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All Journal Jupiter Techno.Com: Jurnal Teknologi Informasi Jurnal Simetris Jurnal sistem informasi, Teknologi informasi dan komputer Jurnal Ilmiah KOMPUTASI Jurnal Riset Informatika Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Community Development Journal: Jurnal Pengabdian Masyarakat Infotech: Journal of Technology Information Jurnal Teknik Informatika (JUTIF) Journal of Business and Audit Information System (JBASE) KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Abdi Masyarakat Indonesia Jurnal Inovasi Pengabdian dan Pemberdayaan Masyarakat Jurnal Sistem Informasi dan Manajemen The Indonesian Journal of Computer Science Jurnal Media Digital
Ade Davy Wiranata
Universitas Muhammadiyah Prof. Dr. HAMKA Jakarta, Indonesia
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Library & Information Science Mathematics Public Health Social Sciences

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Perbandingan Algoritma Naïve Bayes, KNN, dan Decision Tree terhadap Ulasan Aplikasi Threads dan Twitter Muhammad Iqbal; Ade Davy Wiranata; Rayhan Suwito; Ridha Faiz Ananda
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 3 (2023): Desember 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i3.1402

Abstract

Social media is a socializing activity through the internet, which has many conveniences that allow people to communicate and access information quickly. Social media is widely used to get news that is difficult to get. Social media applications are quite popular such as Twitter and recently social media that has similar features, namely Threads. Therefore, the purpose of this study is to compare 3 algorithmic methods of user-generated reviews on two applications, namely Twitter and Threads. We used 899 reviews on Twitter, with 245 positive sentiments and 654 negative sentiments, and 638 reviews on Threads, with 220 positive sentiments and 418 negative sentiments. Cleansing, preprocessing, and modeling are the steps that will be passed to process the data. In this study, split data and cross validation models were used, and the three algorithms used were Naïve Bayes, Decision Tree, and KNN, with a ratio of 80:20 for training data and test data. The accuracy value obtained for Naïve Bayes is 85.56%, Decision Tree is 72.78%, and KNN on the Twitter application, while the threads application gets 66.41% for Naïve Bayes, Decision Tree gets 65.41%, and the threads application gets 66.41%. In the Naïve Bayes algorithm, precision, recall are calculated in the Threads and Twitter applications. The Threads application gets 64.86% in precision and 73.85% in recall, while the Twitter application gets 84.69% in precision and 88.30% in recall.
Pengembangan Aplikasi Try Out Berbasis Web untuk Lembaga Kursus dan Pelatihan Sutrisno, Mirza; Wiranata, Ade Davy; Irawan, Dede
Jurnal Sistem Informasi, Teknologi Informatika dan Komputer Volume 14 No 3, Mei Tahun 2024
Publisher : Universitas Muhammadiyah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24853/justit.14.3.188-193

Abstract

Pengamatan langsung dilakukan terhadap proses pelaksanaan tes uji coba (try out) serta penilaian siswa dan pembahasan materi try out di Lembaga Kursus dan Pelatihan (LKP). Aplikasi ini dirancang untuk mempersiapkan siswa menghadapi Asesmen Nasional Berbasis Komputer (ANBK) di tingkat SMP dan SMA. Meskipun demikian, dalam pelaksanaannya, masih terdapat kendala seperti proses pengerjaan, pendistribusian soal dan lembar jawaban, serta pengkoreksian dan penilaian yang memerlukan waktu karena banyaknya peserta tes uji coba. Aplikasi dirancang menggunakan permodelan Unified Modelling Language (UML) dengan metode pengembangan sistem menggunakan waterfall yang selanjutnya diuji dengan metode black box testing. Diharapkan dengan adanya aplikasi try out bagi Lembaga Kursus dan Pelatihan ini, proses pelaksanaan try out dapat lebih efisien dan meningkatkan citra Lembaga Kursus dan Pelatihan.Kata Kunci : Aplikasi Try Out, Lembaga Kursus, Waterfall, Blackbox Testing
LITERATURE REVIEW : ANALISIS METODOLOGI PERANCANGAN APLIKASI TOEFL (TEST OF ENGLISH AS A FOREIGN LANGUAGE) DI INDONESIA Sutrisno, Mirza; Wiranata, Ade Davy; Irawan, Dede
Jurnal Sistem Informasi, Teknologi Informatika dan Komputer Volume 13 No 2, Januari Tahun 2023
Publisher : Universitas Muhammadiyah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24853/justit.13.2.92-99

Abstract

English Proficiency Index (EPI) atau Indeks Kecakapan Bahasa Inggris tahun 2022 menunjukkan bahwa secara Global, Indonesia berada pada posisi ke-81 dari 111 negara, dan dalam kategori rendah. TOEFL (Test of English as a Foreign Language) adalah salah satu tes kecakapan berbahasa Inggris untuk non-English native speaker. Tes TOEFL diperlukan baik untuk keperluan akademik maupun profesional, serta untuk hal-hal umum lainnya. Seiring dengan perkembangan di bidang Information Technology (IT),  maka banyak muncul aplikasi TOEFL yang dapat membantu penggunanya. Tujuan  studi ini adalah melakukan kajian literature terhadap penelitian tentang penggunaan model metodologi dalam perancangan aplikasi TOEFL. Metode  penyusunan artikel ini didasarkan pada metode kajian literatur. Studi ini mengidentifikasi berbagai metodologi yang digunakan dalam merancang aplikasi TOEFL. Hasil kajian menunjukkan bahwa metode waterfall menjadi yang paling umum digunakan. Sedangkan pengujian sistem paling banyak dilakukan menggunakan metode Black-Box Testing. Tinjauan ini memberikan gambaran tentang jumlah artikel yang diterbitkan tentang desain aplikasi TOEFL di Indonesia dan metode yang digunakan dalam setiap penelitian. Diharapkan dengan adanya literature review ini dapat membantu penulis lain dalam mencari literatur atau referensi mengenai analisis metodologi dalam perancangan aplikasi TOEFL.Kata Kunci: Aplikasi TOEFL, Blackbox Testing, Kajian Literatur, Waterfall
PERANCANGAN SISTEM INFORMASI PENDAFTARAN DAN SELEKSI PESERTA MERDEKA BELAJAR KAMPUS MERDEKA (MBKM) BERBASIS WEBSITE Erizal, Erizal; Hamimuddin, Moch; Mutiarawa, Rezza Anugrah; Wiranata, Ade Davy
JURSIMA Vol 12 No 1 (2024): Volume 12 Nomor 1 2024
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v12i2.867

Abstract

Program Mardeka Belajar Kampus Mardeka (MBKM) menawarkan peluang bagi mahasiswa untuk belajar di luar program studinya, yang dapat memperkaya pengalaman dan mempersiapkan mereka untuk dunia kerja. Namun, dalam tiga tahun pelaksanaannya di FTII UHAMKA, ditemukan kendala berupa ketiadaan sistem yang memadai untuk pendaftaran dan seleksi peserta. Hal ini menyebabkan dokumentasi dan proses seleksi peserta menjadi tidak optimal. Penelitian ini bertujuan mengembangkan sistem informasi manajemen berbasis web untuk mengelola MBKM menggunakan metode agile development. Sistem informasi manajemen yang dibuat dapat mempermudah mahasiswa mendaftar program MBKM. Setelah dilakukan pengujian menggunakan blackbox testing, Sistem yang dibuat berjalan dengan baik dan bisa digunakan untuk mempermudah koordinator MBKM atau kaprodi dalam mengelola data mahasiswa yang mengikuti program MBKM. Hasil yang didapat dari pengujian blackbox testing yaitu 90% valid semua fitur dapat berjalan dengan baik.
PEMILIHAN DOSEN PEMBIMBING SKRIPSI TERBAIK MENGGUNAKAN METODE COMPOSITE PERFORMANCE INDEX (CPI) Muryono, Tupan Tri; Wiranata, Ade Davy; Sudaryana, I Ketut; Irwansyah, Irwansyah
Infotech: Journal of Technology Information Vol 8, No 1 (2022): JUNI
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v8i1.132

Abstract

Lecturers are professional educators and scientists with the main task of transforming, developing, and disseminating science, technology, and art through education, research, and community service. The problem in this research is that the process of selecting the best thesis lecturer is still subjective without considering the criteria and weighting factors and is also done manually resulting in the selection process being less effective and efficient. The method used in this research is the Composite Performance Index (CPI). Methods of data collection techniques by means of observation, interviews, documentation. From this research, the result is that the CPI method can help in selecting the best thesis supervisor and also the first rank is A6 with a value of 500, the second rank is A4 with a value of 470, and the third rank is A2 with a value of 445.
KOMPARASI ALGORITMA DECISION TREE, NAIVE BAYES DAN K-NEAREST NEIGHBOR UNTUK MENENTUKAN KUALITAS UDARA DI PROVINSI DKI JAKARTA Irwansyah, Irwansyah; Wiranata, Ade Davy; M, Tupan Tri
Infotech: Journal of Technology Information Vol 9, No 2 (2023): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v9i2.203

Abstract

Air quality in DKI Jakarta Province refers to the state and cleanliness of the air in the area at a given time. The type and concentration of air pollutants are among the indicators used to assess air quality. DKI Jakarta's air pollution is severe, causing respiratory irritation, respiratory illnesses, and long-term health issues such as cardiovascular disease and lung cancer. Air pollution can also harm the environment by limiting visibility and harming ecosystems. The problem with the research is that no appropriate and relevant features for predicting air quality were used. The goal of this study is to identify and compare algorithms with the highest accuracy between decision trees. In determining air quality, naive Bayes and k-nearest neighbor are used. According to the findings of the K-5fold evaluation process performed with the RapidMiner tool, the accuracy of the Decision Tree algorithm was 95.89%, the accuracy of the Nave Bayes algorithm was 93.15%, and the accuracy of the K-NN algorithm was 91.78%. Based on these findings, the decision tree method has the greatest or best accuracy when compared to the Nave Bayes and K-NN algorithms.
SISTEM PAKAR DETEKSI KERUSAKAN JARINGAN LOCAL AREA NETWORK (LAN) MENGGUNAKAN METODE BECKWARD CHAINING BERBASIS WEB Irwansyah, Irwansyah; Wiranata, Ade Davy; Muryono, Tupan Tri; Budiyantara, Agus
Infotech: Journal of Technology Information Vol 8, No 2 (2022): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v8i2.150

Abstract

The form of computer network connection can be via cable or wireless such as fiber optic, microwave, wireless, or satellite. One type of computer network that is often used to connect personal computers and workstations in an office or an organization, company or factory for the use of shared resources is a local area network. The purpose of this research is to analyze, design and create an application that can detect damage to Local Area Network (LAN) networks. The research method used is backward chaining. The results of this study are applications that can detect damage to local area networks using the web-based backward chaining method. With this expert system application, it can speed up and make it easier to detect damage to Local Area Network networks.
KLASIFIKASI DATA MINING UNTUK MENENTUKAN KUALITAS UDARA DI PROVINSI DKI JAKARTA MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBORS (K-NN) Wiranata, Ade Davy; Soleman, Soleman; Irwansyah, Irwansyah; Sudaryana, I Ketut; Rizal, Rizal
Infotech: Journal of Technology Information Vol 9, No 1 (2023): JUNI
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v9i1.164

Abstract

Air plays an important role in maintaining the life of living things on earth. Metabolic processes that occur in the bodies of living things cannot take place without oxygen from the air. The air pollution problem in DKI Jakarta is very serious and can cause health problems such as irritation of the respiratory tract, respiratory diseases, and long-term health problems such as cardiovascular disease and lung cancer. Air pollution can also affect environmental quality, reduce visibility, and damage ecosystems. The purpose of this study is to determine the accuracy of classifying air quality in DKI Jakarta province. The data mining method that the author uses is the K-Nearest Neighbors (K-NN) algorithm. From the results of the evaluation process of the K-Nearest Neighbors (K-NN) algorithm using the K-5 fold that has been carried out using the RapidMiner tool, the results of K-2 fold accuracy of 73.97%, K-3 fold accuracy of 72.60%, K-4 fold accuracy of 72.60%, and K-5 fold accuracy of 75.35%.
Implementasi Business Intelligence Menggunakan Tableau Untuk Visualisasi Data Dampak Judi Online Di Indonesia Baktiar, Muhammad Yusuf; Ade Davy Wiranata
Jurnal Ilmiah Komputasi Vol. 23 No. 2 (2024): Jurnal Ilmiah Komputasi : Vol. 23 No 2, Juni 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32409/jikstik.23.2.3609

Abstract

Kasus judi online di Indonesia yang semakin meningkat seiring dengan perkembangan teknologi dan penggunaan internet. Perkembangan teknologi seluler dan internet telah memberikan kemudahan komunikasi, namun juga membuka peluang bagi aktivitas negatif seperti judi online. Judi online menyebabkan masalah sosial, kesehatan mental, dan ekonomi, termasuk perselisihan rumah tangga, pencurian, dan kriminalitas. Penelitian ini menggunakan metode Business Intelligence (BI) dengan platform Tableau untuk memproses data sekunder dari situs Kaggle. Data tersebut kemudian divisualisasikan untuk mendukung proses pengambilan keputusan terkait penanganan kasus judi online. Hasil penelitian menunjukkan bahwa provinsi Jawa Barat memiliki jumlah kasus judi online tertinggi dengan 265.800.000 kasus pada tahun 2023, sementara jumlah pengguna terendah berada di DKI Jakarta dengan 130 akun. Keseluruhan pengguna judi online di Indonesia mencapai 5.372 akun, dengan total 740.160.000 kasus pada tahun 2023. Visualisasi data dalam bentuk berbagai grafik dan dashboard di Tableau membantu menyampaikan pemahaman dan perbandingan mengenai fenomena judi online kepada masyarakat. Dengan analisis ini, diharapkan berbagai pihak dapat lebih mudah memahami dan mengambil langkah untuk mengatasi masalah judi online yang semakin marak.
Analisis Sentimen Terhadap Rangka E-SAF Honda Pada Media Sosial X Dengan Algoritma Naïve Bayes Cleary Syafi'i, Akbar; Ade Davy Wiranata
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 5 No. 1 (2024): Agustus 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v5i1.1993

Abstract

Motorcycles are the best vehicles for traveling when traffic is heavy because motorcycles allow people to save time while going about their daily commute due to their small size and ability to move on narrow streets. An important component in a motorcycle is the motorcycle frame, the motorcycle frame is a useful part to support the weight of these components in the motorcycle vehicle system. However, it is rumored that a motorcycle frame with the E-SAF type has poor quality, so a sentiment analysis is needed. This research aims to collect the number of comments, both positive and negative, from social media users X about the E-SAF framework, and also to determine the accuracy of the application of the Naive Bayes method. The datasets collected from social media X amounted to 756 datasets. Then after going through the stages of data cleaning such as cleansing, tokenize, and stopword filters, the data that can be used for this research amounted to 696 datasets. The next stage is data labeling, namely by dividing the dataset with a ratio of 60:40, namely 60% of the training data totaling 417 datasets that have been manually labeled with the results of 224 negatively charged data, 193 positively charged data while the test data is 40% with a total of 279 datasets which will later be automatically labeled with the implementation of the Naive Bayes method. The next stage is that the test data goes through the data processing stage so that the test data is ready to be implemented into the Naive Bayes method. After implementing the Naive Bayes method, the accuracy obtained was 70.27% with a precision of 76% and also a recall of 79.17%. There was also a true Positive data of 57 and a true Negative data of 21. Data Visualization also displays words that appear frequently in the dataset. Here it shows that the Naive Bayes method is quite effective for the classification of sentiment analysis
Co-Authors Al-Tain, Qolibu Rozak Aldisa, Rima Tamara Asruddin Asrul Sani Azhar, Nur Chalik Baktiar, Muhammad Yusuf Budiyantara, Agus Candra, Ariya Pannadhitthana Catur Nugroho Cleary Syafi'i, Akbar Dede Irawan Deni Mahdiana Deni Mahdiiana Dewanto, Yogga Tolly Dzikrillah, Ahmad Rizal Elvinaadellia, Elvinaadellia Erik, Muhammad Erizal Erizal Fadhilah, Ash Shoffi Hana Fakhriyyah , Alma Nisa Firmansyah, Firadaus Fitria Nur Hasanah Gunadi, Reza Haderiansyah Haderiansyah Haderiansyah Haderiansyah Hamimuddin, Moch I Ketut Sudaryana, I Ketut Imam Riadi Irwansyah Irwansyah Irwansyah Irwansyah Iswahyudi Iswahyudi Jazuli, Umar Jefri Kusuma Rambe M, Tupan Tri MA'MUN, AKHMAD HAQIQI Makmun, Akhmad Haqiqi Maulana, Ninda Baitza Meitiyani, Meitiyani Miftahuddin Miftahuddin Mirza Sutrisno Muhammad Efrizal Febriyan Muhammad Iqbal Mukhtar, Ahmad Amirrudin Murniasih, Intan Muryono, Tupan Tri Mutiarawan, Rezza Anugrah Nunik Pratiwi Rabbani, Abrar Dyah Rachman, Hafid Sulistyo Rafie Rafie Rahardjo, Rafi Diandra Dani Rayhan Suwito Rezza Anugrah Mutiarawan Ridha Faiz Ananda Rima Tamara Aldisa Rima Tamara Aldisa Riza Alamsyah Rizal Rizal Rosalina Rosalina Saifudin, Yazid Sinduningrum, Estu Soleman, Soleman Sulaeman, Mia Kamayani Sulistiawati Sulistiawati Sunardi Sunardi Sutrisno, Mirza Syakura, Rais Abdan Widodo, Muhammad Adnan