are needed, namely Oscillating Water Column Technology Ocean Wave Power Plants (PLTGL-OWC). The objective of this study is to determine the performance of the bidirectional long short-term memory (Bi-LSTM) method in predicting the potential power generated from the height, length, and period of the Sawu Sea waves in NTT using PLTGL-OWC. This study utilises Sawu Sea wave data collected every 12 hours over 9 months. Bi-LSTM is used in this study because it can overcome the vanishing Gradient problem by utilising both the forward layer and the backward layer, making it more effective in solving complex issues, such as time series prediction. This study conducted tests on hyperparameter batch size and hidden layer node configurations. The smallest mean absolute percentage error (MAPE) prediction values obtained were 9.1943% for the wave height parameter, 11.3585% for the wave length parameter, and 7.1485% for the wave period parameter. It means that the Bi-LSTM method is suitable for predicting the electrical power generated by the PLTGL-OWC in the Sawu Sea, as the height and period parameters fall within the MAPE < 10% category, and the length parameter falls within the MAPE 10-20% category. The average electrical power generated is 2,639,865.948 watts per day over a 31-day period. The Sawu Sea has the potential to serve as a renewable energy source in the NTT region.

Heart Disease Classification Using Extreme Learning Machine (ELM) Method With Outlier Handling One-Class Support Vector Machine (OCSVM) Ariyanto, Dimas; Novitasari, Dian Candra Rini; Hamid, Abdulloh
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.9763

Heart disease remains the leading cause of death globally, accounting for approximately 32% of all deaths. Developing countries are particularly affected due to prevalent risk factors such as hypertension, diabetes, and poor lifestyle habits. Accurate and early diagnosis is essential for effective treatment and prevention. Technological advancements have enabled the precise analysis of complex clinical data. This study investigates the application of the Extreme Learning Machine (ELM) algorithm combined with outlier handling using One-Class Support Vector Machine (OCSVM) for heart disease classification. The dataset, obtained from the University of California, Irvine Machine Learning Repository, consists of 1190 clinical records with 12 numerical features. The ELM model was evaluated using the Tanh activation function and 10-fold cross-validation. Among the tested configurations, the best performance was achieved using 450 hidden neurons, yielding a sensitivity of 92,52% with a standard deviation of 4,00%. These results indicate that ELM, when paired with effective outlier handling and properly tuned parameters, can provide reliable and stable performance in heart disease classification.

Optimasi Produksi Makanan Menggunakan Fuzzy Linear Programming Putri, Evi Septya; Farmita, Mayandah; Novitasari, Dian Candra Rini
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Vol 6, No 2 (2022): InfoTekJar Maret
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/infotekjar.v6i2.5033

Restoran Chickenoya adalah rumah makan yang memproduksi berbagai macam olahan daging ayam. Pemilik restoran belum maksimal dalam menentukan banyaknya ayam yang harus diproduksi untuk mencapai keuntungan yang maksimum. Hal tersebut dikarenakan ada beberapa faktor yang mempengaruhi, seperti ketidakpastian jumlah bahan baku yang tersedia dan kondisi keuangan yang tidak stabil. Oleh karena itu perlu dilakukannya optimasi yaitu dengan metode Fuzzy Linear Programming (FLP). Dari hasil penelitian diperoleh solusi optimal untuk produksi pada menu Ayam Geprek sebanyak 4532 porsi dan Menu Ayam Krispi sebanyak 2366 porsi dengan keuntungan sebesar Rp. 20.514.680.

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

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.

Co-Authors Abdulloh Hamid Abdulloh Hamid Achmad Teguh Wibowo Adam Fahmi Khariri Adyanti, Deasy Ahmad Hanif Asyhar Ahmad Hidayatullah Ahmad Zoebad Foeady Ahmad Zoebad Foeady Aisyah, Nora Alvin Nuralif Ramadanti Amin, Faris Mushlihul Arifin, Ahmad Zaenal Aris Fanani Ariyanto Wijaya, Indra Ariyanto, Dimas Azmi, Tasya Auliya Ulul Chalawatul Ais Damayanti, Adelia Deasy Adyanti 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 Farida, Yuniar 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 Kurniawan, Mohammad Lail Kusaeri Kusaeri Lubab, Ahmad Luluk Mahfiroh Lutfi Hakim Lutfi Hakim Lutfi Hakim Luthfi Hakim Luthfi Hakim M. Hasan Bisri Mardiyah, Ilmiatul Masruroh Kusman, Umi Maulana, Achmad Resnu Maulana, Jeneiro Moh. Hafiyusholeh Mohammad Rizal Abidin Mohd Fauzi, Shukor Sanim Monika Refiana Nurfadila MUHAMMAD FAHRUR ROZI Muhammad Fahrur Rozi Muhammad Syaifulloh Fattah Muhammad Thohir Musfiroh Musfiroh, Musfiroh Nanang Widodo Nanang Widodo Nanang Widodo Nanang Widodo Nisa Trianifa Noviati Maharani Sunariadi Noviati Maharani Sunariadi Nur Afifah Nur Hidayah Nurissaidah Ulinnuha Pramesti, Diah Devi 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 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, Yuniar Yusuf, Ahmad Yuyun Monita Yuyun Monita Zahroh, Khofifah Auliyatuz Zulfa, Elok Indana

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