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All Journal JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Abdi Jurnal Publikasi Spectrum: Multidisciplinary Journal
Asyiah, Nilovar
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences Other

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SOSIALISASI DIGITAL GUNA MENGARAHKAN SISWA/SISWI SMPN 2 GUNUNG SINDUR UNTUK PEMANFAATAN INTERNET PRODUKTIF Asyiah, Nilovar; Rahayu, Eka Sri; Nurhasanah
Abdi Jurnal Publikasi Vol. 2 No. 6 (2024): Juni
Publisher : Abdi Jurnal Publikasi

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Abstract

The utilization of the internet among teenagers nowadays tends to lean towards less productive activities such as playing online games, social media, and excessive consumption of entertainment content. This can disrupt their academic and social development. Therefore, systematic efforts are needed to guide internet use towards more productive activities. This program aims to raise awareness and improve the skills of students at SMPN 2 Gunung Sindur in utilizing the internet as a learning tool, developing creativity, and exploring opportunities that can support their future.The introduction to internet technology and platforms considers other important aspects such as online safety, privacy, digital ethics, and the development of critical skills. This program provides students with an understanding of wise and productive internet use. Additionally, students will gain an understanding of internet usage ethics and ways to avoid negative risks such as cyberbullying and false information.Students at SMPN 2 Gunung Sindur will be able to utilize the internet more productively and responsibly, enhancing digital skills beneficial for their academic and personal development in the future. The success of this program is measured by the increase in students' knowledge and skills in utilizing the internet, as well as behavioral changes towards more positive and constructive internet use.  
Perancangan Sistem Bel Otomatis Dan Informasi Waktu Belajar Di Sekolah Berbasis Internet Of Things: (Studi Kasus: SMK Bina Mandiri) Asyiah, Nilovar
Spectrum: Multidisciplinary Journal Vol. 1 No. 3 (2024): Spectrum: Multidisciplinary Journal
Publisher : Sapta Arga Nusantara

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Pendidikan formal dari Sekolah Dasar hingga Sekolah Menengah Atas/Sekolah Menengah Kejuruan berlangsung menurut jadwal yang telah ditentukan dimana awal dan akhir setiap pelajaran ditandai dengan bunyi bel sekolah. Di SMK Bina Mandiri pengoperasian bel sekolah dilakukan manual oleh guru piket sesuai jadwal yang ditentukan dengan cara melihat jam dinding dan menekan tombol bel. Namun terkadang mereka lupa atau terlambat membunyikan bel sekolah karena ada tugas lain yang di lakukan oleh guru piket sehingga terjadi ketidak efisienan waktu dan tenaga dalam proses belajar mengajar. Siswa juga kurang paham dalam mengartikan maksud bunyi bel yang di tekan dan tidak ada bedanya bunyi bel dalam satu yayasan. Dalam penelitian ini menggunakan dua mode yaitu yang pertama untuk membuat bel otomatis dengan jadwal yang telah di buat wakil kurikulum dengan output berupa suara dengan format .mp3 dan sistem informasi berupa running text. Penelitian ini untuk mengembangkan sistem bel sebelumnya dan menerapkan kembali pengaturan bel dan pesan informasi supaya bisa di lakukan oleh smartphone dimana saja karena dengan teknologi internet of things.
Penerapan BERTopic dan Analisis Sentimen Leksikal Pada Ulasan Relevan di Google Maps Mengenai Universitas Pamulang Asyiah, Nilovar; Aktavia, Widodo
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): Juli 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.8007

Abstract

The rapid advancement of information technology has encouraged the public to actively share reviews through digital platforms such as Google Maps. These reviews are not only informative but also reflect real user opinions and experiences regarding places or institutions, including higher education institutions. This study aims to analyze the main topics and sentiment classification contained in Google Maps reviews related to Universitas Pamulang. The approach used in this research combines two main methods. First, topic modeling is conducted using BERTopic, a modern technique based on transformer embeddings and HDBSCAN clustering algorithms, which can capture the semantic context of text more deeply. Second, sentiment analysis is performed using a lexicon-based approach, applying an Indonesian sentiment lexicon to efficiently identify the polarity of opinions without requiring model training.The data analyzed were collected through web scraping of relevant public reviews on Google Maps across four Universitas Pamulang locations: Central Campus, Viktor Campus, Witanaharja Campus, and Unpam Serang. The analysis revealed several dominant topics such as academic services, campus facilities, and bureaucracy. The majority of sentiments identified were neutral to positive, although negative opinions were also found in certain aspects. These findings are expected to serve as strategic input for the university to enhance service quality and strengthen its institutional image in the digital landscape.
Implementasi dan Optimalisasi Metode Naive Bayes Dalam Sistem Deteksi Dini Penyakit Tiroid Nurhasanah, Nurhasanah; Asyiah, Nilovar; Irawati, Okta
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): Juli 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7940

Abstract

This study aims to develop an early detection system for thyroid disease using the Naive Bayes algorithm. The dataset used is the Thyroid Disease Dataset from the UCI Machine Learning Repository, consisting of thousands of patient records. Prior to model training, the data undergoes preprocessing steps such as handling missing values, numerical normalization, and categorical encoding. The classification process involves calculating the prior probability, likelihood, and posterior probability for each class: normal, hypothyroid, and hyperthyroid. The system also presents the probability percentage for each class as an automated diagnosis result. Model accuracy is evaluated using a Confusion Matrix, achieving an accuracy score of 98.01% on the test data. These results indicate that the proposed approach can effectively and accurately classify thyroid conditions for early diagnosis purposes.
Co-Authors Aktavia, Widodo Irawati, Okta Nurhasanah Nurhasanah Nurhasanah Rahayu, Eka Sri