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All Journal snimed Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI J I M P - Jurnal Informatika Merdeka Pasuruan PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat JUSTIN (Jurnal Sistem dan Teknologi Informasi)
Fadil Indra Sanjaya
Universitas Teknologi Yogyakarta
Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Engineering Law, Crime, Criminology & Criminal Justice Public Health Social Sciences

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Anotasi Wilayah Melanoma dengan Komputasi Ekstraksi Ciri Pengolahan Citra PH2 Heksaputra, Dadang; Sanjaya, Fadil Indra
Seminar Nasional Informatika Medis (SNIMed) 2018
Publisher : Magister Teknik Informatika, Universitas Islam Indonesia

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

Abstract

Kanker menjadi penyebab utama kematian dan terus mengalami kenaikan. Berdasarkan data statistik, kematian diakibatkan kanker tergolong tinggi. Hasil investigasi dan pengujian instrumen kuesioner dasar oleh badan penelitian kesehatan didapati sejumlah 1,4% penduduk Indonesia menderita kanker. Media Indonesia (2017) memberitakan melanoma merupakan jenis penyakit paling mematikan. Penyebaran melanoma tergolong sangat cepat menyerang organ lain. Sel kanker melanoma menyerang bagian sel warna kulit atau dikenal dengan sel melanosit. Melanoma dikategorikan sebagai jenis kanker ganas. Telah ditemui 119 kasus melanoma sejak 2005. Melanoma menjadi sebab dari 75% kematian pada kanker kulit.Pada penelitian anotasi wilayah melanoma dengan komputasi ekstraksi ciri pengolahan citra dermatologi akan dilakukan penerapan algoritma berdasarkan analisis model. Anotasi wilayah melanoma dengan komputasi ekstraksi ciri pengolahan citra dermatologi PH2 melalui beberapa tahapan. Tahapan tersebut meliputi 1) penyiapan sumber referensi jurnal/buku, 2) pembuatan design interface & perancangan sistem, 3) implementasi pemrograman dari hasil perancangan design. Tahap pengujian anotasi wilayah melanoma dengan komputasi ekstraksi ciri pengolahan citra dermatologi PH2 menggunakan metode single decision threshold (one feature) dengan fiturnya berupa daerah segmentasi penyakit. Pengujian dan validasi ini dilakukan oleh gold standard pakar dermatologi (ground truth). Pengujian lebih ditekankan pada hasil kinerja dengan single decision threshold (one feature) dan reaksi sistem bug pada aplikasi. Tahap perawatan memastikan tidak terdapat kesalahan dalam pengembangan sistem.Nilai dari gold standar sebagai pembanding hasil analisis dengan kinerja sistem menunjukan hasil relatif baik. Rata-rata validasi pengujian menunjukan presentase 96.41%. Hasil ini membuktikan model dapat digunakan untuk segmentasi wilayah kanker melanoma. Pendekatan model anotasi wilayah melanoma dengan komputasi ekstraksi ciri pengolahan citra dermatologi sebagai alternatif untuk membantu ahli klinis khususnya bidang dermatologi penyakit kulit melanoma.
Prediksi Rerata Harga Beras Tingkat Grosir Indonesia dengan Long Short Term Memory fadil indra sanjaya; Dadang Heksaputra
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 7 No 2 (2020): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v7i2.388

Abstract

Fluctuations in prices of food staples, especially rice price which is uncontrolled, have an impact on losses for producers and consumers. To be able to bridge these problems requires the right decision making. Prediction is one element that can be used in supporting the right decision making. Predictions in decision making are based on existing data in the present and the past so that they can be used to describe conditions that are in line with the objectives to be achieved. With accurate rice price predictions, it is expected that decision makers will be able to decide on good policies or take preventive actions to minimize losses. In this study examines the prediction of rice prices at the Indonesian wholesale level using the Recurrent Neural Network Long Short Term Memory (RNN LSTM) approach. In this study, the data used is the average rice price at the Indonesian Wholesale / Wholesale Trade Year 2010-2020 obtained from the Indonesian statistical center. The results obtained from this study indicated that LSTM method can be used to predict the price of rice at the Indonesian wholesale level quite well.
Sistem Pendukung Keputusan Untuk Mengukur Permintaan Produk Pada e-Commerce dengan Fuzzy Inference System: (Studi Kasus Orebae.com) Fadil Indra Sanjaya; Dadang Heksaputra; Muhammad Fachrie; Sulistyo Dwi Sancoko; Nuzula Afini; Zahra Septa Hati
J I M P - Jurnal Informatika Merdeka Pasuruan Vol 7, No 1 (2022): MARET
Publisher : Fakultas Teknologi Informasi Universitas Merdeka Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37438/jimp.v7i1.404

Abstract

Measuring product demand is an important process for e-commerce companies to assess product viability in the future production. Measuring product demand can assist e-commerce companies to produce and developing new products based on market potential. Decision maker usually only using their best seller product as indicator to estimate future market trend. But in the fact future market trend will not only based on best seller product, but also there several criteria which is needs attention too. In order to use several criteria to estimate market trend, need some analysis so it will take a long time. With Decision Support System (DSS), decision making will be easier and faster. In this research the DSS takes into consideration the following input variables:  Total Sales (TS), Rating (R), Viewed (V), Total Comments (TC) and output Product Demand (PD). Once the Fuzzy Inference System model has been developed, an assessment of the variables is made through testing 1-years data, which allows verifying how the variables behave in the system under study, and their impact on the output variables. Through the application of Fuzzy Inference System in DSS regarding the modeling several criteria that impact product demand, it is possible to increased efficiency and maximizing profitKeyword— DSS, Fuzzy Inference System, Tsukamoto, e-Commerce, Product Demand
Inovasi Naive Bayes Classifier dalam Prediksi Rating Game untuk Pengalaman Gaming yang Lebih Menarik Febri Liantoni; Dini Erlinawati; Yuliana Rizki Ikhsanty; Fadil Indra Sanjaya; Mulia Sulistiyono
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 11, No 3 (2023)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/justin.v11i3.67228

Abstract

Ada beberapa jenis game yang muncul dan dibuat untuk menarik perhatian para gamers. Beberapa permainan mampu mengobati rasa lelah, panik, sedih, bosan, dan kebanyakan mengisi waktu luang. Penelitian ini bertujuan untuk mengembangkan dan menerapkan metode Naive Bayes Classifier yang inovatif dalam prediksi rating game. Dengan menggunakan pendekatan yang memberikan rekomendasi rating yang akurat untuk setiap permainan yang akan dirilis, dengan tujuan meningkatkan pengalaman gaming pengguna. Dataset yang digunakan dalam penelitian ini mencakup informasi tentang game-game yang telah dirilis sebelumnya, termasuk rating yang diberikan oleh para pengguna. Hasil eksperimen menunjukkan bahwa metode Naive Bayes Classifier yang dikembangkan kami memiliki kinerja yang baik dalam memprediksi rating game. Penelitian ini memiliki potensi untuk meningkatkan pengalaman gaming pengguna dengan memberikan rekomendasi rating yang akurat. Dengan menggunakan metode Naive Bayes Classifier yang inovatif diharapkan dapat membantu pengguna dalam membuat keputusan yang tepat tentang permainan yang akan mereka mainkan.
Precision Marketing Model using Decision Tree on e-Commerce Case Study Orebae.com Fadil Indra Sanjaya; Anna Dina Kalifia
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 5 (2023): October 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i5.4531

Abstract

The development of the industrial world towards industry 4.0 has resulted in changes in the lifestyle of the wider community in carrying out their activities through digital media, one of which is shopping. This has an impact on the emergence of many business actors in the e-Commerce field, which brings its own challenges to stay alive and face the competition. The demands for innovation in competitive competition are also increasingly diverse with various approaches ranging from technology, social science, management science, and even artificial intelligence. One form of innovation that is widely carried out by e-Commerce today is looking for an ideal and effective form of marketing, where the form of marketing itself is considered less able to accommodate e-Commerce needs. One form of real innovation in finding the ideal and effective marketing is precision marketing. Precision marketing itself is marketing that is carried out by utilizing data where consumers are the center of preference for data collection. In fact, many of the e-commerce companies that were launched were unable to keep up with the competition because they were unable to develop marketing strategies and eventually went bankrupt. Therefore, we need a special way to bridge these problems so that e-Commerce can stay alive, especially for e-Commerce classified as Small and Medium Enterprises (SMEs). This research will focus on developing a precision marketing model in e-Commerce for small businesses, namely orebae.com which can be used as a tool in the development of marketing strategies. This research was carried out using a machine learning approach by adopting a decision tree algorithm. The results of this study showed that the precision marketing model for orebae.com based on customer preferences can be used to increase the number of sales of orebae.com and to reduce marketing costs.
Implementasi Sistem Monitoring Potensi, Ancaman, dan Demografi Desa Wisata Jatimulyo Berbasis Data Driven: Implementation of Data-Driven Monitoring System for Potential, Threats, and Demographics of Jatimulyo Tourism Village Muhammad Zakariyah; Fadil Indra Sanjaya; Anna Dina Kalifia; Fariddudin Ar-Razi Ab; Taufik Hidayah; Elfan Fanhas Khoeri; Muhammad Nurjaman
PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Vol. 9 No. 2 (2024): PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat
Publisher : Institute for Research and Community Services Universitas Muhammadiyah Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33084/pengabdianmu.v9i2.5946

Abstract

Village development and regional governance are central to Indonesia's national development agenda. However, in practice, monitoring demographic data, potential resources, and potential threats often transpires without the utilization of technology, yielding less accurate information. Furthermore, numerous villages, including Jatimulyo Tourism Village in Kulon Progo, have yet to fully embrace technology to harness the full potential of their local resources. Within this context, a pressing need exists for technological innovations to leverage the power of data in facilitating informed decision-making. The primary objective of this community engagement endeavor is to establish a data-driven village monitoring system to enhance the efficacy and efficiency of village monitoring processes while simultaneously promoting transparency, accountability, and community participation. The data-driven approach facilitates the collection of precise, automated data. Technology is anticipated to play a pivotal role in rectifying inaccuracies in information, offering crucial support to local government authorities and tourism managers in making well-informed decisions. This community service initiative's tangible outcome is creating a village monitoring system dashboard designed to facilitate decision-making processes and foster greater community involvement. Moreover, it is envisioned that this undertaking will maximize rural development and regional governance, instigate data-driven decision-making practices, foster the development of a robust village ecosystem, and ultimately enhance the overall well-being of the residents of Jatimulyo Tourism Village.
Co-Authors Anna Dina Kalifia Dadang Heksaputra Dadang Heksaputra Dini Erlinawati Elfan Fanhas Khoeri Fariddudin Ar-Razi Ab Febri Liantoni Heksaputra, Dadang Muhammad Fachrie Muhammad Nurjaman Mulia Sulistiyono Nuzula Afini Sulistyo Dwi Sancoko Taufik Hidayah Yuliana Rizki Ikhsanty Zahra Septa Hati