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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Online Mahasiswa (JOM) Bidang Ilmu Sosial dan Ilmu Politik Indonesia Symposium on Computing IJoICT (International Journal on Information and Communication Technology) JOIN (Jurnal Online Informatika) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Kebidanan JURIKOM (Jurnal Riset Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Teknologi Informasi dan Pendidikan Building of Informatics, Technology and Science Jurnal Fisika dan Terapannya JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) International Journal of Clinical Inventions and Medical Sciences (IJCIMS) INFOKUM Jurnal Bumigora Information Technology (BITe) Jurnal Teknik Informatika (JUTIF) Charity : Jurnal Pengabdian Masyarakat Jurnal Pengabdian Masyarakat Indonesia Journal of Innovation Research and Knowledge Jurnal Pengabdian Masyarakat Bhinneka eProceedings of Engineering Electrician : Jurnal Rekayasa dan Teknologi Elektro Indonesian Counseling and Psychology Jurnal INFOTEL IJoICT (International Journal on Information and Communication Technology)
Sri Suryani Prasetyowati
Universitas Telkom
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Physics Public Health Social Sciences

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Analisis Perbandingan Sistem Rekomendasi dengan Faktorisasi Matriks dan Pearson Berbasis Collaborative Filtering Pada Web E-Commerce Marissa Aflah Syahran; Erwin Budi Setiawan; Sri Suryani
Indonesia Symposium on Computing Indonesian Symposium on Computing 2014/Seminar Nasional Ilmu Komputasi Teknik Informatika (SNIKTI)
Publisher : Indonesia Symposium on Computing

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Abstract

Recommender system merupakan suatu sistem yang mampu memberikan suatu rekomendasi kepada user terhadap item, seperti barang, musik, video, film, buku, dan sebagainya, yang mungkin akan dipilihnya. Penelitian ini mengimplementasikan dan menganalisis perbandingan recommender system dengan algoritma pearson serta faktorisasi matriks yang berbasis Collaborative Filtering. Analisis perbandingan didasarkan pada analisis algoritma, nilai Mean Absolute Error (MAE) dan Response time. Dari hasil analisis, didapatkan bahwa kompleksitas algortima faktorisasi matriks Lebih kompleks dari algoritma pearson. Selain itu didapat nilai MAE recommender system dengan algoritma faktorisasi matriks memiliki nilai MAE yang lebih kecil daripada recommender system dengan algoritma pearson serta nilai Response time recommender system dengan algoritma pearson lebih kecil daripada  algoritma faktorisasi matriks. Metode yang paling baik digunakan adalah faktorisasi matriks karena memiliki MAE lebih akurat dibandingkan dengan metode pearson. Perkembangan hardware juga membuat response time tidak berpengaruh secara signifikan
Prediksi Pola Penyebaran Penyakit Demam Berdarah Dengue Di Kabupaten Sukoharjo Menggunakan Metode Ordinary Block Kriging Ellisa Ratna Dewi; Sri Suryani; Yuliant Sibaroni
Indonesia Symposium on Computing Indonesian Symposium on Computing 2014/Seminar Nasional Ilmu Komputasi Teknik Informatika (SNIKTI)
Publisher : Indonesia Symposium on Computing

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Abstract

Sistem prediksi pola penyebaran penyakit Demam Berdarah Dengue di kabupaten Sukoharjo ini dibentuk dengan meggunakan model semivariogram dan metode estimasi Ordinary Block Kriging. Model dan metode ini dipilih sebagai alat untuk memprediksi pola penyebaran penyakit di kabupaten Sukoharjo karena tidak membutuhkan informasi sebelumnya mengenai mean data, sehingga lebih mudah dalam penggunaanya. Validasi silang dipilih sebagai alat ukur validitas model agar model memiliki kriteria kelayakan untuk digunakan pada proses berikutnya. Model terbaik dihasilkan oleh Gaussian dengan validasi 0.3140, dengan variansi kriging sebesar 0.0251 pada grid 0.05. Dari grid tersebut dapat disimpulkan bahwa penyebaran terbesar berada di kecamatan Kartasura, Gatak, Baki, dan Grogol. Sedangkan error yang dihasilakan dari hasil pengujian sistem dengan membandingkan data asli populasi terjangkit dengan hasil estimasi adalah 0.158845523 atau sekitar 15%. Hasil prediksi ini mengindikasikan bahwa terdapat faktor X yang mempengaruhi penyebaran penyakit Demam Berdarah Dengue di kabupaten Sukoharjo.
Prediksi Kandungan Batubara Pada Daerah Disekitar Tambang Batubara Menggunakan Metode Universal Kriging Muhammad Gentur WitjaksonoKurniawan; Sri Suryani; Rian Febrian Umbara
Indonesia Symposium on Computing Indonesian Symposium on Computing 2014/Seminar Nasional Ilmu Komputasi Teknik Informatika (SNIKTI)
Publisher : Indonesia Symposium on Computing

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Abstract

Salah satu permasalahan dalam dunia pertambangan adalah pengestimasian kadar bahan tambang pada suatu daerah. Permasalahan tersebut berkaitan erat dengan metode yang digunakan dalam pengestimasian kadar bahan tambang agar mendapatkan hasil yang akurat. Salah satu metode yang digunakan untuk pengestimasian bahan tambang yaitu Kriging. Metode Kriging terdiri dari berbagai macam seperti Ordinary Kriging, Simple Kriging. Ordinary dan Simple Kriging hanya dapat digunakan pada jenis data yang stasioner. Namun untuk data yang non-stasioner atau mengandung trend / drift, penaksiran dilakukan menggunakan metode Universal Kriging. Pada penelitian kali ini digunakan metode Universal Kriging untuk menaksir kadar batu bara di Kabupaten Kutai Kartanegara. Tahap yang dilakukan adalah menghitung semivariogram eksperimental, semivariogram teoritis, validasi model dan estimasi menggunakan Universal Kriging. Model semivariogram teoritis terbaik yaitu model eksponensial dengan nilai parameter nugget effect : 0, sill : 3.6 dan range : 20. Estimasi dilakukan dengan membagi daerah menjadi kotak-kotak atau grid kemudian dicari titik center sebagai titik taksiran. Taksiran terbaik diperoleh dengan nilai grid : 0.77 yang menghasilkan variansi : 0.0497053 dan nilai MAPE : 13.34371257%. Berdasarkan percobaan yang dilakukan diperoleh informasi bahwa semakin kecil ukuran grid, tingkat penyebaran semakin tinggi karena semakin rapat yang menyebabkan semakin banyak titik yang diestimasi.
Classification of Malaria Complication Using CART (Classification and Regression Tree) and Naïve Bayes Rachmadania Irmanita; Sri Suryani Prasetiyowati; Yuliant Sibaroni
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 1 (2021): Februari 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (618.483 KB) | DOI: 10.29207/resti.v5i1.2770

Abstract

Malaria is a disease caused by the Plasmodium parasite that transmitted by female Anopheles mosquitoes. Malaria can become a dangerous disease if late have the medical treatment. The late medical treatment happened because of misdiagnosis and lack of medical staff, especially in the countryside. This problem can cause severe malaria that has complications. This study creates a system prediction to classify the severe malaria disease using Classification and Regression Tree (CART) method and the probability of malaria complication using Naïve Bayes method. The first step of this study is classifying the patients that have symptom are infected severe malaria or not based on the model that has been built. The next step, if the patient classified severe malaria then the data predicted if there any probability of complication by the malaria. There are 8 possibilities of complication malaria which are convulsion, hypoglycemia, hyperpyrexia, and the combinations of these four. The first step will evaluate by using F-score, precision and recall while the second step will evaluate by using accuracy. The highest result F-score, precision and recall are 0.551, 0.471 and 0.717. The highest accuracy 81.2% which predicted the complication is Hypoglycemia.
Classification of Dengue Hemorrhagic Fever (DHF) Spread in Bandung using Hybrid Naïve Bayes, K-Nearest Neighbor, and Artificial Neural Network Methods Fatri Nurul Inayah; Sri Suryani Prasetiyowati; Yuliant Sibaroni
International Journal on Information and Communication Technology (IJoICT) Vol. 7 No. 1 (2021): June 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/ijoict.v7i1.562

Abstract

Dengue fever is a dangerous disease caused by the dengue virus. One of the factors causing dengue fever is due to the place where you live in the tropics, so that cases of dengue fever in Indonesia, especially in the Bandung Regency area, will continue to show high numbers. Therefore, information is needed on the spread of this disease by requiring the accuracy and speed of diagnosis as early prevention. In terms of compiling this information, classification techniques can be done using a combination of methods Naïve Bayes, K-Nearest Neighbor(KNN), and Artificial Neural Network(ANN) to build predictions of the classification of dengue fever, and the data used in this Final Project are dataset affected by the spread of dengue fever in Bandung regency in the 2012-2018 period. The hybrid classifier results can improve accuracy with the voting method with an accuracy level of 90% in the classification of dengue fever.
The Prediction of Optimal Route of City Transportation Based on Passenger Occupancy using Genetic Algorithm: A Case Study in The City of Bandung Sri Suryani Prasetiyowati; Yuliant Sibaroni; Derwin Prabangkara
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 3: June 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i3.7077

Abstract

Currently, the existence of city transport is increasingly eliminated by private vehicles such as cars and motorcycles. This situation is further exacerbated by the behavior of city transport drivers who are less discipline in driving, or in picking up and dropping off their passengers. The bad behavior is partly caused by the low level of passenger occupancy. The drivers try to search for passengers as much as possible but often ignore the traffic rules. To overcome this problem, an optimal transport route with high passenger potential is required. Therefore, this study investigated the optimal route of city transport based on the passenger occupancy rate in the city of Bandung as the case study. The method employed for determining the optimal route is Genetic algorithm combined with Ordinary Kriging method used for the process of passenger prediction and fitness calculation. The optimal routes are those with higher occupancy rate. The analysis results showed that the use of the Genetic algorithm with a low number of generations succeed in creating new optimal routes even though the increase is not too high the maximum only reaches 4%.This result is certainly important enough to be used in making better public transport routes.
The Effect of Number of Factors and Data on Monthly Weather Classification Performance Using Artificial Neural Networks Shofura Shofura; Sri Suryani M.Si; Linda Salma; Sri Harini
International Journal on Information and Communication Technology (IJoICT) Vol. 7 No. 2 (2021): December 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/ijoict.v7i2.602

Abstract

Current weather-related research only focuses on weather prediction based on raw data and the factors used are generally 4 factors: average temperature, solar radiation, air pressure, and wind. In this research, monthly weather prediction is done using 5 factors where the additional factor used is rainfall in the previous time. In contrast to previous prediction research, the prediction process carried out in this study emphasizes the modeling of training data according to the desired prediction model.. These two things distinguish this research from previous studies. The prediction model used in this study is a classification-based prediction model that is the Artificial Neural Network (ANN) method combined with the backpropagation algorithm for calculating the weight of the ANN network. The data used are meteorological data from 2010 to 2018 in the Bogor area, where data from 2010 to 2016 are used as training data, and data from 2017 to 2018 are used as test data. The results of this study indicate that the design of the model with the use of data for 6 years with feature data of 5 factors has an accuracy rate of 83.33%.
Correlation Between Post Natal Care and Premature Baby Health in the RSKD Ibu & Anak Siti Fatimah Makassar Jamila Kasim; Ratna; Sri Suryani; Oktovina Suka
International Journal of Clinical Inventions and Medical Sciences Vol 2 No 1 (2020)
Publisher : Lamintang Education and Training Centre, in collaboration with the International Association of Educators, Scientists, Technologists, and Engineers (IA-ESTE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36079/lamintang.ijcims-0201.78

Abstract

Premature babies are babies born alive before the 37th week of gestational age which is calculated from the first day of the last menstruation. Baby care in an incubator is a method of caring for infants by putting the baby in a device that serves to help create adequate ambient temperatures with normal temperatures. Providing optimal nutrition is important in the management of premature and very low weight babies. Prevention of infection is the most important part of every newborn component. The purpose of this study was to determine the relationship between post natal care and premature baby health at the Siti Fatimah Makassar Hospital. This study is a cross sectional study, the population in this study were all babies born at gestational age less than 37 weeks and who were temporarily undergoing treatment at Siti Fatimah Hospital Makassar. Sampling using purposive sampling, obtained 30 samples according to inclusion criteria. Data collection is done in a primary way with direct observation techniques. The collected data is then processed and analyzed using Microsoft Excel computer programs and statistical programs (SPSS) version 6.0. Data analysis includes univariate analysis by looking for frequency distribution, bivariate analysis with chi-square test (x <0.05), to determine the relationship between variables. The results of the bivariate analysis found a relationship between postnatal care with premature infant health (p = 0.033). So it can be concluded that there is a relationship between post natal care with premature baby health at the Siti Fatimah Makassar Hospital. Therefore, paramedics should make efforts to continuously improve health services and carry out care of premature babies properly and apply optimal care facilities. For further research, researchers can conduct studies on other treatments provided to premature babies.
Prediksi Tingkat kerawanan penyakit Demam Berdarah Menggunakan Algoritma K-NN dan Random forest (studi kasus di Bandung) Abduh Salam; Sri Suryani Prasetiyowati; Yuliant Sibaroni
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 3 (2020): Juni 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (322.136 KB) | DOI: 10.29207/resti.v4i3.1926

Abstract

Indonesia is a country that is prone to Dengue Fever, this happens because Indonesia is a country with a tropical climate. More than 50 years after Indonesia contracted the dengue virus, dengue fever cases have not been resolved, currently the cases that occur are greatly increased over time this happens because of factors that cause dengue fever. By considering this serious problem, the authors created a system that can predict the vulnerability level in Bandung and looks for the factors that most influence from all factors of Dengue Fever using the KNN Algorithm and Random Forest. The results of the system show the results of the best model is KNN algorithm with RMSE 29,26, and from the model shows the most influencing factors are population density, growth rate population mobility, rainfall, wind speed. by utilizing the results of the study, the government can adjust actions to each level of sub-district vulnerability and pay more attention to the factors that most influence dengue fever according to the results of the study.
Penyusunan Kalender Masa Tanam Untuk Optimasi Produk Sayuran Organik Dalam Mendukung Program Diversifikasi Olahan Pangan B2SA Kelompok Wanita Tani Kreatif Permata Sri Suryani Prasetiyowati
Charity : Jurnal Pengabdian Masyarakat Vol 3 No 1 (2020): Charity - Jurnal Pengabdian Masyarakat
Publisher : PPM Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/charity.v3i1.2041

Abstract

Seiring dengan berkurangnya lahan terbuka di desa Lengkong karena program pengembangan kawasan perumahan, maka program Kawasan Rumah Pangan Lestari (KRPL) yang telah dicanangkan oleh pemerintah menjadi sulit untuk diimplementasikan. Sehingga dengan program pemberdayaan wanita di desa lengkong dan optimalisasi lahan terbuka dan lahan pekarangan yng ada, terbentuklah Kelompok Wanita Tani Kreatif Permata di desa Lengkong Setelah berjalan 10 bulan, KWT Kreatif mulai dapat meningkatkan produksinya, dan mulai dapat memenuhi warga masyarakat sekitar dalam bentuk konsumsi sayur dan ikan, selain mentah juga diolah menjadi beragam produk makanan inovatif. Olahan pangan tersebut diharapkan dapat memperhatikan aspek Bergizi, Berimbang, Sehat dan Aman (B2SA). Salah satu hal mendasar selain untuk ketahanan pangan, perlu adanya olahan pangan di KWT Kreatif adalah produksi sayuran yang berlebih, dan kadang-kadang proporsinya belum seimbang. Tetapi saat ini, program tersebut belum dijalankan oleh KWT Kreatif, karena keterbatasan pengetahuan, peralatan dan pendanaan untuk menuju olahan pangan berbasis B2SA. Oleh karena itu perlu suatu metode untuk optimasi volume produksi sayurannya melalui penyusunan kalender masa tanam sayuran organik KWT Kreatif Permata.
Co-Authors Abduh Salam Adhe Akram Azhari Adhitya Aldira Hardy Aditya Andar Rahim Aditya Faudzan Aditya Firman Ihsan Aditya Gumilar Afrida, Yenni Akmal Muhamad Faza Aniq A. Rohmawati Aniq Atiqi Rohmawati Aqilla, Livia Naura arief rahman Arnasli Yahya Asdar, Meisya Putri Indrayani Asramanggala, Muhammad Sulthon Aufa, Rizki Nabil Azmi Aulia Rahman Bakara, Stella Maris Chamadani Faisal Amri Christina Natalia Claudia Mei Serin Sitio Damar, Muhammad Dede Tarwidi Derwin Prabangkara Diyas Puspandari Ekaputra, Muhammad Novario Ellisa Ratna Dewi Ellisa Ratna Dewi Elqi Ashok Erna Sri Sugesti Erwin Budi Setiawan Fairuz, Mitha Putrianty Fatha, Rizkialdy Fathin, Muhammad Ammar Fatri Nurul Inayah Gede Astawa Pradika Gilang Brilians Firmanesha Gusti Aji, Raden Aria Gutama, Soni Andika Hari Yudha Fanani Hawa, Iqlima Putri Haziq, Muhammad Raffif Hilda Fahlena Hilman Rama Pratama I Putu Ananda Miarta Utama Ibnu Muzakky M. Noor Ichwanul Muslim Karo Karo Indra Kusuma Yoga Indri Octavellia Wulanissa Irfani Adri Maulana Ita Susanti Jauzy, Muhammad Abdurrahman Al Jeckson, Jeckson Juniardi Nur Fadila Karno Karno Kartika Putri Septiyani Kasim, Jamila Lesmana, Aditya Lie Othman Linda Salma Mahadzir, Shuhaimi Maharani, Anak Agung Istri Arinta Mardha Al Nazhfi Ali Marissa Aflah Syahran Marissa Aflah Syahran Mitha Putrianty Fairuz Muh. Ilham Muh. Kiki Adi Panggayuh Muhammad Alauddin Angka Kurniawan Muhammad Damar Muhammad Gentur WitjaksonoKurniawan Muhammad Gentur WitjaksonoKurniawan Muhammad Ghifari Adrian Muhammad Hadyan Baqi Muhammad Ikram Kaer Sinapoy Muhammad Novario Ekaputra Muldani, Muhamad Dika Nanda Ihwani Saputri Naufal Alvin Chandrasa Nazhrin Nazarudin Achmad Nenny Lisbeth Minarno Ni Made Dwipadini Puspitarini Nur Fadila, Juniardi Nuraena Ramdani Nurul Aliyah Nurul Fajar Riani Oktovina Suka Pernanda Arya Bhagaskara S M Pilar Gautama, Hadid Purwanto, Brian Dimas Putra, Ihsanudin Pradana Putri, Pramaishella Ardiani Regita Rachmadania Irmanita Rafika Salis Rahim, Husnul Fahma Rahmanda, Rayhan Fadhil Ratna Rian Febrian Umbara Ridha Novia Ridho Isral Essa Rifaldy, Fadil Rizky Fauzi Ramadhani Rizky Yudha Pratama Rizky, Muhammad Zacky Faqia Salis, Rafika Salsabila, Syifa Shofura Shofura Sinaga, Astria M P Siti Rahmah Madusari Siti Uswah Hasanah Sri Harini Sri Harini Sri Harini Suhendar, Annisya Hayati Tuti Budiawati Willie Japaries Winico Fazry Wira Abner Sigalingging Yulian Sibaroni Yuliant Sibaroni Zaidan, Muhammad Naufal