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All Journal ComEngApp : Computer Engineering and Applications Journal JSI: Jurnal Sistem Informasi (E-Journal) Jurnal Teknologi Informasi dan Ilmu Komputer Annual Research Seminar BAREKENG: Jurnal Ilmu Matematika dan Terapan PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Jurnal Infomedia Riau Journal of Empowerment Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) CCIT (Creative Communication and Innovative Technology) Journal Indonesian Journal of Electrical Engineering and Computer Science Sriwijaya Journal of Informatics and Applications Jurnal Generic Jurnal Informatika dan Rekayasa Komputer Journal of Embedded Systems, Security and Intelligent Systems

Desty Rodiah

Department Informatics Engineering, Faculty Of Computer Science, Sriwijaya University

Author-ID : 3870336

Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Library & Information Science Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

Published : 31 Documents Claim Missing Document

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Perbandingan Metode Certainty Factor Dan Backpropagation untuk Mendiagnosis Penyakit Gangguan Tidur Oktaria Permata Sari; Arti Dian Nastiti; Rusdi Efendi; Desty Rodiah
Generic Vol 12 No 2 (2020): Vol 12, No 2 (2020)
Publisher : Fakultas Ilmu Komputer, Universitas Sriwijaya

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

Gangguan tidur merupakan salah satu penyakit yang sering diabaikan, kondisi ini jika terus diabaikan maka akan sangat berpengaruh pada kesehatan penderita. Sistem pakar untuk mendiagnosis gejala awal penyakit gangguan tidur sangat diperlukan. Sistem pakar yang dibangun menggunakan metode Certainty Factor dan Backpropagation dimana kedua metode ini akan memberikan informasi hasil diagnosis penyakit, confidance serta solusi awal dari penyakit yang diderita. Hasil Confidance dari metode Certainty Factor dan Backpropagation akan dibandingkan untuk melihat metode mana yang paling akurat dalam mendiagnosis penyakit gangguan tidur. Penelitian ini menggunakan 18 gejala penyakit gangguan tidur, 6 jenis penyakit gangguan tidur serta 24 kasus pengujian. Dari 24 kasus pengujian didapat hasil tingkat akurasi sebesar 100% pada metode Certainty Factor sedangkan untuk metode Backpropagation didapat hasil tingkat akurasi sebesar 70.83%.

Pemanfaatan aplikasi daring untuk peningkatan pemasaran songket dan purun perajin Burai Sri Indra Maiyanti; Anita Desiani; Sugandi Yahdin; Erwin Erwin; Desty Rodiah; Muhammad Naufal Rachmatullah; Dite Geovanni; Muhammad Akmal Shidqi; Muhammad Gibran Al-Filambany
Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) Vol 5, No 2 (2022): Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS)
Publisher : University of Islam Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33474/jipemas.v5i2.14356

Opinion Mining of Light Rail Transit Development in Indonesia Sarifah Putri Raflesia; Dinda Lestarini; Firdaus Firdaus; Desty Rodiah
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 2: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i2.pp791-796

Light rail transit (LRT), or fast tram is urban public transport using rolling stock similar to a tramway, but operating at a higher capacity, and often on an exclusive right-of-way. Indonesia as one of developing countries has been developed the LRT in two cities of Indonesia, Palembang and Jakarta. There are opinions toward the development of LRT, negative and positive opinions. To reveal the level of LRT development acceptance, this research uses machine learning approach to analyze the data which is gathered through social media. By conducting this paper, the data is modeled and classified in order to analyze the social sentiment towards the LRT development.

Effect of Genetic Algorithm on Prediction of Heart Disease Stadium using Fuzzy Hierarchical Model Dian Palupi Rini; Defrian Afandi; Desty Rodiah
Computer Engineering and Applications Journal Vol 11 No 3 (2022)
Publisher : Universitas Sriwijaya

The Fuzzy Hierarchical Model method can be used to predict the stage of heart disease. The use of the Fuzzy Hierarchical Model on complex problems is still not optimal because it is difficult to find a fuzzy set that provides a more optimal solution. This method can be improved by changing the membership function constraints using Genetic Algorithm to get better predictions. Tests carried out using 282 heart disease patient data resulted in a Root Mean Squared Error (RMSE) value of 0.55 using the best Genetic Algorithm parameters, including population size of 140, number of generations of 125, and a combination of cross-over rate and mutation rate of 0.4 and 0.6 whereas the RMSE value generated by the Fuzzy Hierarchical Model before being optimized by the Genetic Algorithm was 0.89. These results indicate an increase in the predictive value of the Fuzzy Hierarchical Model after being optimized using the Genetic Algorithm.

MEMBER ELECTION DECISION SUPPORT SYSTEM SOUTH SUMATERA PASKIBRAKA USING TOPSIS-PROMETHEE METHOD Angga Adiningrat Mulyanata; Yunita Yunita; Desty Rodiah
Sriwijaya Journal of Informatics and Applications Vol 3, No 2 (2022)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/sjia.v3i2.41

Paskibraka is the best young generation selected through various selections to raise and lower the Heritage Flag on Indonesian Independence Day. However, in the enthusiasm of the students to take part, the Dispora of South Sumatra Province still uses a manual assessment system so that several obstacles were found in its implementation. done with Microsoft Excel, as well as a calculation system that can only be used for one period, while this selection is an annual event that is held every time to celebrate Indonesian Independence Day. Therefore we need a way that can help the Dispora of South Sumatra Province in determining the best alternative for paskibraka members. One algorithm that is useful in decision support is Topsis. Topsis is used in the application of values for each criterion and a different range of values. Then using the Promethee method can improve the Topsis method because the Promethee method is used to determine the order of priority in multi-criteria analysis. The data taken by 60 participants were then researched according to predetermined criteria including written test scores, interview tests, health tests, physical fitness, and posture. Produced the best participants according to the system as many as 15 data. The results of the research test have an accuracy of 80%.

Peramalan Produksi Pempek Dengan Metode Moving Average Dan Exponential Smoothing Desty Rodiah; Yunita
Jurnal Informatika Dan Rekayasa Komputer(JAKAKOM) Vol 2 No 1 (2022): JAKAKOM Vol 2 No 1 April 2022
Publisher : LPPM Universitas Dinamika Bangsa

Keberagaman jenis pempek membuat peminat pempek memiliki kegemaran tertentu terhadap jenis pempek. Hal tersebut membuat pelaku pempek kadang kesulitan dalam menentukan jumlah produksi pempek sesuai dengan kegemaran peminat pempek. Sistem peramalan diperlukan untuk menentukan jumlah produksi pempek agar jumlah pempek sisa dapat di minimalisir. Penelitian menggunakan Metode Single Moving Average (SMA) dan metode Single Exponential Smoothing (SES) untuk meramal jumlah produksi pempek yang harus dibuat di kemudian hari. Penelitian ini menggunakan menggunakan nilai alfa 0,1 sampai 0,9 untuk metode SES dan nilai pergerakan 2 sampai 5 untuk metode SMA. Penelitian ini menggunakan 9 jenis pempek yang dijadikan data uji dan setiap jenis pempek ada 303 data. Indikator perbandingan dilihat dari akurasi peramalan dengan mencari kesalahan terkecil degan menggunakan metode Mean Absolute Percentage Error (MAPE). Metode SES menghasilkan persentase kesalahan yang paling kecil dengan nilai alfa 0,9 terdapat pada jenis pempek lenjer kecil (6,90%), Tahu (2,51%), Adaan (1,83%), Kulit (2,62%), Keriting (12,07%), Model (11,79%) dan Telor besar (4,05%). Metode SMA menghasilkan persentase kesalahan paling kecil dengan nilai pergerakan =2 terdapat pada jenis pempek keriting (31,80%), Model (12,33%), Tekwan (0,1%) dan telor besar (1,40%).

Implementation of K-Means and SAW Methods in Determining Non-Cash Food Aid Recipients Yunita Yunita; Rizki Kurniati; Desty Rodiah; Allsela Meiriza; Luh Sri Mulia Eni
CCIT Journal Vol 16 No 2 (2023): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/ccit.v16i2.2525

Determination of prospective non cash food assistance recipients, especially in Air Talas village, still uses a manual system so that in the process of determining the recipient there is a risk that the recipient will be inaccurate, so that the village government needs a system that can assist the process of determining prospective non cash food assistance recipients. This study aims to implement the K-Means and SAW methods in determining recipients of non cash food assistance in Air Talas village. The benefits of this research can help the Air Talas village government in determining and recommending prospective non cash food assistance recipients in accordance with established criteria, making it easier to filter, group, and rank appropriate population data according to criteria. In addition, this research is also useful for providing convenience to the community through data collection, clustering, and ranking in a transparent, real, and fast and accurate manner using decision support system software. The K-Means clustering method and the Simple Additive Weighting Ranking method were used in this study with data collection techniques through interviewing sources, in this case the village government, the social section of the community, and through collecting village archive data and relevant journals. The research location is Air Talas village with 316 data used. The results of the study are clustering data as much as 77 data obtained from feasible clusters. The cluster data was then tested using the accuracy value and obtained a value of 80%. Then the research is also in the form of ranking data using clustered data which obtains an accuracy value of 64%.

Text Summarization with K-Means Method Ari Firdaus; Novi Yusliani; Desty Rodiah
Sriwijaya Journal of Informatics and Applications Vol 2, No 2 (2021)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/sjia.v2i2.25

Text Summarization is a tool used to generate a short form of text that contains important information that is needed by the user automatically. In this study, Text Summarization was conducted on Indonesian news using K-Means method. The news is taken from CNN Indonesia with a free topic. K-Means is used to classify sentences that already have weight in the news with 2 clusters, namely text summaries and not text summaries. The initial centroid is selected based on the sentence with the largest value and the sentence with the smallest value. The test conducted on Indonesian news with a total 50 news and tested for feasibility using a questionnaire. K-Means was successfully summarizing the news with an average 27.3 % of original news length and gain 87% good summarize based on respondents from questionnaire.

Pencarian Tugas Akhir dengan Ontologi dan Boyer-Moore (Studi Kasus: Jurusan Teknik Informatika UNSRI) Rodiah, Desty; Yunita, Yunita; Yusliani, Novi
Generic Vol 15 No 1 (2023): Vol 15, No 1 (2023)
Publisher : Fakultas Ilmu Komputer, Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/generic.v15i1.140

Website sipeta.ilkom.unsri.ac.id adalah website yang menampung data tugas akhir mahasiswa Jurusan Teknik Informatika UNSRI. Namun website tersebut menggunakan penyimpanan dengan basis data biasa. Pada penelitian ini membuat pencarian data tugas akhir mahasiswa dengan memanfaatkan web semantik ontologi agar data yang dimiliki tidak hanya memiliki nilai, tetapi juga memiliki pengetahuan tentang relasi antar informasi yang saling berkaitan. Komponen yang digunakan dalam teknologi semantik adalah RDF yang dipergunakan sebagai representasi pengetahuan yang digunakan, kemudian SPARQL yang digunakan sebagai query untuk mengambil informasi yang terdapat dalam Ontologi RDF. Selain itu juga digunakan Algoritma Boyer Moore untuk mendapatkan nilai similarity antara data yang didapatkan dari hasil pencarian dengan keyword yang dimasukkan. Jenis pencarian yang dirancang ada 3 pencarian yaitu keyword search, simple search dan advanced search. Dan ketiga pencarian tersebut juga akan di kombinasikan dengan algoritma Boyer Moore. Hasil pencarian dengan ontologi dengan pencarian dengan ontologi dan Algoritma Boyer Moore dihasilkan bahwa pencarian dengan Boyer Moore membutuhkan waktu lebih lama secara rata-rata sekitar >=0,0001 perdetik dalam 5 kali percobaan dibandingkan pencarian dengan ontologi saja. Untuk Algoritma Boyer Moore dilakukan pengujian dengan ROC didapatkan hasil akurasi sebesar 99,84% untuk 16 kali percobaan.

Comparison Of Dempster Shafer AND Certainty Factor Methods In Expert System For Early Diagnosis Of Stroke Disease Arsalan, Osvari; Febrivia, Pretty Fujianti; Utami, Alvi Syahrini; Rodiah, Desty
Sriwijaya Journal of Informatics and Applications Vol 5, No 1 (2024)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/sjia.v5i1.79

Stroke is one of endangering disease if not treated properly and could lean to death. Most people unwilling to check their health because of high cost, lack of medical service, medical staff of neurologist and their limited working time. Therefore, we need an expert system that can help in early diagnosis of stroke. The Dempster Shafer and Certainty Factor methods are expert systems methods used in many cases to support uncertainty from the expert. The aim of this study is to compare two methods to determine the best method in the expert system for diagnosing stroke, by calculating symptoms so as to produce CF values in the Certainty Factor method and density values in the Dempster Shafer method. The data used in the study to diagnose stroke consisted of data on eighteen disease symptoms and two types of stroke identified. Based on the results of testing on 105 test data, the accuracy value of the expert system for diagnosing stroke using the Dempster Shafer method is 95.2% and the accuracy value of the expert system for diagnosing stroke with the Certainty factor method is 98.1%.

Co-Authors Abdiansah Abdiansyah, Abdiansyah Afandi, Defrian Ahmad Nauvan Zikri Al Ghifran Akbar, Muhammad Rafi Al-Filambany, Muhammad Gibran Allsela Meiriza, Allsela Alvi Syahrini Utami Angga Adiningrat Mulyanata Anita Desiani Ardani, Vanya Terra Ari Firdaus Arti Dian Nastiti Buchari, Muhammad Ali Defrian Afandi Dellin Irawan Dian Palupi Rini Dian Palupi Rini Dicky Ahmad Rizaldi Dinda Lestarini Dite Geovanni Erwin Erwin Erwin, Erwin Fahriza, Dicky Febrivia, Pretty Fujianti Firdaus Firdaus Fitria Khoirunnisa Geovanni, Dite Irawan, Dellin Irmeilyana Jambak, Muhammad Ihsan Junia Kurniati Junia Kurniati, Junia Kanda Januar Miraswan Luh Sri Mulia Eni M. Fachrurrozi . Mardiana Mardiana Marjusalinah, Anna Dwi Mastura Diana Marieska Mudinillah, Adam Muhammad Akmal Shidqi Muhammad Gibran Al-Filambany Muhammad Naufal Rachmatullah Ngudiantoro . Novi Yusliani Nur Hamidah Oktaria Permata Sari Osvari Arsalan Qurrota ‘Aini Muthmainnah Rizki Kurniati Rusdi Efendi Sadana, Feron Samsuryadi Samsuryadi Saparudin Saparudin Sarifah Putri Raflesia Sarpanda, Dama Putra Shidqi, Muhammad Akmal Sri Indra Maiyanti Sri Indra Maiyanti Sugandi Yahdin Vanya Terra Ardiani Wahyuni, Putri Eka Winda Agusthia Yunita YUNITA Yunita Yunita Yunita Yunita Yunita Yunita

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