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All Journal JUTI: Jurnal Ilmiah Teknologi Informasi JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Community Development Journal: Jurnal Pengabdian Masyarakat
Arisa, Nursanti Novi
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Health Professions Library & Information Science Public Health

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PERHITUNGAN DAN PEMISAHAN SEL DARAH PUTIH BERDASARKAN CENTROID DENGAN MENGGUNAKAN METODE MULTI PASS VOTING DAN K-MEANS PADA CITRA SEL ACUTE LEUKEMIA Arisa, Nursanti Novi; Fatichah, Chastine
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 16, No. 2, Juli 2018
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v16i2.a661

Abstract

Leukemia is one of the dangerous diseases that can cause death. One of the types of leukemia is acute leukemia that includes ALL (Acute Lymphoblastic Leukemia) and AML (Acute Myeloid Leukemia). The fastest identification against this disease can be done by computing and analysing white blood cell types. However, the manual counting and identification of the white blood cell types are still limited by time. Therefore, automatic counting process is necessary to be conducted in order to get the results more quickly and accurately. Previous studies showed that automatic counting process in the image of Acute Leukemia cells faced some obstacles, the existence of touching cell and the implementation of  geometry feature that cannot produce an accurate counting. It is because the shapes of the cell are various. This study proposed a method for the counting of white blood cells and the separation of touching cells on Acute Leukemia cells image by using Multi Pass Voting method (MPV) based on seed detection (centroid) and K-Means method. Initial segmentation used for separating foreground and background area is canny edge detection. The next stage is seed detection (centroid) using Multi Pass Voting method. The counting of white blood cells is based on the results of the centroid produced. The existence of the touching cells are  separated using K-Means method, the determination of the initial centroid  is based on the results of the Multi Pass Voting method. Based on the evaluation results of 40 images of Acute Leukemia dataset, the proposed method is capable to properly compute based on the centroid. It is also able to separate the touching cell into a single cell. The accuracy of the white blood cell counting result is about 98,6%.
KOLABORASI TRIPLE HELIX DALAM PROSES PENGELOLAAN SAMPAH DI KELURAHAN KLANDASAN ILIR Arisa, Nursanti Novi; Amalia, Dwi Nur; Rini, Intan Dwi Wahyu Setyo
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 6 No. 1 (2025): Volume 6 No. 1 Tahun 2025
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v6i1.39809

Abstract

Pembangunan IKN bukan hanya sekedar memindahkan ibu kota negara dari pulau Jawa ke pulau Kalimantan, melainkan untuk meraih visi Indonesia Emas 2045. Kota Balikpapan merupakan salah satu kota yang terletak di pesisir timur Kalimantan yang mengalami perkembangan ekonomi yang pesat, berkat posisinya sebagai pusat industri, perdagangan, dan transportasi. Sebagai kota yang terus berkembang. Balikpapan tidak hanya menghadapi tantangan dalam aspek infrastruktur dan ekonomi, tetapi juga dalam masalah lingkungan, khususnya pengelolaan sampah. Seiring dengan adanya peningkatan jumlah penduduk yang mencapai 281,6 juta berbanding lurus dengan jumlah sampah yang dihasilkan yang mencapai 31,9 juta ton. Permasalahan sampah di Balikpapan semakin kompleks karena adanya ketidakseimbangan antara laju pertumbuhan sampah dan kemampuan sistem pengelolaan sampah yang ada. Sebagian besar sampah tersebut masih berakhir di Tempat Pembuangan Akhir (TPA). Kegiatan pengabdian masyarakat dilakukan berfokus pada peningkatan kesadaran masyarakat sekaligus memberikan edukasi dalam pengelolaan limbah sampah. Keberhasilan kegiatan turut melibatkan sinergitas dari pemerintah, akademis, dan industry dengan mengusung konsep Triple Helix. Kegiatan ini mengahasilkan dampak postif kepada masyarakat sebagai bentuk dukungan mengurangi volume sampah di Kelurahan Klandasan Ilir.
Analisis Sentimen dan Pemodelan Topik Terhadap Ulasan Aplikasi Mobile JKN Menggunakan SVM dan LDA Arisa, Nursanti Novi; Himawan, Kevin
Journal of Information System Research (JOSH) Vol 7 No 1 (2025): Oktober 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i1.8029

Abstract

In 2024, the number of internet users in Indonesia reached 221.56 million, accounting for 79.5% of the population an increase of 1.4% from the previous year (APJII). This growth has driven digital transformation in various sectors, including healthcare. To support this, the government launched the Mobile JKN app as part of the digitalization of the National Health Insurance (JKN) program, aimed at expanding access to services, especially in remote areas. Despite over 50 million downloads, the app still faces technical issues such as difficulties with registration, verification, and frequent updates that disrupt user experience. This study analyzes user complaints using sentiment analysis with the Support Vector Machine (SVM) algorithm and topic modeling via Latent Dirichlet Allocation (LDA). A total of 285,661 reviews from the Google Play Store (June 2016–December 2024) were collected and pre-processed. Of these, 181,657 reviews were analyzed—80% used for training (145,615) and 20% for testing (36,042). The SVM model showed strong performance, achieving 90% accuracy, 90% precision, 89% recall, and an F1-score of 89%. It classified 12,965 reviews as positive and 23,077 as negative. Topic modeling of negative reviews revealed five key themes with a coherence score of 0.5064: app usage, login and registration, data verification, online services and data changes, and app updates. Further analysis of version 4.12.0 informed improvement recommendations, particularly regarding phone number verification, login, and facial recognition issues.
Co-Authors Amalia, Dwi Nur Chastine Fatichah Himawan, Kevin Intan Dwi Wahyu Setyo Rini