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All Journal Jurnal Algoritma Jurnal Wawasan Ilmiah Jurnal Teknologi Informasi dan Ilmu Komputer JAIS (Journal of Applied Intelligent System) JOIN (Jurnal Online Informatika) Edu Komputika Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal ULTIMATICS Aiti: Jurnal Teknologi Informasi Jurnal Teknik Informatika (JUTIF) Teknika Journal of Community Development Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal PkM MIFTEK Jurnal Algoritma Engineering Science Letter IT-Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi
Asri Mulyani
Institut Teknologi Garut
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Nursing Public Health Social Sciences Other

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THE PREDICTION OF PPA AND KIP-KULIAH SCHOLARSHIP RECIPIENTS USING NAIVE BAYES ALGORITHM Asri Mulyani; Dede Kurniadi; Muhammad Rikza Nashrulloh; Indri Tri Julianto; Meta Regita
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.2022.3.4.297

Abstract

The aim of the research is was to predict the scholar recipient for Peningkatan Prestasi Akademik (PPA) and the Kartu Indonesia Pintar Kuliah (KIP-K). The prediction results of scholarship recipients will provide information in the form of the possibility of acceptance and non-acceptance of scholarship applicants. To achieve this goal, this study uses the Naive Bayes algorithm, where this algorithm predicts future opportunities based on past data by going through the stages of reading training data, then calculating the number of probabilities and classifying the values in the mean and probability table. The data analysis includes data collection, data processing, model implementation, and evaluation. The data needed for analysis needs to use data from the applicants for Academic Achievement Improvement (PPA) scholarship and the Indonesia Smart Education Card (KIP-K) scholarship. The data used for training data were 145 student data. The results of the study using the Naive Bayes algorithm have an accuracy of 80% for PPA scholarships and 91% for KIP-K scholarships.
Data Mining Algorithm Testing For SAND Metaverse Forecasting Indri Tri Julianto; Dede Kurniadi; Muhammad Rikza Nashrulloh; Asri Mulyani
Journal of Applied Intelligent System Vol 7, No 3 (2022): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v7i3.7155

Abstract

Metaverse is a technology that allows us to buy virtual land. In the future life in the real world can be duplicated into the Metaverse to increase efficiency, effectiveness, and a world without being limited by space and time. To buy land in the Metaverse, one can be done by using SAND. SAND is a crypto asset from a game called The Sandbox which functions as a transaction tool where in that game we can buy land and build it for various purposes just like we can store our Non-Fungible Tokens there. Metaverse is a digital business that will promise in the future because it offers easy and fast transactions. This study aims to compare the exact algorithm for making predictions about the SAND cryptocurrency used to buy Metaverse land. 7 algorithms are being compared, namely Deep Learning, Linear Regression, Neural Networks, Support Vector Machines, Generalized Linear Models, Gaussian Process, and K-Nearest Neighbors. The research method used is Knowledge Discovery in Databases. The research results show that the Support Vector Machines Algorithm has the most optimal Root Means Square Error value, root_mean_squared_error: 0.022 +/- 0.062 (micro average: 0.062 +/- 0.000). Based on this comparison, the Support Vector Machines Algorithm is suitable for predicting SAND Metaverse prices.
DATA MINING CLUSTERING FOOD EXPENDITURE IN INDONESIA Indri Tri Julianto; Dede Kurniadi; Muhammad Rikza Nashrulloh; Asri Mulyani
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 6 (2022): JUTIF Volume 3, Number 6, December 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.6.331

Abstract

The availability of food in a country is determined by a conducive climate. Prolonged droughts, floods, and natural disasters, especially for food crop production areas, will have an impact on the availability of natural disaster conditions faced by all countries including Indonesia is the Covid-19 pandemic, where this will affect food security in Indonesia. Data mining is the process of discovering the hidden meaning of a very large data set. The technique used in this study is Data Mining Clustering and the validity index used is Davies-Bouldin. This study aims to determine the Food Security Strategy in Indonesia through the Data Mining Clustering process based on food expenditure data and the Indonesian people's food expenditure per capita. The methodology used is Cross Industry Standard for Data Mining using the K-Means and K-Medoids Algorithm. The best cluster for the K-Means Algorithm is K=7 with a value of 0.341 and for the K-Medoids Algorithm, it is K=7 with a value of 0.362. This research produces the best algorithm, namely K-Means with a value of 0.341, which has a smaller value than K-Medoids with a value of 0.362. The results showed that the regional. cluster with the highest average expenditure on food was cluster 5 covering the DKI Jakarta area, while the cluster with the lowest expenditure was cluster 6 covering Central Java, East Nusa Tenggara, Southeast Sulawesi, Gorontalo, and West Sulawesi. In cluster 6, it is necessary to implement a strategy to increase food security by increasing production capacity and food reserves in each region.
PENGEMBANGAN APLIKASI INDIKATOR STRATEGIS GARUT BERBASIS ANDROID PADA BADAN PUSAT STATISTIK KABUPATEN GARUT Dede Kurniadi; Muhammad Abdul Yusup Hanifah; Indra Trisna Raharja; Asri Mulyani
IT Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Vol 1 No 2 (2022): IT-Explore Juni 2022
Publisher : Fakultas Teknologi Informasi, Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (672.022 KB) | DOI: 10.24246/itexplore.v1i2.2022.pp133-144

Abstract

Peranan Badan Pusat Statistik (BPS) adalah menyediakan kebutuhan data bagi pemerintah dan masyarakat. Data ini didapatkan dari sensus atau survei yang dilakukan sendiri dan juga dari departemen atau lembaga pemerintahan lainnya sebagai data sekunder. Data ini bisa dilihat dalam bentuk informasi di website resmi BPS, tetapi informasi yang disajikan belum lengkap karena terdapat data-data lain yang belum bisa di tampilkan khususnya untuk BPS Kabupaten Garut. BPS dibagi-bagi kedalam beberapa seksi untuk memenuhi tugas atau peranannya, dan yang menangani tugas diatas adalah seksi IPDS (Integrasi Pengolahan Diseminasi Statistik). Tujuan penelitian ini adalah merancang Aplikasi Indikator Strategis Garut Berbasis Android. Metode yang digunakan adalah Unified Approach dengan tahapannya yaitu Analisis, Desain, dan Kontruksi, sedangkan untuk pemodelannya menggunakan Unified Modelling Language. Penelitian ini menghasilkan sebuah perancangan aplikasi indikator strategis garut berbasis android yang diharapkan dapat digunakan dengan baik dan mampu membantu kinerja bidang IPDS menjadi lebih efektif dan efisien.
Sistem Informasi Geografis Pemetaan Tempat Oleh-Oleh di Kabupaten Garut Berbasis Android Asri Mulyani; Ade Sutedi; Gina Muhtari
Jurnal Algoritma Vol 20 No 1 (2023): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.20-1.1184

Abstract

Indonesia is a country that is rich in the diversity of characteristics of each region, as in the city of Garut which has regional souvenirs, one of which is dodol arrowroot, souvenirs made of leather and so on. However, currently tourists who want to buy souvenirs in Garut lack the information they get or the knowledge of tourists about the regional specialties they visit. Geographic information systems can help users find places of interest and also by mapping places where souvenirs are made to help users find information about several souvenir shops in the city of Garut. The methodology used is the Rational Unified Process which has four stages, namely Inception, Elaboration, Construction, and transition. This system is built using the React Native framework and using the JavaScript programming language. The result of this research is to create a Geographic Information System for mapping souvenir places in Garut City based on Android, it is hoped that tourists can find it easy to find souvenir locations in Garut city.
Prediction System for Problem Students using k-Nearest Neighbor and Strength and Difficulties Questionnaire Dede Kurniadi; Asri Mulyani; Inda Muliana
JOIN (Jurnal Online Informatika) Vol 6 No 1 (2021)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v6i1.701

Abstract

The student counseling process is the spearhead of character development proclaimed by the government through education regulation number 20 of 2018 concerning strengthening character education. Counseling at the secondary school level carries out to attend to these problems that might resolve with a decision support system. So that makes research challenging to measure completion on target because it is not doing based on data. The counseling teacher does not know about student's mental and emotional health conditions, so it is often wrong to handle them. Therefore, we need a system that can recognize conditions and provide recommendations for managing problems and predicting students who have potential issues. The Algorithm used to predict problem students is K-Nearest Neighbor with a dataset of 100 students. The stages of predictive calculation are data collection, data cleaning, simulation, and accuracy evaluation. Meanwhile, building the system is done using the rapid application development methodology where the instrument used to map the student's condition is the Strenght and Difficulties Questionaire instrument. This research is a system to predict problem students with an accuracy rate of 83%. The level of user experience based on the User Experience Questionnaire (UEQ) results in the conclusion that the system reaches "Above Average.". This system is expecting to help counseling teachers implement an early warning system, help students know learning modalities, and help parents recognize the child's personality better.
Implementasi Metode Forward Chaining Pada Sistem Pakar Diagnosis Keperawatan Penyakit Stroke Infark Dede Kurniadi; Asri Mulyani; Sri Rahayu
AITI Vol 17 No 2 (2020)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v17i2.104-117

Abstract

Pasien yang telah di diagnosa secara medis yaitu stroke infark dan menjalankan perawatan di rumah sakit mungkin akan meninggalkan gangguan dari dampak penyakit stroke infark. Salah satu gangguan yang muncul pada penderita stroke infrak yaitu hambatan mobilitas fisik. Adapun peerawatan yang dapat dilakukan untuk pasien stroke infark dengan gangguan hambatan mobilitas fisik diantaranya degan latihan mobilisasi dan melakukan Range of Motion aktif. Perawatan ini sangat efektif untuk mencegah terjadinya ke kakuan pada otot-otot. Tujuan dari penelitian ini adalah mengembangkan aplikasi sistem pakar untuk membantu pasien stroke infark dalam mengetahui gangguan yang mungkin muncul setelah keluar dari rumah sakit. Metode penarikan kesimpulan mengggunakan Forward Chaining dan untuk pengembangan sistem dengan pendekatan Expert System Development Life Cycle. Kami menguji 10 sample berdasarkan hasil diagnosis perawat sesungguhnya dengan hasil diagnosa sistem pakar yang dibuat. Hasil dari perbandingan pengujian hasil diagnosis sistem menunjukan tingkat akurasi 90 persen sehingga sistem pakar yang dibuat layak untuk digunakan.
Sistem Deteksi Penyakit Covid-19 Berdasarkan Gejala Awal Menggunakan Algoritma Naive Bayes Berbasis Android Dede Kurniadi; Asri Mulyani; Diar Nur Rizky
Teknika Vol 12 No 3 (2023): November 2023
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v12i3.678

Abstract

Data penelitian terakhir menunjukkan bahwa masyarakat merasa takut untuk melakukan pemeriksaan ke instansi kesehatan akibat kurangnya pengetahuan Covid-19, sehingga menyebabkan ketidak pedulian dalam aktivitas sehari-hari terhadap dampak dari situasi penyakit Covid-19. Oleh karena itu dibutuhkan sebuah aplikasi sistem deteksi gejala awal penyakit Covid-19 berbasis mobile. Tujuan dari penelitian ini membuat aplikasi sistem deteksi penyakit Covid-19 dengan menerapkan metode pengklasifikasian Naive Bayes sehingga mempermudah pengguna dalam melakukan tes mandiri gejala awal Covid-19. Metode perancangan yang digunakan adalah Extreme Programming (XP) yang terdiri dari planning, analysis, design, implementation, dan maintenance. Data yang digunakan terdiri dari 2 dataset yaitu dataset untuk pengklasifikasian penyakit Covid-19 dengan jumlah data sebanyak 44.453 dan dataset untuk pengklasifikasian varian Covid-19 berjumlah 128.769. Penelitian ini melakukan 2 kali pemodelan menggunakan Split Data dengan perbandingan 5:5 untuk klasifikasi penyakit Covid-19 dan perbandingan 3:7 untuk klasifikasi varian Covid-19. Hasil penelitian ini berhasil membangun Sistem deteksi penyakit Covid-19 berdasarkan gejala awal menggunakan algoritma Naive Bayes berbasis android dan telah mampu memprediksi penyakit Covid-19 ke dalam 4 class dengan nilai F1-Score yaitu Allergy 0,98, Cold 0,61, Covid 0,56, dan Flu 0,95, serta gejala yang paling berpengaruh pada class Allergy yaitu CS13 (Loss of taste) dengan nilai 0,50, class Cold yaitu CS3 (Tiredness) dengan nilai 0,52, class Covid yaitu CS12 (Difficulty breathing) dengan nilai 0,51, dan class Flu yaitu CS19 (Sneezing) dengan nilai 0,53, sistem yang dibangun juga mampu memprediksi varian Covid-19 ke dalam 3 class dengan nilai F1-Score yaitu alpha 0,85, delta 0,78, dan omicron 0,93, serta gejala yang paling berpengaruh pada class Alpha yaitu VS3 (Loss of appetite) dengan nilai 0,74, class Delta yaitu VS12 (Cough) dengan nilai 0,87, dan class Omicron yaitu VS10 (Sore throat) dengan nilai 0,67, juga aplikasi berhasil dan dapat dirancang dengan pendekatan Extreme Programming (XP).
Penerapan Metode Certainty Factor pada Sistem Pakar Diagnosis Penyakit Difteri Berbasis Web Asri Mulyani; Dede Kurniadi; Sri Intan Multajam
Teknika Vol 12 No 3 (2023): November 2023
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v12i3.686

Abstract

Difteri adalah penyakit menular dan mematikan, penyakit ini dilaporkan oleh Dinas Kesehatan Jawa Barat kembali merebak akibat penanganan yang lambat. Jauhnya fasilitas layanan kesehatan dan keterbatasan jumlah dokter menjadi permasalahan. Tujuan dari penelitian ini adalah merancang dan membangun sistem pakar yang mampu melakukan diagnosis awal penyakit difteri melalui penerapan metode certainty factor. Aplikasi ini dirancang dalam bentuk web dengan mengikuti proses pengembangan aplikasi ESDLC (Expert System Development Life Cycle). Hasil dari penelitian ini adalah sebuah aplikasi sistem pakar berbasis web untuk mendiagnosis penyakit difteri dengan basis pengetahuan terdiri dari 12 gejala penyakit. Sistem pakar diagnosis penyakit difteri ini telah melalui proses uji coba menggunakan metode blackbox testing, hasilnya menunjukkan semua fitur dalam aplikasi yang sudah dibuat dapat beroperasi dengan baik. Selain itu, tingkat akurasi dari sistem pakar ini sebesar 90% berdasarkan akurasi yang telah dilakukan terhadap 10 data uji. Hasil tersebut menunjukkan bahwa diagnosis yang dihasilkan dari sistem pakar mempunyai hasil yang sejalan dengan diagnosis pakar.
Implementing Scrum in Executive Information System at University Setiawan, Ridwan; Mulyani, Asri; Fitriani, Pipit; Gusti, Kharisma Wiati
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 1 (2024): Articles Research Volume 8 Issue 1, January 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.13074

Abstract

Executive Information System is a type of system that provides information about reports generated by the system, assists executives in making necessary decisions, and provides easy access to information from both internal and external sources. This system aims to help specific organizations solve problems. The objective of this research is to design and develop a web-based executive information system that can provide access to student, faculty, and program data at the Faculty of Economics, Garut University, with data visualization in the form of graphs and numbers using the Scrum method. The Executive Information System can provide a real-time overview of data for executive-level individuals, namely the faculty leaders. Scrum is the development methodology used, with stages such as product backlog, sprint, daily scrum meeting, sprint review, and sprint retrospective. The results of this research have produced an Executive Information System that provides data on students, faculty, and programs. This system features functions such as filtering, drilldown, and importing. Testing results indicate the successful achievement of sprints on time or even ahead of schedule, and the team was able to meet targets in each sprint. In this research, the Scrum method has been effectively utilized in creating the executive information system. Therefore, this method can be employed to develop similar executive information systems in the future.
Co-Authors AA Sudharmawan, AA Abania, Nia Abdurrohman, Muhammad Akmal Ade Sutedi Ade Sutedi, Ade Aditya Permana Aditya Permana Agung Gumelar Agus Hermawan Ahmad Badar Muttaqin, Dadan Ahmad Budiman Ahzam, Faiq Muhammad Ai Karlina Ainun, Taanafa Nurul Akbar, Fazri Haikal Alamsyah, Fathi Ridwan Aldiansah, Aldiansah Alfiansyah, Dandan Alhakim, Much Kahfi Amrulloh, Muhammad Fawaz Andarista, Hilda Dian Anggi Wandani Annisa Atmanati Ansori, Hasbi Hamdan Al Ardimansyah, Dendi Arifin, Pipin Zaenal Asep Deddy Supriatna Asri Indah Pertiwi Astri Yuliastri Asyah, Cha Cha Nisya Aulia, Husni Aulia, Wafa Gaida Ayu Latifah Balilo Jr, Benedicto B. Banowati, Rika Burdani, Aditya Mauludin Burhanuddin, Ridwan Choerunisa, Alma Deddy Supriatna, Asep Dede Kurniadi Deni Heryanto Dewi Tresnawati Dhea Arynie Noor Annisa Diar Nur Rizky Diazki, Moch. Haiqal Dini Destiani Siti Fatimah Dudy Mohammad Arifin Ependi, Nasep Eri Satria Erick Fernando B311087192 Erwin Gunadhi Erwin Gunadhi Rahayu, Raden Evita Prananda Dewi Fadiel Muhammad Fadillah, Hadi Bagus Fahmi Ilham Ardiansyah Fahru Nisa Aulia Faisal Nurur Ramadhan Faisal, Ridwan Nur Fathon, Ahmad Fatimah, Raden Dini Destiani Siti Faturrohman, Nadhif Fauzan, Muhammad Farhan Fauzi, Rizky Ahmad Fauziyah, Asyifa Febrianti, Tiara Fikri Fahru Roji Firdaus, Raden Syaban Firmansyah, Marshal Fitri Nuraeni FITRIANI, PIPIT Gina Muhtari Gugum Gumilar Setia Permana Gustiawan, Restu Fajar Halim, Muhammad Aufa Fauza Haolilah, Siti Hilmi Aulawi Homsatin, Asyifa Azsma Iis Oktaviani Ikbal Lukmanul Hakim Inda Muliana Indra Trisna Raharja Indrakusumah, Muhamamad Rafi Indri Tri Julianto Irfanov, Muhammad Irpan Ahmad Fauzi Ismaya, Karina Jajang Romansyah JAMALUDIN Jamiludin, Irfan Janatunnisa, Raisya Agni Juliansyah, Fauzan Romi Kamal, Chaerul Syah Al Karlina, Ai Khaifa, Raisha Sarah Kharisma Wiati Gusti Khoiriyyah, Fakhrun Mahda Kurniawan, Ihsan Hafiiz Latif, A. Abdul Latifah, Ayu Leni Fitriani, Leni Lufti Lukmanurkarim Lukmanurkarim, Lufti M Rafiq Syahputa M. Mesa Fauzi Mahendra Akbar Musadad Maulud, Restu Bagja Meta Regita Mubarok, Ilham Muhamad, Zaki Muhammad Abdul Yusup Hanifah Muhammad Rikza Nashrulloh Muharam, Muhamad Riyan Muhtari, Gina Muliana, Inda Mustaatinah, Tutin Nasrullah, Muhammad Rikza Nita Novianti Firmansyah Nugraha, Aldi Nugraha, Praja Salya Nugroho, Salmanudin Nuraisah, Tintin Nurazizah, Neng Putri Nurhaliza, Nabila Putri Nurhidayanti, Shopi Nurmahmudi, Raihan Nurpajar, Dini Siti Nurrifan Syabandhi Nursaidah, Syifa Nursofiana, Muhammad Fauzan Nursyaban, Dzikri Nurul Fauziah Nurusyam, Moh Algifari Oktavian, Gilang Anhari Oktavian, Muhamad Ar Rasyid Rizki Oktavian, Zordan Oktaviani, Iis Padilah, Eva Nurul Pasundan, Gia Aghista Prayoga, Hardi Putri, Elsinta Ismawati Putri, Mita Hidayani Qalam Ilmayasa, Muhammad Raharja, Indra Trisna Rahayu, Maulida Fasha Rahayu, Yari Ardiansyah Rahmat, Agil Rahmawan, Muhammad Kahfi Rais, Azfa Muhammad Ramdan, Galih Muhammad Ramdani Setiawan Ramdani, Dikri Ramdani, Idham Ramdhani, Nabila Aprilia Rangga, Wisnu Ranti Rahayu Pujianti Renaldy Alamsyah Rengganis, Nadia Fauziah Revi Rexi Muhamad Fadilah Ridwan Setiawan Ridwan Setiawan Rifky Muhammad Shidiq Rima Ardianti Rinda Cahyana Riyad Sabilul Muminin Rizal Mulyana Rizki, Riyandi Muhamad Rizky Helmi Romadan, Mochamad Rizki Rosita Wulandari Rostilawati, Detila Ruli Ahmad Rusmana Ruspa, Rena Saadah, Roro Saepul Rochman Sahdan Hadianto Salsabila, Kailla Sambas, Keisha Aulia Saparudin, Hopid Saputri, Amellia Sarah Khoerunisa Saripudin Saripudin Setiawan, Ahmad Dandi Sidik, Muhammad Luthfi Farid Sinta Nurfatonah Siti Rima Fauziyah Slamet, Bagus Solahudin, Muhammad Husni Sopandi, Pendi Sopian, Alpi Sri Intan Multajam Sri Rahayu SRI RAHAYU Sugriantha, Irham Sukirno Sukirno Sukmawan, Tegar Sulaeman, Gilman Fajar Suwandy, Mochamad Riefky Rafliana Syabandhi, Nurrifan Tania Agusviani Wahidah Taupik Hidayat, Taupik Wahdaniah, Hamidah Nur Yana Nuryana Yoga Handoko Agustin Yosep Septiana Yuliastri, Astri Yundari, Yundari Yuni Yuliani Yusuf, Nadhif Murtadho Zaelani, Jaka Muhammad Zahra, Lubna Nur Zulkarnaen, Ade Iskandar