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IMPLEMENTASI ALGORITMA APRIORI UNTUK ANALISA PEMILIHAN TIPE GENRE FILM ANIME (STUDI KASUS : MYANIMELIST.NET) Mochammad Abdul Azis; Nur Hadianto; Jaja Miharja; Saifulloh Rifai
Jurnal Pilar Nusa Mandiri Vol 14 No 2 (2018): PILAR Periode September 2018
Publisher : LPPM Universitas Nusa Mandiri

As with Japanese animated films or can also be called an anime film which is now starting to be popular with all circles regardless of age, status and profession. In Japanese anime films, it has several genres from action, comedy, drama, romance, adventure, etc., can be accessed as in online media such as websites that offer various types of anime, one of which is myanimelist.net on this web having 14,000 anime films shared genre. One way to increase the appeal of anime films is to use the genre data that is often watched by anime movie lovers. With these data we foam analyze what types of genres are the most watched, as wellas the tendency to choose alternative genre types that are liked by anime movie lovers. So with these data the creator can determine the strategy for the type of genre that will be created next. a priori algorithm is good for use for itemset formation, pattern searching and so on. Therefore in this study the a priori algorithm was used to determine the pattern of selection of genre types in Japanese Anime Films.

PREDIKSI TINGKAT KELULUSAN NILAI MAHASISWA TERHADAP MATAKULIAH WEB PROGRAMMING MENGGUNKAN METODE NEURAL NETWORK Mochammad Abdul Azis; Agung Fazriansyah
Jurnal Pilar Nusa Mandiri Vol 15 No 2 (2019): PILAR Periode September 2019
Publisher : LPPM Universitas Nusa Mandiri

Penerapan teknologi informas dalan dunia pendidikan juga dapat menghasilkan data yang berlimpah mengenai data mahasiswa dan nilai pembelajaran yang dihasilkan. Seperti nilai matakuliah unggulan tersebut yang sangat mempengaruhi jumlah ipk dan kelulusan karna jika salah satu matakuliah unggulan seperti Web Programing tersebut mendapatkan nilai D maka mahasiswa tersebut tidak dapat melakukan pendaftaran Tugas akhir atau Skripsi. Salah satunya caranya adalah dengan melakukan klasifikasi daa nilai mahasiswa untuk mengetahui nilai matakuliah unggulan apa saja yang paling krusial dari semester pertama. Neural Network lebih flesksibel yaitu tidak ada batasan apriori yang dikenakan bila dibandingkan dengan pemodelan statistic klasik, sehingga Neural Network cenderung memberikan prediksi yang akurat.

Pelatihan Pembuatan Sistem Informasi Berbasis Website Pada Remaja Islam Masjid At-Taubah Jakarta Menuju SDM Unggul Ahmad Al Kaafi Kaafi; Leliyanah Leliyanah; Suparni Suparni; Mochammad Abdul Azis Azis
Abditeknika Jurnal Pengabdian Masyarakat Vol. 2 No. 1 (2022): April 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/abditeknika.v2i1.1131

Tujuan kegiatan Pengabdian Kepada Masayarakat ini adalah memberikan pengetahuan dan keterampilan mengenai pembuatan sistem informasi berbasis web. Website informasi merupakan media informasi yang dapat dimanfaatkan oleh masyarakat secara efektif dan efisien dalam penyampaian informasi-informasi yang berhubungan tentang kegiatan Masjid At-Taubah Jakarta. Kegiatan dilakukan secara tatap muka selama satu hari dengan tetap menerapkan protokol kesehatan dalam pencegahan Covid-19. Pelatihan ini lebih menitikberatkan pada kegiatan praktek dibandingkan dengan penjabaran materi. Pelaksanaan pelatihan secara hybird dengan menggunakan media conference dengan materi yang telah disusun sistematis. Hasil kegiatan pelatihan dapat menunjukkan bahwa peserta memiliki pemahaman yang meningkat terkait manfaat website sebagai sarana atau media informasi dan target luaran berupa publikasi di media elektronik. Kemampuan peserta terkait cara membuat dan mengelola website juga dapat mengalami peningkatan kemampuan menuju SDM unggul.

Klasifikasi Human Stress Menggunakan Adagrad Optimization untuk Arsitektur Deep Neural Network Mochammad Abdul Azis; Ahmad Fauzi; Ginabila Ginabila; Imam Nawawi
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 7 No. 1 : Tahun 2022
Publisher : LPPM UNIKA Santo Thomas

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

According to the World Health Organization, stress is a type of mental illness that affects human health and there is no one in this world who does not suffer from stress or depression. Stress is a term that is often used synonymously with negative life experiences or life events. . Analysis of data that has an unbalanced class results in inaccuracies in predicting human stress. This study shows that using the Deep Neural Network (DNN) Architecture model by optimizing several parameters, namely the optimizer, Learning rate and epoch. The best DNN Architect results are obtained with 4 Hidden Layers, Adagard Optimization, Learning rate 0.01 and the number of epochs 100. Accuracy, precision, recall and f-measure scores get 98.25%, 83.00%, 98.25%, 91.00%, respectively.

RANCANG BANGUN (SISTEM INFORMASI E-LEARNING BERBASIS WEB PADA SMK DAARUT TAUFIQ TANGERANG Eka Wulansari Fridayanthie; Mochammad Abdul Azis; Aliffah Kusumaningrum
Swabumi Vol 6, No 2 (2018): Volume 6 Nomor 2 Tahun 2018
Publisher : Universitas Bina Sarana Informatika Kota Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/swabumi.v6i2.4560

ABSTRAKSI Selama ini semua proses pembelajaran di SMK Daarut Taufiq Tangerang masih bersifat konveksional, dengan kata lain bahwa proses belajar mengajar antara siswa dengan guru hanya dapat dilakukan dengan syarat terjadinya pertemuan antara siswa dengan guru di dalam kelas. Jika pertemuan antara siswa dengan guru tidak terjadi atau guru yang bersangkutan tidak hadir dan waktu pembelajaran yang dibatasi pihak sekolah m maka secara otomatis proses pembelajaran pun akan terhambat. Untuk merancang aplikasi ini digunakan metode pererancangan struktural yaitu pembuatan Entity Relationship Diagram (ERD) dan pembuatan Logical Relationship Structure (LRS) untuk merancang dan mendokumentasikan sistem perangkat lunak berdasarkan aliran data. Dengan adanya e-learning ini dapat membantu proses belajar mengajaran agar lebih optimal. Memudahkan para guru untuk dapat mendistribusikan materi pelajaran untuk siswa/i di SMK Daarut Taufiq Tangerang dn juga siswa/i dapat dengan mudah mendapat materi pelajaran. Kata Kunci: SMK Daarut Taufiq Tangerang, E-learning ABSTRACT So far, all learning process in SMK Daarut Taufiq Tangerang is still convective, in other words, that the teaching and learning process between students and teachers can only be done on the condition of meeting between students with teachers in the classroom. If the meeting between students and teachers does not occur or the teacher is not present and the learning time is limited by the school m then automatically the learning process will be hampered. To design this application used structural design method that is making Entity Relationship Diagram (ERD) and making Logical Relationship Structure (LRS) to design and documenting software system based on data flow. With this e-learning can help the teaching-learning process to be more optimal. Facilitate the teachers to be able to distribute the subject matter for students in SMK Daarut Taufiq Tangerang in also students / I can easily get the subject matter. Keywords: SMK Daarut Taufiq Tangerang, E-learning

Analisis Prediksi Kelulusan Mahasiswa Menggunakan Decission Tree Berbasis Particle Swarm Optimization Hendra Hendra; Mochammad Abdul Azis; Suhardjono Suhardjono
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 9, No 1 (2020): MARET
Publisher : ISB Atma Luhur

Good accreditation results are the goal of the college. With good accreditation, prospective students can glance at and enter the tertiary institution. To achieve this, there are several aspects that affect good accreditation results, one of which is graduate students who play an important role in determining accreditation. Timely graduate students can benefit the college or a student. Graduates can be predicted before the final semester using a method one of which is the decision tree. Decision tree is a method that is simple and easy to understand by producing rules in the form of a decision tree, but using a decision tree model alone is not enough to produce optimal results. So we need a method for optimization that is particle swarm optimization with advantages can improve accuracy by eliminating unused features. From the results of research with primary data of 2000-2003 graduate students in Amik PPMI Tangerang explained that the particle swarm optimization method can increase accuracy by 87.56% and increase by 01.01% from the decision tree method with a value of 86.55%. From the particle swarm optimization method can also find out which unused attributes have no weight, so that way can improve accuracy. From the results of the increase, it can be used by the Amik University of Tangerang to prevent students from graduating on time.

Klasifikasi Human Stress Menggunakan Adagrad Optimization untuk Arsitektur Deep Neural Network Mochammad Abdul Azis; Ahmad Fauzi; Ginabila Ginabila; Imam Nawawi
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 7 No. 1 : Tahun 2022
Publisher : LPPM UNIKA Santo Thomas

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

According to the World Health Organization, stress is a type of mental illness that affects human health and there is no one in this world who does not suffer from stress or depression. Stress is a term that is often used synonymously with negative life experiences or life events. . Analysis of data that has an unbalanced class results in inaccuracies in predicting human stress. This study shows that using the Deep Neural Network (DNN) Architecture model by optimizing several parameters, namely the optimizer, Learning rate and epoch. The best DNN Architect results are obtained with 4 Hidden Layers, Adagard Optimization, Learning rate 0.01 and the number of epochs 100. Accuracy, precision, recall and f-measure scores get 98.25%, 83.00%, 98.25%, 91.00%, respectively.

ANALYSIS OF NEURAL NETWORK CLASSIFICATION ALGORITHM TO KNOW THE SUCCESS LEVEL OF IMMUNOTHERAPY Agung Fazriansyah; Mochammad Abdul Azis; Yudhistira Yudhistira
Techno Nusa Mandiri: Journal of Computing and Information Technology Vol 17 No 1 (2020): TECHNO Period of March 2020
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Cancer is a disease that is feared by humans at this stage, the genetic term of most diseases that have the characteristics of abnormal cell growth and beyond the normal cell limits so that they can attack cells that cover and are able to spread to other organs. For cancer recovery therapy is immunization therapy. Of course in this alternative treatment still needs to be done research to determine the level of success with existing conditions and parameters. Increasingly sophisticated, developing technology that helps human work. The neural network algorithm is used to analyze large datasets, the purpose of this study is to find the accuracy and immunotherapy methods of the dataset using a neural network learning machine with 200 data training cycles, 0.9 momentum and 0.01 learning levels that produce quite high accuracy 80 % and AUC value of 0.738

MOBILE-BASED ONLINE EXAM APPLICATIONS USING PROBLEM WEIGHT CLASSIFICATION TECHNIQUES, GROUPING AND RANDOMIZING Muhammad Iqbal; Abdul Hamid; Nuraeni Herlinawati; Mochammad Abdul Azis; Muhammad Rezki; Ali Mustopa
Techno Nusa Mandiri: Journal of Computing and Information Technology Vol 17 No 1 (2020): TECHNO Period of March 2020
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Education is an agenda for designing the country's development. Implementation in the field of education is a joint responsibility of both the government and the community, educational institutions are one that plays an important role in the ongoing learning process activities one of which is the examination activities. The test is an evaluation of the learning process to obtain learning outcomes as a form of achievement recognition or completion in an educational unit. The test is still cheating, it is triggered by the lack of confidence in working on the exam questions and the same type of exam questions will provide an opportunity to chat and work together. The author aims to provide a solution in the form of the application of online-based online test applications using question weight classification techniques, grouping and randomization. This mobile-based online exam application was developed using the waterfall model. The results obtained from research on this mobile-based exam application has features to prevent screen capture or screenshots, prevent video recording or video recorder and prevent switching applications that can run multiplatform on Android and iOS. This application has been through the process of testing the user and distributing questionnaires to determine the feasibility of using the weight classification technique with a percentage of 80% so it is suitable for use in examination activities.

Grouping of Covid-19 Affected Areas in Bogor City Using The K-Means Algorithm Zulia Imami Alfianti; Sugiono; Mochammad Abdul Azis; Ahmad Fauzi
Jurnal Mantik Vol. 4 No. 4 (2021): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.Vol4.2021.1142.pp2336-2341

Clustering plays an important role in processing big data, making predictions and overcoming anomalies in data, identical characteristics in data sets are grouped using iterative techniques. Because data is always evolving from day to day, very large data sets with little can be identified into interesting patterns by grouping, special methods are needed to handle it. In December 2019 there was an outbreak of acute respiratory syndrome caused by coronavirus 2 infection that occurred in Wuhan and on February 12, 2020, the World Health Organization officially named the disease Corona Virus 2019 (Covid 19). This research will conduct clustering of areas affected by Covid 19 in the City of Bogor. The clustering was done using the K-Means method and dividing the data into 3 clusters, namely the low-impact cluster, the medium-impact cluster and the high-impact cluster. The results showed that from 68 urban villages in the city of Bogor, 45% of the area was in the low-affected category, 35.29% of the area was in the medium-affected category and 19.12% of the area was in the high-affected category.

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