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All Journal JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Terapan Abdimas INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Dinamisia: Jurnal Pengabdian Kepada Masyarakat JPP IPTEK (Jurnal Pengabdian dan Penerapan IPTEK) INTEK: Jurnal Penelitian Building of Informatics, Technology and Science Journal Zetroem Jurnal Ilmiah Teknologi Informasi dan Robotika KLIK: Kajian Ilmiah Informatika dan Komputer Jikom: Jurnal Informatika dan Komputer Software Development Digital Business Intelligence and Computer Engineering
Dianni Yusuf
Unknown Affiliation
Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Social Sciences Other

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Si-Bidan: Sistem Informasi Kesehatan Ibu dan Anak Kusuma, Dedy Hidayat; Shodiq, Mohammad Nur; Yusuf, Dianni; Saadah, Lailatus
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 3 No 1 (2019): Vol. 3 No. 1 Februari 2019
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (433.328 KB) | DOI: 10.29407/intensif.v3i1.12508

Abstract

Midwives are one of the health workers who provide child and maternal health (CMH) services and family planning. At present, most of the recording of midwife services is still managed conventionally by manual book keeping. It is less effective and efficient which causes the workload to increase, the information retrieval process is quite long and the risk of missing important data is likely to occur frequently. On the other hand, maternal patients are required to visit the midwife directly if they want to know the information on the progress of the pregnancy and their child. Based on these facts, a CMH information system was built that was accessible to midwives and parents. The information system developed consists of two integrated applications, namely web-based applications for midwives and mobile applications for parents. The web application facilitates midwives to record transactions, make reports, and deliver information to patients. While the mobile application makes it easier for parents to monitor the development of maternal and child health and other information provided by midwives. The system was developed using the water-fall software development model. The test results using the black-box test method indicate that the CMH system has been able to meet the user's functional requirements.
Disease Detection of Dragon Fruit Stem Based on The Combined Features of Color and Texture Hakim, Lutfi; Kristanto, Sepyan Purnama; Yusuf, Dianni; Shodiq, Mohammad Nur; Setiawan, Wahyu Ade
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 5 No 2 (2021): August 2021
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (843.916 KB) | DOI: 10.29407/intensif.v5i2.15287

Abstract

Dragon fruit is one of the favorite commodities in Banyuwangi Regency's agriculture. In 2019, this commodity had the fourth largest harvest area among other fruit commodities in Banyuwangi until it was exported to China. However, disease attacks often appeared in several dragon fruit plantations in Banyuwangi, and the identification system was still conventional. Many farmers did not know the types of disease and how to handle it, causing the quality and quantity of their crops to decline. Therefore, this study implemented two feature extraction methods. Both methods include color feature extraction using the color moments method and texture feature extraction using gray level co-occurrence matrices (GLCM). The methods used to develop a system that recognized or detected the three types of dragon fruit stem based on digital image processing using Support Vector Machine and k-Nearest Neighbors methods as comparison methods. The results obtained from this study indicated that the combination of the two proposed feature extraction methods could distinguish between stem rot, smallpox, and insect stings with an optimal accuracy score of 87.5% obtained by using Support Vector Machine as a classification method.
Classification of Dragon Fruit Stem Diseases Using Convolutional Neural Network Hakim, Lutfi; Asyhari, Aditya Roman; Kristanto, Sepyan Purnama; Yusuf, Dianni; Prasetyo, Junaedi Adi; Siregar, Hamdan Maruli
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 7 No 2 (2023): August 2023
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v7i2.20093

Abstract

A holticulture plant known as dragon fruit (pitaya) is a fruit that has many benefits and is widely cultivated by farmers in several areas of Banyuwangi. In dragon fruit plants there are various kinds of diseases that attack including red spot, stem rot, black rot, scab, and mosaic. Farmers still recognize diseases on dragon fruit stems manually so that sometimes there are errors in disease recognition. In this research, a system was developed to identify the types of diseases on dragon fruit stems. This system was built by proposing the Convolutional neural network method with the proposed architecture using the Python programming language with the Tensorflow, Keras, and Scikit-Learn libraries. The proposed system is tested using k-fold cross validation with tunning parameters fold = 5 and epoch = 5. The training results show that the highest accuracy performance value is 85.06% with the data used as test data as many as 191 images producing 147 correct data and 44 data wrong, while the average overall accuracy score was 76.43%.
Implementasi Sistem Informasi Terpadu sebagai Sarana Optimalisasi Pengelolaan Santri dan Siswa untuk Sekolah Berbasis Pesantren (SBP) di Ponpes Nuruttauhid Rini, Eka Mistiko; Yusuf, Dianni; Haq, Endi Sailul; Panduardi, Farisqi
JPP IPTEK (Jurnal Pengabdian dan Penerapan IPTEK) Vol 9, No 2 (2025): November
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.jpp-iptek.2025.v9i2.8316

Abstract

Sekolah Berbasis Pondok Pesantren (SBP) Nuruttauhid mengintegrasikan sistem sekolah formal dan pendidikan pesantren pada jenjang SMP. Pengelolaan administrasi santri dan siswa masih dilakukan secara manual, terutama pada pendaftaran dan pembayaran sehingga menimbulkan ketidakefisienan, keterlambatan, dan kesalahan data. Mitra juga mengalami kesulitan dalam melakukan pemantauan dan evaluasi administrasi, serta belum memiliki sarana digital untuk menyampaikan branding dalam rangka meningkatkan citra dan daya tarik pesantren. Sebagai solusi, diusulkan implementasi sistem informasi terpadu untuk mengoptimalkan pengelolaan santri dan siswa di SBP Nuruttauhid. Sistem ini mencakup fitur utama berupa pendaftaran online, pencatatan administrasi pembayaran biaya pondok dan sekolah, serta pengembangan web profil pesantren. Penerapan sistem ini meningkatkan kecepatan, akurasi, dan transparansi administrasi, serta memudahkan akses informasi bagi pihak pesantren dan orang tua. Target luaran program meliputi sistem informasi yang siap digunakan dan pelatihan penggunaan sistem. Program meliputi analisis kebutuhan, pengembangan, uji coba, pelatihan, dan monitoring. Hasil evaluasi menunjukkan peningkatan efisiensi operasional dengan kepuasan pengguna rata-rata 4,16 dan efektivitas informasi publik 4,54 (Sangat Baik). Implementasi ini diharapkan memperkuat citra pesantren berbasis teknologi dan menjadi model bagi lembaga serupa.
Co-Authors Arrizki, Mohammad Rashel Arum Andary Ratri Asyhari, Aditya Roman Aulia, Fatwa Bachtiar, Riza Rahimi Bagus Aris Pradana Dewi Widyastutik Endi Sailul Haq Erly Mulyani Erly Mulyani Farizqi Panduardi Galih Hendra Wibowo Hari Setiawan Hidayatullah, Arief HIDAYATULLAH, ARIEF Indira Nuansa Ratri Joko, Mohamad Junaedi Adi Prasetyo Kusuma, Dedy Hidayat Lutfi Hakim Lutfi Hakim Mistiko Rini, Eka Mohammad Nur Shodiq, Mohammad Nur Muh Fuad Al Haris Mukti, Masetya Nur Hanif, Muhamad Panduardi, Farisqi Pangestu, Yoga Purwaningtyas, Ayu Puspikawati, Septa Indra Rahmad Adhi Sasono Rifqi, Eriz Rifqi, Mochamad Misbahur Rini, Eka Mistiko Riska Arinta Saadah, Lailatus Sepyan Purnama Kristanto Sepyan Purnama Kristanto Setiawan, Wahyu Ade Siregar, Hamdan Maruli Susanto, Eko Bagus Utomo, Agus Priyo Wari, Naris Wibowo, Galih Hendra