Garuda - Garba Rujukan Digital

Decision Tree and K-Nearest Neighbor (K-NN) Algorithm Based on Particle Swarm Optimization (PSO) for Diabetes Mellitus Prediction Accuracy Analysis Andi Nur Rachman; Supratman Supratman; Euis Nur Fitriani Dewi
CESS (Journal of Computer Engineering, System and Science) Vol 7, No 2 (2022): July 2022
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v7i2.34245

Penyakit Diabetes Mellitus merupakan penyakit tidak menular, tetapi penyakit ini merupakan salah satu penyakit yang mematikan bagi yang mengidapnya. Penyakit ini disebabkan oleh beberapa factor diantaranya pola makan hidup yang tidak teratur atau berlebihan. Apabila penyakit ini tidak dihentikan, maka penderita penyakit Diabetes Mellitus akan semakin memakan para pasien penderita penyakit ini. Menurut WHO atau World Health Organization, sekitar 425 juta orang menderita penyakit diabetes, kemudian 1,6 juta kematian setiap tahunnya di akibatkan oleh penyakit diabetes. Kemudian, pada tahun 2016 di Indonesia, kematian yang disebabkan oleh penyakit diabetes sekitar 99 ribu jiwa. Penyakit diabetes pada tahun ke tahun semakin meningkat, jadi perlu adanya sebuah sistem yang dapat membantu medis untuk melakukan klasifikasi terhadap diabetes berdasarkan data kesehatan pasien. Salah satu metode yang dapat digunakan untuk memprediksi penyakit diabetes mellitus adalah dengan menggunakan data mining. Data mining merupakan suatu proses yang interaktif untuk memprediksi penyakit diabetes mellitus. Prediksi untuk mendiagnosis penyakit ini menggunakan seleksi fitur berbasis Particle Swarm Optimization (PSO) pada dataset Kaggle.com. Dan metode klasifikasi yang digunakan yaitu metode Decision Tree dan K-Nearest Neighbors (K-NN). Hasil dari penelitian ini menghasilkan nilai akurasi tertinggi sebanyak 79.8% dengan AUC 0.71 dengan menggunakan metode Decision Tree, dan untuk menggunakan optimasi metode K-Nearest Neighbors (K-NN) menggunakan Particle Swarm Optimization (PSO) memiliki nilai akurasi tertinggi sebanyak 77.09%.

IMPLEMENTASI APLIKASI TOKO ONLINE GANGER UNTUK PENDAUR ULANG SAMPAH BERBASIS WEB DI TASIKMALAYA Andi Nur Rachman; Cecep Muhamad Sidik Ramdani; Euis Nur Fitriani Dewi
Journal of Appropriate Technology for Community Services Vol. 1 No. 1 (2020)
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/jattec.vol1.iss1.art2

Currently in 2018 Indonesia's creative industry is growing rapidly with evidence of the emergence of start-ups and companies of the nation's work more and more popping up as well as GoJek, BukaLapak and others. The community is also very supportive of this, seen from the number of users on each of these platforms. This can conclude that the Indonesian people today prefer facilities that are efficient, fast and inexpensive. Therefore the Digitat company has a wide market in Indonesia. These problems such as economic and waste issues, Garbage Ranger or abbreviated as GANGER present as an application that can be a link between buying and selling providers or waste management and recycling business, becoming a place of buying and selling between consumers and recycling businesses, being a provider of information on product manufacturing -products from trash and waste pricing information providers.

USABILITY EVALUATION SIMAK SILIWANGI UNIVERSITY USING HEURISTIC EVALUATION AND WEBUSE APPROACH Andi Nur Rachman; Euis Nur Fitriani Dewi; Reynaldi Akbar Maulana; Arif Muhamad Nurdin
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 4 (2022): JUTIF Volume 3, Number 4, August 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.4.218

Sistem Informasi Akademik (SIMAK) of Siliwangi University is one of the information systems developed by UPT TIK, Siliwangi University. SIMAK must be able to become a website that is easy to use, has informative value, and has a high level of usability. User experience in using and operating it can be a measure of acceptance of SIMAK. Based on previous research, it is stated that SIMAK still does not meet the expectations of users. Therefore, in this study usability evaluation was carried out based on the Heuristic Evaluation and Web Usability Evaluation (WEBUSE) approaches. This study discusses the results of usability analysis based on the results of data collection from questionnaires distributed to 100 respondents who are active students (S1), lecturers, and staff at Siliwangi University. The results of usability measurements based on the Heuristic Evaluation method obtained usability points of 70.74% and the results of usability measurements based on the WEBUSE method obtained usability points of 67.84%. The results of usability measurements based on the Heuristic Evaluation and WEBUSE methods have consistent results which state that the SIMAK UNSIL website has a usability level of "Good". However, in some variable indicators there are still indicators that have low values, therefore it is necessary to make improvements based on the recommendations given to improve SIMAK quality.

COVID-19 Vaccination Sentiment Analysis on Twitter Using Random Forest and Information Gain Andi Nur Rachman; Husni Mubarok; Euis Nur Fitriani Dewi; Mitha Maharani
IJISTECH (International Journal of Information System and Technology) Vol 6, No 3 (2022): October
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v6i3.246

Covid-19 in Indonesia has increased from January 2021 unti February 2021 there were 1,217,468 people who were confirmed positive for the corona virus. As a result the increase in the number, the government has taken preventive measures, one of which is the distribution of vaccines or vaccinating the Indonesian people, which has been started since January 13,2021. The government’s covid-19 vaccination efforts had a broad influence on the community through social media (especially Twitter) which then led to pros and cons. Therefore, sentiment analysis is needed to predict the tendency of public opinion regarding the Covid-19 vaccination policy which is classified into positive opinions, neutral opinions, and negative opinions. Random Forest Classifier has high performance compared to other machine learning methods. But the Random Forest Classifier is weak in the level of accuracy and stability of data, so it requires a selection feature to increase its accuracy by applying Information Gain which can increase accuracy by optimizing data features. Measurement of accuracy and sentiment prediction is measured by confusion matrix and classification report. The results show that the application of Information Gain can improve accuracy with the highest accuracy obtained in experiment 1 of 0.00747, that is 0.94776 from 0.94029 with a precision value of 0.65, recall 0.43 and f1-score 0.47 and have a tendency to have a neutral opinion on public tweets about the Covid-19 vaccination on Twitter

COVID-19 Vaccination Sentiment Analysis on Twitter Using Random Forest and Information Gain Andi Nur Rachman; Husni Mubarok; Euis Nur Fitriani Dewi; Mitha Maharani
IJISTECH (International Journal of Information System and Technology) Vol 6, No 3 (2022): October
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v6i3.246

Covid-19 in Indonesia has increased from January 2021 unti February 2021 there were 1,217,468 people who were confirmed positive for the corona virus. As a result the increase in the number, the government has taken preventive measures, one of which is the distribution of vaccines or vaccinating the Indonesian people, which has been started since January 13,2021. The government’s covid-19 vaccination efforts had a broad influence on the community through social media (especially Twitter) which then led to pros and cons. Therefore, sentiment analysis is needed to predict the tendency of public opinion regarding the Covid-19 vaccination policy which is classified into positive opinions, neutral opinions, and negative opinions. Random Forest Classifier has high performance compared to other machine learning methods. But the Random Forest Classifier is weak in the level of accuracy and stability of data, so it requires a selection feature to increase its accuracy by applying Information Gain which can increase accuracy by optimizing data features. Measurement of accuracy and sentiment prediction is measured by confusion matrix and classification report. The results show that the application of Information Gain can improve accuracy with the highest accuracy obtained in experiment 1 of 0.00747, that is 0.94776 from 0.94029 with a precision value of 0.65, recall 0.43 and f1-score 0.47 and have a tendency to have a neutral opinion on public tweets about the Covid-19 vaccination on Twitter

Application of Point Tracking Technology in 360 Degree Panorama Virtual Tour Applications for Introduction to Siliwangi University Campus Muhammad Adi Khairul Anshary; Cecep Muhamad Sidik Ramdani; Euis Nur Fitriani Dewi; Andi Nur Rahman; Rezi Syahriszani
CESS (Journal of Computer Engineering, System and Science) Vol 8, No 1 (2023): January 2023
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v8i1.39363

Most of the campus area introduction media use brochures to provide information to prospective students. This media among teenagers is no longer attractive. Most prospective students prefer information through multimedia such as short videos. Due to the limited time of video media, very little content is provided so that delivery will be very less. The use of Virtual Tour 360 multimedia technology will help to provide clear information in the form of text and the application of Point tracking technology will make it easier for users to feel like they are in a campus environment. The methodology used in making this application is the Luther-Sutopo version of the Multimedia Development Life Cycle (MDLC). The 360 Degree Panorama Virtual Tour Application Introduction to the Siliwangi University Campus is expected to make it easier to convey information that can be easily accepted by users. This application can see a real environment simulation on the Siliwangi University campus by representing information in the form of 360° panoramic images making it easy to display information visually. The test results obtained from the alpha test of the application of Point tracking can make it easier for users to run the application and the beta test results that the application functions very well get a score of 83.75%.

Application of Virtual Assistant in Information System for Student Practicum Case Study Laboratory Informatics Department Siliwangi University Cecep Muhamad Sidik Ramdani; Andi Nur Rachman; Euis Nur Fitriani Dewi
CESS (Journal of Computer Engineering, System and Science) Vol 8, No 1 (2023): January 2023
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v8i1.39365

Practical activities are carried out in an orderly and timely manner and require systematic recording of activities. The implementation of practicum activities takes place in the Siliwangi University laboratory, to create conducive conditions for practicum activities, a system must be able to support academic success. Not only that, due to the COVID-19 pandemic, previous practicum lectures were held offline and campus policy required online learning. These problems can be overcome by building a logbook information system that can record and keep records of laboratory activities automatically. This information system was created using the Extreme Programming system development method. Starting from database design, system design with UML, system development with Visual Studio. NET 2021. This technology can be used by universities for practical activities at the Siliwangi University Laboratory. The application will remind students to complete each activity in each session by displaying notifications in each practicum schedule, rewards, announcements, and other information related to practicum activities. All activities must be recorded in the application. Based on the results of black box testing, the system can run according to the system test design that the response from each student to the application used is 75.68% which can be concluded that the application of virtual assistant is in the interesting category.

Comparative Sentiment Analysis of Delivery Service PT.POS Indonesia and J&T Express on Twitter Social Media Using The Support Verctor Machine Algorithm Euis Nur Fitriani Dewi; Aldy Putra Aldya; Andi Nur Rachman; Ara Ramdani
IJISTECH (International Journal of Information System and Technology) Vol 6, No 5 (2023): February
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v6i5.284

Based on a survey conducted by the Top Brand Award in the courier service category, the J&T Express company is in the highest position from 2018 to 2021 beating Pos Indonesia. Social media Twitter is a place often used by customers to submit complaints and opinions regarding the services of a company. The method used to determine the tendency of the views to contain positive or negative sentiments is sentiment analysis. Sentiment analysis will classify the polarity of the text in sentences or documents to determine whether the opinions expressed are positive or negative. This study uses the Support Vector Machine (SVM) algorithm. The results of the user tweet data used are as many as 1000 data with details of data 206 (20.6%) have positive sentiments and 794 (79.4%) have negative sentiments. In the Pos Indonesia tweet data, 110 positive sentiment data were obtained, while the positive sentiment data in the J&T Express tweet data was 96 data. This shows that the Pos Indonesia delivery service has better customer service than J&T Express. The highest level of accuracy using the SVM algorithm in classifying sentiment is 80.14% with a comparison of 70% training data and 30% test data with an average precision of 90%, an average recall of 51.74%, and an average f-measure of 47.80%.

Comparative Sentiment Analysis of Delivery Service PT.POS Indonesia and J&T Express on Twitter Social Media Using The Support Verctor Machine Algorithm Euis Nur Fitriani Dewi; Aldy Putra Aldya; Andi Nur Rachman; Ara Ramdani
IJISTECH (International Journal of Information System and Technology) Vol 6, No 5 (2023): February
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v6i5.284

Based on a survey conducted by the Top Brand Award in the courier service category, the J&T Express company is in the highest position from 2018 to 2021 beating Pos Indonesia. Social media Twitter is a place often used by customers to submit complaints and opinions regarding the services of a company. The method used to determine the tendency of the views to contain positive or negative sentiments is sentiment analysis. Sentiment analysis will classify the polarity of the text in sentences or documents to determine whether the opinions expressed are positive or negative. This study uses the Support Vector Machine (SVM) algorithm. The results of the user tweet data used are as many as 1000 data with details of data 206 (20.6%) have positive sentiments and 794 (79.4%) have negative sentiments. In the Pos Indonesia tweet data, 110 positive sentiment data were obtained, while the positive sentiment data in the J&T Express tweet data was 96 data. This shows that the Pos Indonesia delivery service has better customer service than J&T Express. The highest level of accuracy using the SVM algorithm in classifying sentiment is 80.14% with a comparison of 70% training data and 30% test data with an average precision of 90%, an average recall of 51.74%, and an average f-measure of 47.80%.

PELATIHAN BERKEBUN HIDROPONIK SEBAGAI UPAYA DALAM MENJAGA KETAHANAN PANGAN KELUARGA DI MASA PANDEMI Fera Sulastri; Visi Tinta Manik; Astri Srigustini; Euis Nur Fitriani Dewi
Jurnal Pendidikan dan Pengabdian Masyarakat Vol. 4 No. 1 (2021): Februari
Publisher : FKIP Universitas Mataram

Menjaga kestabilan ketahanan pangan selama Pandemi covid 19 perlu di upayakan oleh masyarakat. Keterbatasan lahan bukan menjadi kendala bagi masyarakat untuk tetap bisa produktif dalam menghasilkan pangan untuk kebutuhan pangan keluarga. Tim PKK sebagai garda terdepan dalam menjaga ketahanan keluarga perlu dibekali keterampilan dan pengetahuan untuk itu. Begitupun peserta PKH (Program Keluarga Harapan) perlu dibekali keterampilan untuk bisa mandiri dalam menyediakan kebutuhan pangan keluarga. Salah satu upaya untuk mewujudkan hal tersebut melalui pelatihan berkebun hidroponik. Selain bertujuan untuk menghasilkan berbagai jenis pangan seperti aneka sayuran juga sebagai alternatif dalam mengoptimalkan lahan yang sempit. Pelatihan dilakukan dengan beberapa tahapan, yaitu persiapan, pelaksanaan, dan evaluasi/ monitoring. Proses monitoring berjalan selama enam minggu dan panen dilakukan kurang lebih setelah 4 minggu pindah tanam.

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