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All Journal IJCIT (Indonesian Journal on Computer and Information Technology) Jurnal Teknik Komputer AMIK BSI JIKA (Jurnal Informatika) Jurnal Infortech Akrab Juara : Jurnal Ilmu-ilmu Sosial Computer Science (CO-SCIENCE) Sci-Tech Journal Paradigma Literasi: Jurnal Pengabdian Masyarakat dan Inovasi Informatics and Software Engineering (ISE)
Musriatun Napiah
Universitas Bina Sarana Informatika
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering Library & Information Science Medicine & Pharmacology Public Health Other

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Pengembangan Sistem Kontrol Populasi Ikan Berbasis Arduino Uno dengan Sensor Ultrasonik Eka Kusuma Pratama; Musriatun Napiah; Sujiliani Heristian; Arina Selawati
JURNAL TEKNIK KOMPUTER AMIK BSI Vol 10, No 1 (2024): Periode Januari 2024
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jtk.v10i1.20151

Abstract

Fish populations are one of the important assets in maintaining the balance of aquatic ecosystems. To manage fish populations effectively, an innovative and automated approach is needed. This research aims to develop an Arduino Uno-based fish population control system with ultrasonic sensors as an environmentally friendly and efficient solution. The developed system uses ultrasonic sensors to detect the presence of fish in a pond or water container. The detection data from the ultrasonic sensor is then processed by the Arduino Uno microcontroller. The system can identify the number of fish in aquatic containers and take appropriate action to control fish populations. This research integrates ultrasonic sensor technology with Arduino Uno control capabilities to provide an accurate and automated solution in controlling fish populations. In trials, this system succeeded in identifying and controlling fish populations well, maintaining the balance of aquatic ecosystems without the need for direct human intervention The results of this research have great potential in fish farming applications, environmental research, and natural resource conservation. With the proposed automated approach, it is expected to make a positive contribution in maintaining the balance of aquatic ecosystems and supporting environmental sustainability
Perbandingan Algoritma Machine Learning pada Klasifikasi Penyakit Jantung Napiah, Musriatun; Heristian, Sujiliani
Jurnal Infortech Vol 6, No 1 (2024): Juni 2024
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/infortech.v6i1.21888

Abstract

Jantung merupakan organ paling penting dalam tubuh manusia yang memiliki fungsi utama untuk memompa darah ke seluruh tubuh melalui pembuluh darah,  World Health Organization (WHO) menyebutkan bahwa penyakit jantung koroner (PJK) menjadi salah satu masalah kesehatan dalam system kardiovaskular yang jumlahnya meningkat cepat dengan angka kematian 6,7 juta kasus pada tahun 2017. Banyak alternatif atau cara yang digunakan untuk mencegah dan mendeteksi penyakit jantung, namun karena kurangnya pengetahuan, penderita penyakit jantung banyak yang terlambat untuk memeriksa diri ke dokter. Tujuan dari penelitian ini adalah untuk mendeteksi penyakit jantung akibat gangguan kadiovaskular dengan menggunakan dataset dari http://archive.ics.uci.edu/ml/ dengan data sebanyak 1026 data penyakit jantung. Metode yang digunakan pada penlitian ini adalah Machine Learning dengn algoritma logistic regression, naive bayes, dan k-nearest neighbour (KNN) . Hasil yang didapatan dari penelitian ini yang tertinggi adalah dengan menggunakan metode k-nearest neighbour (KNN) yaitu akurasi sebesar 91%, sedangkan dengan algoritma logistic regression akurasinya sebesar 85%, dan naive bayes akurasinya sebesar 83%.
Rancang Sistem Penyajian Bank Soal Untuk Jenjang Sekolah Menengah Atas Berbasis Web Napiah, Musriatun; Raharjo, Mugi; Putra, Jordy Lasmana; Heristian, Sujiliani; Leksono, Ilham Nur
Jurnal Infortech Vol 2, No 2 (2020): Desember 2020
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/infortech.v2i2.9022

Abstract

Sekolah Menengah Atas sebagai salah satu institusi penyelenggara pendidikan di Indonesia. Pelaksanaan ujian pada SMA Cengkareng 1 masih bersifat konvensional yang artinya belum adanya metode pembelajaran berbasis web. Penelitian ini bertujuan untuk merancang aplikasi yang mampu mendokumentasikan seluruh soal dan kegiatan selama pelaksanaan ujian dan pemberian tugas. Analisis dan desain menggunakan metode waterfall. Penelitian diawali dengan melakukan studi literature, pengumpulan data, analisis sistem dan kebutuhan, membuat pemodelan sistem menggunakan UML, merancang implementasi aplikasi, melakukan pengujian dengan Black Box Testing dan maintance atau pemeliharaan data sistem. Aplikasi Bank Soal berbasis web dirancang memiliki fitur untuk pendataan soal dan penjadwalannya, monitoring pelaksanaan ujian dan monitoring upload tugas siswa. Hasil penelitian ini dapat digunakan sebagai dasar pengembangan aplikasi Bank Soal berbasis web dalam rangka pengelolaan evaluasi belajar yang lebih interkatif di studi kasus untuk jenjang Sekolah Menengah Atas.
Prediksi Pengaruh Matakuliah Terhadap Peminatan Outline Tugas Akhir Mahasiswa Dengan Jaringan Syaraf Tiruan Raharjo, Mugi; Napiah, Musriatun; Putra, Jordy Lasmana; Mustofa, Mustofa
Jurnal Infortech Vol 2, No 1 (2020): Juni 2020
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (348.616 KB) | DOI: 10.31294/infortech.v2i1.7965

Abstract

Spesialisasi jurusan menjadi hal penting bagi mahasiswa untuk menentukan outline tugas akhir. Dalam penulisan ini kami membuat prediksi peminatan berdasarkan data nilai matakuliah terkait. Penulis menggunakan metode Jaringan Syaraf Tiruan (Artificial Neural Network) yang menghasilkan model seperti syaraf otak manusia berupa neuron dalam memecahkan masalah. Berdasarkan hasil pengumpulan data dan sudah melewati proses pemilihan data (Preproccessing), selanjutnya diproses menggunakan software rapidminer didapatkan keluaran berupa data neuralnet yang menghasilkan output dan performance dengan tingkat akurasi sebesar 85,97% dan nilai AUC sebesar 0,801. Diharapkan dengan adanya hasil ini dapat program studi atau himpunan bisa menentukan focus terhadap mahasiswanya dan dapat dikembangkan lagi dalam penelitian berikutnya.Kata kunci:  jaringan syaraf tiruan, proses, data
ANDROID BASED ANIMALS AND PLANTS NAME DICTIONARY APPLICATION WITH SEQUENTIAL SEARCHING METHOD RAHARJO, MUGI; NAPIAH, MUSRIATUN
Jurnal Infortech Vol 3, No 1 (2021): Juni 2021
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/infortech.v3i1.10461

Abstract

Smartphone telah menjadi bagian dari kehidupan sehari-hari masyarakat, Dalam hal ini penulis membuat aplikasi Kamus Nama Ilmiah atau bahasa latin hewan dan tumbuhan berbasis android adalah suatu ide dan gagasan pengembangan aplikasi mobile yang memungkinkan penggunanya dapat mencari kata dengan mudah dan cepat. Aplikasi ini memungkinkan pengguna dengan cepat mencari arti dari bahasa latin hewan maupun tumbuhan. Proses yang terjadi pada aplikasi ini meliputi pencarian kesamaan kata dengan menggunakan metode pencarian Sequential Searching. Input-an berupa nama hewan atau tumbuhan merupakan nilai string yang akan dijadikan parameter pencarian didalam database. Hasil pengujian Kamus pencarian menggunakan metode Sequential Searching berhasil dengan kecepatan kurang dari satu detik waktu pencarian. Dalam pengujian ini, digunakan kata terdepan dalam database sehingga pencarian kata lebih cepat. Kecepatan proses pencarian menggunakan metode Sequential Searching bergantung kata yang dicari dalam indeks pencarian.
Linear Regression Analysis to Predict the Percentage of Smoking in the Population Age 15 Years and Over Riziq Shihab, Muhammad Alfata; Napiah, Musriatun
Informatics and Software Engineering Vol. 2 No. 2 (2024): December 2024
Publisher : SAN Scientific

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58777/ise.v2i2.328

Abstract

Smoking is a serious public health problem in many countries, including Indonesia, as it can cause diseases such as lung cancer, heart disease and respiratory disorders. According to data from the Ministry of Health of the Republic of Indonesia, the prevalence of smoking among the population aged 15 years and above is still high. This study uses secondary data from the Central Bureau of Statistics (BPS) that records the percentage of smoking in the population aged 15 years and above by age group from 2019 to 2023. With this data, a linear regression algorithm was applied using RapidMiner to predict the percentage of smoking in 2024. The analysis showed that out of 11 age groups, 6 age groups experienced an increase in smoking percentage from the previous year: 15-19, 20-24, 25-29, 30-34, 55-59, and 60-64. Meanwhile, the other 5 age groups experienced a decrease: 35-39, 40-44, 45-49, 50-54, and 65+. Evaluation of the prediction model using root mean squared error (RMSE) resulted in a value of 0.4 +/- 0.000. This RMSE value indicates that the model has a low error rate, making it reliable for predicting the percentage of smoking by age group in Indonesia.   Merokok adalah masalah kesehatan masyarakat yang serius di banyak negara, termasuk Indonesia, karena dapat menyebabkan penyakit seperti kanker paru-paru, penyakit jantung, dan gangguan pernapasan. Menurut data Kementerian Kesehatan Republik Indonesia, prevalensi merokok di kalangan penduduk usia 15 tahun ke atas masih tinggi. Penelitian ini menggunakan data sekunder dari Badan Pusat Statistik (BPS) yang mencatat persentase merokok penduduk usia 15 tahun ke atas berdasarkan kelompok umur dari tahun 2019 hingga 2023. Dengan data ini, algoritma regresi linear diterapkan menggunakan RapidMiner untuk memprediksi persentase merokok pada tahun 2024. Hasil analisis menunjukkan bahwa dari 11 kelompok umur, terdapat 6 kelompok umur yang mengalami peningkatan persentase merokok dari tahun sebelumnya: 15-19, 20-24, 25-29, 30-34, 55-59, dan 60-64. Sementara itu, 5 kelompok umur lainnya mengalami penurunan: 35-39, 40-44, 45-49, 50-54, dan 65+. Evaluasi model prediksi menggunakan root mean squared error (RMSE) menghasilkan nilai 0.884 +/- 0.000. Nilai RMSE ini menunjukkan bahwa model memiliki tingkat kesalahan yang rendah, sehingga dapat diandalkan untuk memprediksi persentase merokok berdasarkan kelompok umur di Indonesia.
Analisis Sentimen Ulasan Pelanggan Menggunakan Algoritma Naive Bayes pada Aplikasi Gojek Heristian, Sujiliani; Napiah, Musriatun; Erawati, Wati
Computer Science (CO-SCIENCE) Vol. 5 No. 1 (2025): Januari 2025
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v5i1.7775

Abstract

Transportation is a means that a person uses to move from one place to another. One mode of transportation that is popular among the public is online motorcycle taxis, such as Gojek. Gojek continues to innovate to meet customer needs more effectively, as well as expand the scope of its services. This research aims to identify the number of positive and negative sentiments in the user review dataset, evaluate the performance of the algorithm used, and measure the level of customer satisfaction with Gojek services. Analysis was carried out on 6,485 customer reviews, which resulted in 4,387 positive sentiments and 2,098 negative sentiments. The classification model used, namely Naive Bayes, shows an accuracy of 88.5%, precision of 88.1%, and recall of 89.0%. The results of this research indicate that the Naive Bayes method provides good performance in analyzing the sentiment of user reviews of Gojek services
IMPLEMENTASI ALGORITMA DJIKSTRA MENENTUKAN JARAK TERDEKAT JELAMBAR KAMPUS STMIK NUSA MANDIRI CENGKARENG Musriatun Napiah; Rachma Darma Astuti; Mustofa Mustofa
Akrab Juara : Jurnal Ilmu-ilmu Sosial Vol. 7 No. 1 (2022): Februari
Publisher : Yayasan Azam Kemajuan Rantau Anak Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58487/akrabjuara.v7i1.1757

Abstract

Traffic jams in Jakarta have become our daily sight. There are many steps that have been taken by the government to solve congestion in Jakarta. However, traffic jams still occur today. The high mobility of road users is often constrained by the lack of limited road facilities and infrastructure. Therefore, road users must find their own way to solve this problem. That is, one of the most effective and efficient ways is to find an alternative route or route for the shortest distance that can be traversed using the Djikstra Algorithm. So that the journey from the Jelambar area to the STMIK NUSA MANDIRI Cengkareng campus can be passed quickly without being blocked by traffic jams. The use of the Djikstra Algorithm can provide a solution because the Djikstra Algorithm provides output in the form of the fastest and shortest path from the place of origin to our destination.
SENTIMENT ANALYSIS OF VIDEO EDITING APPLICATIONS USING SUPPORT VECTOR MACHINE ON GOOGLE COLAB Raharjo, Mugi; Putra, Jordy Lasmana; Heristian, Sujiliani; Napiah, Musriatun
Jurnal Informatika Vol 9, No 2 (2025): JIKA (Jurnal Informatika)
Publisher : University of Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/jika.v9i2.13699

Abstract

Sentiment analysis is an important approach in understanding user opinions about an application. This study aims to analyze user reviews of the CapCut application using the Support Vector Machine (SVM) algorithm on the Google Colab platform. The preprocessing stages include data cleaning, word normalization using a dictionary from Kaggle, case folding, tokenization, stopword removal, and stemming. Furthermore, the data is converted into a numerical representation using the TF-IDF vectorization method. The labeling process is carried out using a sentiment lexicon obtained from GitHub. After performing data splitting, the SVM model is applied to classify sentiment into three categories: positive, negative, and neutral. The evaluation results show that the SVM model achieves the best accuracy of 90.12%. Based on the classification report, the model has high precision of 0.94 for positive and negative classes and 0.83 for the neutral class. Additionally, the confusion matrix indicates that the model can classify sentiment quite well, although there are still minor errors in predicting neutral sentiment. The findings of this study demonstrate that the SVM method can be effectively used to analyze user sentiment toward the CapCut application, providing valuable insights for improving user experience in the future.
APLIKASI PERHITUNGAN BERAT BADAN IDEAL MENGGUNAKAN METODE IMT BERBASIS ANDROID Setiawan, Ade; Adilah M, Tika; Muharrom, Muhammad; Napiah, Musriatun
Akrab Juara : Jurnal Ilmu-ilmu Sosial Vol. 4 No. 4 (2019)
Publisher : Yayasan Azam Kemajuan Rantau Anak Bengkalis

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

Abstract

Knowledge of normal weight is very important. Many general public whose lifestyle is unhealthy and irregular. One pattern of unhealthy living is excessive consumption of food. So that the height and weight are not balanced. When we consume too much food excessively, this can cause obesity. Because various kinds of diseases arise due to obesity problems. So from this we the authors make an android-based application whose function is to socialize the importance of ideal body weight. Of course many methods are used to find out the ideal weight category. Here the author uses the IMT (Body Mass Index) method to calculate and determine the ideal weight category and the tools used are eclipse indigo.
Co-Authors Ade Setiawan Ade Setiawan Aminuyati Arina Selawati Dwiza Riana Eka Kusuma Pratama Endrawan, Afif Eni Heni Hermaliani Erawati, Wati Fajar Akbar Fajar Shidiq Jordy Lasmana Putra Leksono, Ilham Nur Mila Desi Anasanti Mugi Raharjo Muhammad Haris Muhammad Muharrom Muhammad Muharrom Mustofa Mustofa Mustofa Mustofa Rachma Darma Astuti Rachmat Adi Purnama Rachmawati Darma Astuti Rachmawati Darma Astuti Raharjo, Mugi Rian Septian Anwar Rifki Sadikin Riziq Shihab, Muhammad Alfata Sujiliani Heristian Susafa'ati Susafa'ati Tika Adilah M Tommi Alfian Armawan Sandi Waeisul Bismi Waesul Bismi