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All Journal Jurnal Informatika SISFOTENIKA Indonesian Journal on Software Engineering (IJSE) Jurnal Teknik Komputer AMIK BSI Jurnal Pilar Nusa Mandiri Techno Nusa Mandiri : Journal of Computing and Information Technology INTI Nusa Mandiri JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Infortech Jurnal Sistem Informasi Computer Science (CO-SCIENCE) SPEED - Sentra Penelitian Engineering dan Edukasi Jurnal Teknologi Sistem Informasi Journal Medical Informatics Technology Jurnal Pengabdian Kepada Masyarakat International Journal of Computer Technology and Science
Taopik Hidayat
Universitas Nusa Mandiri
Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Medicine & Pharmacology Public Health Social Sciences Other

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Implementasi Algoritma Klasifikasi Terhadap Tweet Pornografi Kaum Homoseksual Pada Twitter Hidayat, Taopik; Pebrianto, Rangga; Pratiwi, Risca Lusiana; Gata, windu; Saputri, Daniati Uki Eka
Indonesian Journal on Software Engineering (IJSE) Vol 6, No 2 (2020): IJSE 2020
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/ijse.v6i2.9008

Abstract

Abstract: Twitter is one of the social media with the number of users who reach millions of users. The number of Twitter users in 2019 increased by 17 percent in 2018 to 145 million users with a variety of good both positive and bad. The negative impacts that occur such as the spread of status, images, and videos that affect pornography especially among freedom groups. Homosexuals are sexually oriented people who like the same sex that occurs in men, the rejection often experienced by men makes one of the reasons intellectuals use Twitter social media to show their personal relationships, open to each other, socializing with same sex, looking for conversation, to become a place to find a partner. The purpose of this study is to determine the positive and negative sentiments to determine the level of accuracy of intellectual pornography tweets in Indonesia from data taken from Twitter tweets by using the TF-IDF and k-NN methods. The results of this study get an accuracy value of 88.25% containing pornography and the remaining 11.75% not containing pornography will contain news, news, and other information.Keywords: homosexual, sentiment analysis, twitterAbstrak: Twitter merupakan salah satu media sosial dengan jumlah pengguna mencapai jutaan pengguna. Jumlah pengguna Twit-ter pada tahun 2019 dicatat meningkat 17 persendari tahun 2018 menjadi 145 juta pengguna dengan berbagai dampak baik dampak positif maupun dampak negatif. Dampak negatif yang ditimbulkannya seperti penyebaran status, gambar, dan video yang bersifat pornografi khsusunya di kalangan kaum homoseksual. Homoseksual merupakan orang yang berorientasi seksual sebagai penyuka sesama jenis yang terjadi pada kaum pria, Penolakan yang sering dialami kaum homoseksual men-jadikan salah satu alasan kaum homoseksual menggunakan media sosial Twitter untuk menunjukkan identitas diri mereka, saling terbuka, bersosialisasi dengan sesama jenis, mencari penghasilan, hingga menjadi ajang pencarian pasangan. Tujuan dari penelitian ini adalah untuk mengetahui sentimen positif dan negatif untuk mengetahui tingkat akurasi terhadap tweet pornografi kaum homoseksual di Indonesia dari data yang diambil dari tweet Twitter dengan menggunakan metode TF-IDF dan k-NN. Hasil penelitian ini mendapatkan nilai accuracy sebesar 88,25% mengandung unsur pornografi dan sisanya sebesar 11,75 tidak mengandung unsur pornografi akan tetapi berisi iklan, berita, dan informasi lainnya.Kata kunci: homoseksual, sentimen analisis, twitter
Klasifikasi Gambar Palmprint Berbasis Multi-Kelas Menggunakan Convolutional Neural Network Hidayat, Taopik; Khasanah, Nurul; Saputri, Daniati Uki Eka; Khultsum, Umi; Pratiwi, Risca Lusiana
Jurnal Sistem Informasi Vol 11 No 1 (2022): JSI Periode Februari 2022
Publisher : LPPM STMIK ANTAR BANGSA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (504.405 KB) | DOI: 10.51998/jsi.v11i1.474

Abstract

Abstract—Biometric technology is developing to be the most relevant mechanism in identity identification. The main purpose of an identity management system is to be able to establish a relationship between individuals and their identities when needed under certain conditions. Among the newly proposed identity verification and personal identification technologies, biometrics is rapidly becoming the most relevant mechanism for identity recognition. This study proposes a new biometric recognition method for authentication and personal identification. Palm image recognition based on image processing for authentication and personal identification is proposed, namely competitive coding using the Convolutional Neural Network (CNN) and Local Binary Pattern (LBP) texture extraction with hyperparameter modifications. The dataset used comes from the Birjand University Mobile Palmprint Database (BMPD) which consists of 20 classes with a total of 800 palm images. The research was conducted using a data distribution of 80% training data and 20% validation data. The tests carried out resulted in a good accuracy value of the proposed model of 93.3% for the training process and 90.6% for the validation process. Keywords: Biomethric, CNN, LBP Intisari— Teknologi biometrik berkembang menjadi mekanisme paling relevan dalam pengidentifikasi identitas. Tujuan utama dari sistem manajemen identitas adalah untuk dapat membangun hubungan antara individu dan identitas mereka ketika dibutuhkan dalam kondisi tertentu. Di antara verifikasi identitas yang baru diusulkan dan teknologi identifikasi pribadi, biometrik dengan cepat menjadi mekanisme yang paling relevan untuk pengenalan identitas. Penelitian ini mengusulkan metode pengenalan biometrik terbaru untuk otentikasi dan identifikasi pribadi. Pengenalan citra telapak tangan berbasis image processing untuk otentikasi dan identifikasi pribadi yang diusulkan yaitu pengkodean kompetitif menggunakan metode Convolutional Neural Network (CNN) dan ekstraksi tekstur Local Binary Pattern (LBP) dengan modifikasi hyperparameter. Dataset yang digunakan berasal dari Birjand University Mobile Palmprint Database(BMPD) yang terdiri dari 20 kelas dengan total 800 citra telapak tangan. Penelitian dilakukan dengan menggunakan distribusi data sebesar 80% data training dan 20% data validasi. Pengujian yang dilakukan menghasilkan nilai akurasi yang baik dari model yang diusulkan sebesar 93,3% untuk proses training dan 90,6% untuk proses validasi. Kata Kunci: Biometrik, CNN, LBP  
ANALISA DAN IMPLEMENTASI JARINGAN WIRELESS MAC ADDRESS MENGGUNAKAN FILTERING PADA PT. FAYA KUNTURA AGUNG KONSULTINDO Dipo Era Ginanti; Ade Christian; Taopik Hidayat
INTI Nusa Mandiri Vol 16 No 2 (2022): INTI Periode Februari 2022
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v16i2.2781

Abstract

The evolution of this era is become advancing as well for Technology Information and Telecommunications. This evolution has been explored in Wireless Technology, even in all devices such as smartphones, tablets and laptops can use it. The Internet has tremendously impacted culture and it become a daily necessity by people in the world, as the internet can support the process of communicating, learning, and data transfer. Places that use wireless networks have started a lot such as schools, universities, and companies. Yet, wireless networks still have security that is quite vulnerable because it can be misused by other parties. To minimize this problem we can use MAC Address Filtering. MAC Address Filtering is a technique for prevents access to a network if the MAC Address of the devices attempting to connect does not match any addresses marked as allowed. MAC Address Filtering has 2 tasks of verification so before it does filtering, the user must log in first using the MAC Address that has been registered and then enter the username and password if it matches the MAC Address then the login will be successful, otherwise, it will be rejected. This wireless MAC Address Filtering security can avoid hackers who can enter the wireless network which makes a slow network.
ANALISIS SENTIMEN TERHADAP KINERJA MENTERI KESEHATAN INDONESIA SELAMA PANDEMI COVID-19 Tri Rivanie; Rangga Pebrianto; Taopik Hidayat; Achmad Bayhaqy; Windu Gata; Hafifah Bella Novitasari
Jurnal Informatika Vol 21, No 1 (2021): Jurnal Informatika
Publisher : IIB Darmajaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30873/ji.v21i1.2864

Abstract

The pandemic that occurred in Indonesia has not yet subsided and far from under control. Indonesian Ministry of Health is most appropriate person to responsible for providing an explanation of actual situation and extent to which state has handled it. However, he has rarely appeared in public lately to explain about handling of Covid-19 pandemic. In response, many people are pros and cons come to give their opinions and feedback. The increasing use of internet during pandemic, especially on social media, where one of them is Twitter, which is a means of expressing opinions. Posting tweets is a community habit to assess or respond to events, as well as represent public's response to an event, especially Ministry of Health steps and policies in handling and breaking chain of Covid-19 pandemic.The tweet posts were taken only in Indonesian-language and also related to performance of Government, especially Ministry of Health. After that, a label is given so that sentiment of tweets is known. To test results of these sentiments, an algorithm is used by comparing two methods of Support Vector Machine (SVM) and Naïve Bayes (NB). Validation was carried out using k-Fold Cross Validation to obtain an accuracy value. The results show that accuracy value for NB algorithm is 66.45% and SVM algorithm has a greater accuracy value of 72.57%. So it can be seen that SVM algorithm managed to get the best accuracy value in classifying positive comments and negative comments related to sentiment analysis towards Ministry of Health. Keywords—Support Vector Machine, Naïve Bayes, Analisis sentimen, K-Fold Cross Validation
IMPLEMENTATION OF DECISION TREE AND K-NN CLASSIFICATION OF INTEREST IN CONTINUING STUDENT SCHOOL Daniati Uki Eka Saputri; Fitra Septia Nugraha; Taopik Hidayat; Abdul Latif; Ade Suryadi; Achmad Baroqah Pohan
Jurnal Techno Nusa Mandiri Vol 17 No 1 (2020): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1075.117 KB) | DOI: 10.33480/techno.v17i1.1289

Abstract

Education is important to prepare quality Human Resources (HR) because quality human resources is an important factor for the nation and state development. Therefore, it is expected that every citizen has the right to get high educational opportunities from the 12-year compulsory education level. This study aims to implement the Decision Tree and K-NN algorithm in the classification of student interest in continuing school. This study proposes combining the Decision Tree and K-NN algorithm methods to improve accuracy with the Gain Ratio, Information Gain and Gini Index approaches for the measurement process. The test results show that the use of the Decision Tree algorithm produces an accuracy value of 97.30% while using the K-NN algorithm produces an accuracy of 89.60%. While the proposed method by combining the Decision Tree and K-NN algorithms produces an accuracy value of 98.07%. The results of evaluation measurements using the Area Under Curve (AUC) on the Decision Tree algorithm are 0.992 and the AUC on K-NN is 0.958 and on the combination of the Decision Tree and K-NN algorithms of 0.979. These results indicate that the proposed algorithm is very significant towards increasing accuracy in the classification of the interests of high school students continuing school
KLASIFIKASI GAMBAR PALMPRINT BERBASIS MULTI-KELAS MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK Taopik Hidayat; Nurul Khasanah; Daniati Uki Eka Saputri; Umi Khultsum; Risca Lusiana Pratiwi - Universitas Nusa Mandiri
SPEED - Sentra Penelitian Engineering dan Edukasi Vol 14, No 1 (2022): Speed Januari 2022
Publisher : APMMI - Asosiasi Profesi Multimedia Indonwsia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55181/speed.v14i1.748

Abstract

Teknologi biometrik berkembang menjadi mekanisme paling relevan dalam pengidentifikasi identitas. Tujuan utama dari sistem manajemen identitas adalah untuk dapat membangun hubungan antara individu dan identitas mereka ketika dibutuhkan dalam kondisi tertentu. Di antara verifikasi identitas yang baru diusulkan dan teknologi identifikasi pribadi, biometrik dengan cepat menjadi mekanisme yang paling relevan untuk pengenalan identitas. Penelitian ini mengusulkan metode pengenalan biometrik terbaru untuk otentikasi dan identifikasi pribadi
Clustering of Clean Water Needs in Indonesia for the 2012-2017 Period Using the K-Means Algorithm Daniati Uki Eka Saputri; Taopik Hidayat; Siti Masturoh
SISFOTENIKA Vol 12, No 2 (2022): SISFOTENIKA
Publisher : STMIK PONTIANAK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30700/jst.v12i2.1241

Abstract

The need for clean water is important to support all activities of human survival. Data from the Central Statistics Agency (BPS) in 2017 showed the highest number of clean water distribution in each province was only 72.04%. These data indicate that access to clean water to meet daily needs is still far from sufficient. This study aims to classify the need for clean water for the period 2012-2017 using the K-Means algorithm. The data source was obtained from the official BPS website, namely data on the volume of clean water distributed to each province in Indonesia in 2012-2017. The process of replacing missing values was carried out on the missing data, then the data were grouped into three clusters, namely low (C0) in 25 provinces, high (C1) in 4 provinces, and moderate (C2) in 5 provinces using the K-Means algorithm. The centroid value for the C0 cluster is 150588.24, the centroid data for the C1 cluster is 1939461, the centroid data for the C2 cluster is 857876.6. The results of the K-Means clustering were tested using the Davies Bouldin Index (DBI) Validation as many as 3 clusters with a value of 0.534, the cluster results were optimal because the DBI value was close to 0.
FINAL GRADE PREDICTION MODEL BASED ON STUDENT'S ALCOHOL CONSUMPTION rangga ramadhan saelan; Siti Masturoh; Taopik Hidayat; Siti Nurlela; Risca Lusiana Pratiwi; Muhammad Iqbal
Jurnal Techno Nusa Mandiri Vol 19 No 1 (2022): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v19i1.3056

Abstract

Untuk mengetahui pengaruh konsumsi alcohol dan dan beberapa faktor lainnya yang diperkirakan memiliki peran terhadap tingkat kinerja belajar remaja yang masih bersekolah, maka saat ini dilakukan penelitian terhadap data publik yang telah didapatkan dengan menggunakan teknik machine learning dengan melatih beberapa model untuk memprediksi nilai akhir sebagai acuan kinerja belajar pelajar. Dengan melatih beberapa model machine learning untuk memprediksi nilai tahun akhir dari bahasa portugal dengan melakukan metode komparatif membandingkan model Support Vector Regressor (SVR) dan Random Forest (RF) sehingga akan didapatkan model terbaik untuk memprediksi. Semua model memiliki hyperparameter yang harus disesuaikan. Untuk menyetel hyperparameter ini menggunakan menggunakan Cross Validation. Model terbaik untuk memprediksi nilai akhir G3 adalah Support Vector Regressor (SVR) dan Random Forest (RF), dan memiliki mean absolute error (MAE) masing-masing sekitar 2,24 dan 2,25. Melalui plot MAE, model SVR dan RF bekerja dengan baik. Tetapi, Dengan menganalisis distribusi kesalahan yang dibuat oleh kedua model, dapat disimpulkan bahwa SVR lebih seimbang, yaitu memiliki rasio yang lebih baik antara nilai yang diremehkan dan ditaksir terlalu tinggi, sementara RF berkinerja lebih baik pada outlier.
PENERAPAN METODE DESIGN THINKING PADA MODEL PERANCANGAN UI/UX PADA FITUR REPORT HELPDESK TICKETING SISTEM Ilmalia Hartina; Nurmalasari Nurmalasari; Taopik Hidayat
INTI Nusa Mandiri Vol 17 No 1 (2022): INTI Periode Agustus 2022
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v17i1.3451

Abstract

Wijaya Karya (Persero) Tbk. Yaitu perusahaan yang bergerak di bidang infrastruktur. Sebagai perusahaan yang besar WIKA memiliki aplikasi untuk membantu proses bisnisnya. Aplikasi-aplikasi tersebut sebagian besar dikelola oleh departemen Sistem Informasi. Dari kekurangan aplikasi tersebut, tentunya akan ada keluhan-keluhan pengguna aplikasi yang telah dibuat. Proses pekerjaan yang dilakukan saat ini masih belum optimal karena belum adanya report ticket yang memudahkan Agen dan Manajer untuk melihat seluruh data tiket dan tampilan dari web helpdesk ticketing system yang kurang menarik sehingga penulis ingin mengubah tampilannya. Berdasarkan masalah di atas, maka diperlukan perancangan sistem pada aplikasi Helpdesk ticketing system. Perancangan ini menggunakan metode design thinking, yang terdiri dari tahapan empathize, define, ide, prototipe dan tes. Sehingga hasil dari perancangan ini memberikan rekomendasi berupa model UI/UX pada aplikasi Helpdesk ticketing system.
MEAT IMAGE CLASSIFICATION USING DEEP LEARNING WITH RESNET152V2 ARCHITECTURE Taopik Hidayat; Daniati Uki Eka Saputri; Faruq Aziz
Jurnal Techno Nusa Mandiri Vol 19 No 2 (2022): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v19i2.3932

Abstract

Meat is a food ingredient that can be consumed by humans and consists of essential nutrients, especially protein, which are needed for various physiological functions in the human body. Beef, goat and pork are meats that are commonly used by Indonesian people as daily processed foods. A very high level of meat consumption results in a high economic value of meat consumption. However, many people do not know how to distinguish between the types of beef, mutton and pork. This study aims to classify types of beef, goat and pork using the ResNet152V2 algorithm. The data used are 600 images with 200 images of beef, 200 images of mutton and 200 images of pork. The process carried out is pre-processing using 4 stages, namely image augmentation, image sharpness process, then the image is resized to adjust the size needed by the algorithm. The last pre-processing is to perform the image normalization process. After the pre-processing is done, then the data training stage is carried out using the ResNet152V2 algorithm to build a classification model and then the model is tested against data testing to get the results of the optimal classification of pork, goat and beef images by looking at the results of accuracy and loss values.
Co-Authors Abdul Latif Achmad Baroqah Pohan Achmad Bayhaqy Ade Christian Ade Suryadi Andi Saryoko Aziz, Faruq Budi Santoso, Satrio Daniati Uki Eka Saputri Dipo Era Ginanti Eka Saputra, Bagas Eka Saputri , Daniati Uki Faruq Aziz Faruq Aziz Fitra Septia Nugraha Gata, Windu Hafifah Bella Novitasari Ilmalia Hartina Khultsum, Umi M. Rangga Ramadhan Saelan Mulia Rahmayu Muzakki Ramadhan, Naufal Nurmalasari Nurmalasari Nurmalasari Nurmalasari Nurul Khasanah Nurul Khasanah Nurul Khasanah, Nurul Nurwijayanti Pratiwi, Risca Lusiana Rangga Pebrianto Retno Sari Rina Rina Risca Lusiana Pratiwi Risca Lusiana Pratiwi - Universitas Nusa Mandiri Salsabila, Unik Hanifah Seimahuira, Syarah Septian, Rendi Siti Masturoh Siti Masturoh siti nurlela Tri Rivanie Uki Eka Saputri, Daniati Umi Khultsum Veithzal Rivai Zainal Windu Gata YOANDA, YURIKA PRISILIA