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All Journal TEKNIK INFORMATIKA Jurnal Simetris JURNAL DERIVAT: JURNAL MATEMATIKA DAN PENDIDIKAN MATEMATIKA Prosiding SNATIF NUMERICAL (Jurnal Matematika dan Pendidikan Matematika) Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi JURNAL MANAJEMEN (EDISI ELEKTRONIK) Shirkah: Journal of Economics and Business Simtek : Jurnal Sistem Informasi dan Teknik Komputer STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Jurnal Teknologi Informasi dan Multimedia Jurnal Informatika dan Rekayasa Elektronik Seminar Nasional Teknologi Informasi Komunikasi dan Administrasi [SEMINASTIKA] G-Tech : Jurnal Teknologi Terapan JUKI : Jurnal Komputer dan Informatika Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat TIN: TERAPAN INFORMATIKA NUSANTARA Infotech: Journal of Technology Information Riset Pendidikan Bahasa dan Sastra Indonesia (Repetisi) Simpatik: Jurnal sistem Informasi dan Informatika Buletin Sistem Informasi dan Teknologi Islam Journal of Management and Digital Business Duta.com : Jurnal Ilmiah Teknologi Informasi dan Komunikasi Duta Abdimas: Jurnal Pengabdian Masyarakat Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Innovative: Journal Of Social Science Research Nusantara Journal of Computers and its Applications Jurnal INFOTEL SmartComp CSRID Jurnal Sosialita: Jurnal Kajian Sosial dan Pendidikan Journal of Information Technology Jurnal Teknik Informatika dan Teknologi Informasi
Nurmalitasari Nurmalitasari
Universitas Duta Bangsa Surakarta
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Rancang Bangun Sistem Informasi Geografis Untuk Pemetaan Lokasi Sosialisasi Pasien Rumah Sakit Umum Islam Banyubening Boyolali (Studi Kasus : RSUI Banyubening) Ali Muhdi; Eko Purwanto; Nurmalitasari Nurmalitasari
Jurnal DutaCom Vol 15 No 1
Publisher : LPPM Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (890.591 KB) | DOI: 10.47701/dutacom.v15i1.2003

Abstract

Teknologi SIG mengintegrasikan operasi pengolahan data berbasis database yang biasa digunakan saat ini, seperti pengambilan visualisasi yang khas serta berbagai keuntungan yang mampu ditawarkan analisis geografis melalui gambar-gambar petanya. Setiap seminggu sekali Rumah sakit Banyubening Boyolali melakukan proses pencatatan dan penulisan data sosialisasi rumah sakit tersebut masih menggunakan buku dan menggunakan peta berukuran besar yang di pajang di ruang marketing hal tersebut memiliki kelemahan dalam hal penggunaan material seperti ruang dan kertas menumpuk membuat pencarian data pun kurang efektif sesuai kebutuhan. Tujuan menerapkan SIG diharapkan dapat Membantu mempetakan tempat yang belum terjangkau promosi oleh Marketing Rumah Sakit Umum Islam Banyu Bening Boyolali serta meningkatkan efisiensi dan efektifitas instansi untuk bagian marketing. Metode yang digunakan dalam penelitian ini adalah metode UML (Unifield Modeling Language). Aplikasi yang dibangun menggunakan bahasa pemrograman PHP dengan database MySQL. Hasil penelitian ini adalah sebuah Sistem Informasi Geografis Pemetaan Lokasi Persebaran Pasien Rumah Sakit Umum Islam Banyubening Boyolali dapat memberikan informasi yang akurat guna untuk memperluas area promosi rumah sakit kepada masyarakat umum.
Prediksi Performa Mahasiswa Menggunakan Model Regresi Logistik Nurmalitasari Nurmalitasari; Eko Purwanto
Jurnal Derivat: Jurnal Matematika dan Pendidikan Matematika Vol. 9 No. 2 (2022): Jurnal Derivat (Desember 2022)
Publisher : Pendidikan Matematika Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/jderivat.v9i2.2639

Abstract

Prediction of student performance is an important thing for a university. This is because it can help a university to prevent or treat students who are at risk of failing in their studies early. This study aims to predict student performance at Duta Bangsa Surakarta University (UDB). The model used in this study is a logistic regression model. Logistic regression is a mathematical modelling method used to determine the relationship between a binary dependent variable and one or more independent variables. The results showed that the logistic regression model could be used to predict student performance with MAPE by 8%.  Keyword: Student Performace, Logistic Regression, UDB, MAPE
Sistem Informasi Prediksi Stok Sparepart Motor Menggunakkan Metode Single Moving Average Yusmawan Dwi Suseno; Eko Purwanto; Nurmalitasari Nurmalitasari
Bianglala Informatika Vol 11, No 1 (2023): Bianglala Informatika 2023
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/bi.v11i1.14126

Abstract

Usaha dagang adalah salah satu kegiatan penjualan dan pembelian barang atau jasa dengan tujuan untuk meraih keuntungan. Penjualan sparepart motor adalah jenis usaha yang menjual produk sparepart motor seperti kampas rem, busi, ban, shock, oli mesin dan sparepart kendaraan bermotor lainnya. Prediksi penjualan dibutukan dalam proses persediaan barang agar tidak terjadi kehabisan stok. Penelitian ini menggunakan data penjualan barang sparepart jenis Mpx 2 periode 2021 jangka waktu periode Juli – Desember. Proses prediksi dalam penelitian ini mengunakan metode perhitungan SMA (Single Moving Average). Perhitungan prediksi bulan Juli 2021 sampai Januari 2022 dihitung menggunakkan Rumus Single Moving Average didapatkan hasil 117,8333. Hasil perhitungan Mean Absolute Deviation (MAD) adalah 2.777773. Berdasarkan perhitungan pengukuran nilai akurasi menggunakkan metode MAPE (Mean Absolute Percentage Error) Hasil Nilai MAPE yaitu 2,45 maka sistem prediksi pada studi kasus menunjukkan hasil dengan kategori Sangat Baik karena nilai 2,45 termasuk kedalam klasifikasi Sangat Baik. Berdasarkan hasil pengujian pengguna menggunakan kuesioner yang terdiri atas pengujian dari sisi admin (15 responden) dengan nilai 96% dan pengujian pengguna dari sisi pemilik dengan nilai 100% maka dari itu sistem yang dibangun dapat dikatakan baik, mudah di pahami, dan sangat membantu kinerja proses prediksi stok barang di ARTHA MOTOR Karanganyar.Kata Kunci : Sistem, Informasi, Prediksi, Single, Moving, Average Trading business is one of the activities of selling and buying goods or services to make a profit. Sales of motorcycle spare parts is one type of trading business, a trading business engaged in the sale of motorcycle spare parts itself conducts buying and selling activities for spare parts to maintain motorcycles such as tires, brake linings, spark plugs, shocks, engine oil, and many more such as study sites. the case in this study, namely in ARTHA MOTOR Karanganyar ARTHA MOTOR is a trading business engaged in the sale of motorcycle spare parts owned by individuals. ARTHA MOTOR is a trading business that is progressing at this time, it can be seen from the amount of inventory available. Based on the results of interviews with the business owners, it was stated that there were many requests for spare parts, so ARTHA MOTOR tried to meet customer needs by completing the types of spare parts and increasing the stock of goods available at the store so that they were no longer out of stock. Utilization of information technology through the Information System can help the spare part prediction process by applying the SMA (Single Moving Average) calculation model, from the spare part sales data obtained from the calculation, ACF (Autocorrelation Function) & PACF (Partial Autocorrelation Function) no lag that cuts or outside the red interval line. Therefore, the data can be said to be stationary data and the calculation results from ACF & PACF obtained MAPE with length 6 of 2.4509.Keywords: System, Information, Prediction, Single, Moving, Average
IMPLEMENTASI DATA MINING CLUSTERING UNTUK MENGETAHUI POTENSI PRODUKTIFITAS KACANG TANAH DI INDONESIA Herliyani Hasanah; Nurmalitasari Nurmalitasari; Nugroho Arif Sudibyo
NJCA (Nusantara Journal of Computers and Its Applications) Vol 5, No 1 (2020): Juni 2020
Publisher : Computer Society of Nahdlatul Ulama (CSNU) Indonesia

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Abstract

Kondisi produktifitas kacang tanah yang mengalami fluktuasi, pemerintah perlu memberlakukan kebijakan tertentu di bidang pertanian. Dengan kebijakan tersebut diharapkan dapat mewujudkan ketahanan pangan tingkat nasional. Salah satu informasi yang dapat digunakan untuk mendukung kebijakan tersebut adalah pengelompokan provinsi di Indonesia berdasarkan hasil panen kacang tanah di Indonesia.  Pengelompokan ini dilakukan karena beragamnya potensi hasil produksi kacang tanah di masing-masing provinsi, sehingga perlu dilakukan pengelompokan untuk mengetahui provinsi mana yang memiliki hasil produksi kacang tanah tertinggi sehingga dapat membantu untuk mengoptimalkan program-program pemerintah dibidang pertanian tanaman pangan. Pengelompokan tersebut menggunakan analisis cluster k-means. Dalam penelitian ini simulasi pemetaan menggunakan metode K-Means Clustering berbasis mobile. Proses pemetaan dilakukan berdasarkan 2 (dua) variabel yaitu luas panen (Ha) dan produksi (ton). Hasil pemetaan akan dikelompokkan menjadi dua (2) cluster, yaitu hasil panen tinggi dan rendah. Dari perhitungan manual, aplikasi mobile dan simulasi menggunakan Rapid Miner diperoleh hasil yang sama yaitu cluster 1 meliputi provinsi no 12 (Jawa Barat), 13 (Jawa Tengah) dan 15 (Jawa Timur). Sedangkan sisanya ada 20 data masuk ke cluster 0.
Indonesian news classification application with named entity recognition approach Nurchim Nurchim; Nurmalitasari Nurmalitasari; Zalizah Awang Long
JURNAL INFOTEL Vol 15 No 2 (2023): May 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i2.909

Abstract

Nowadays, many netizens search for news via search engines with countless amounts of information, so it is increasingly difficult to determine when the number of news articles that appear changes very quickly and dynamically. Thus, it is necessary to process the extraction of news information to display the core information of the news. Problems arise, especially in Indonesian, which has a structure of various noun phrase entities with shallow parsing or grammatical induction. Named Entity Recognition (NER) has the opportunity to overcome this because it can extract news entities in depth, starting from proper nouns in text documents containing information search, machine translation, answering questions, and automatic summarization. This study aims to apply NER in Indonesian language news classification. This study uses Design-Based Research whose process includes (1) pre-implementation, (2) design, (3) implementation and revision, and finally, (4) reflection and evaluation. This application was developed on the platform python, streamlit, BeautifulSoup, gnews, and spacy library. The results of application accuracy testing have an F1-score value of 89.69% for all entities consisting of place, figure, day, date, and organization.
Prediksi Harga Rumah di Kabupaten Karanganyar Menggunakan Metode Regresi Linear Ashary Vermaysha; Nurmalitasari Nurmalitasari
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2023
Publisher : Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta

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Abstract

This research aims to apply linear regression method in predicting house prices in Karanganyar Regency, using land area, building area, number of bathrooms, number of bedrooms, and electricity capacity as independent variables. A dataset consisting of house prices and the independent data was used in the analysis. The research results show that the predicted house prices have a relatively low level of accuracy, with an error of 651614542,27. To improve the prediction accuracy, three steps are recommended. First, adding data variations from several real estate websites to expand the sample and covered house characteristics. Second, expanding the dataset by adding supporting variables such as dates, which provide information about market trends and fluctuations. Finally, exploring alternative prediction algorithms that are more supportive than linear regression. The conclusion of this research is that although linear regression can be used to predict house prices in Karanganyar Regency, the accuracy level still needs to be improved. Therefore, the proposed recommendations need to be implemented to improve the prediction model. Thus, it is expected that house price predictions in Karanganyar Regency will become more accurate and useful for use in the property market.
Analisis Kemiskinan Menggunakan Metode Algoritma Clustering K-Means Dwiki Rasya Rahadian; Nurmalitasari
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2023
Publisher : Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta

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Abstract

Poverty has a broad and serious impact on the lives of individuals and society. When people live in poverty, they may face difficulties meeting basic needs, such as adequate food, adequate housing, and proper education. These limitations can negatively impact physical and mental health, education, employment opportunities, and overall quality of life. The purpose of this study is to find out the grouping of districts/cities that have similar characteristics based on the 2019 poverty indicators. This research uses data obtained from the BPS (Central Bureau of Statistics). The method used is the k-means clustering method which is a clustering partition method for grouping objects into k clusters. Based on the research results, the characteristics of each cluster were grouped based on the poverty indicator values in several districts/cities in 2019 as many as 2 clusters. Formed from 20 districts/cities in cluster 1 and 29 districts/cities in cluster 2. Cluster 1 has the characteristics of Low Work Challenges, with Low Per Capita Expenditure Rates and Low Unemployment Rates while Cluster 2 has the characteristics of High Job Challenges, with Per Capita Expenditure Levels High and High Non Working Rate.
Analisis Faktor-Faktor yang Mempengaruhi Produksi Padi di Sumatera Menggunakan Metode Regresi Linier Mohammad Yusuf Nugroho; Nurmalitasari
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2023
Publisher : Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta

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Abstract

In research data must go through a processing process so that it can be used in the research. The data used must be valid to be able to produce an appropriate solution. This study aims to analyze the factors that influence rice production in paddy fields. The island of Sumatra has more than 50 percent of agricultural land in each province with the most dominant main food commodity being rice, while the remainder is corn, peanuts and sweet potatoes. Agricultural products in Sumatra are very vulnerable to climate change which can affect cropping patterns, planting time, production and yield quality. Climate change can have a negative impact on the production of these basic commodities. Moreover, an increase in the earth's temperature due to the impact of global warming which will affect the pattern of precipitation, evaporation, water runoff, soil moisture, and climate variations which are very fluctuating as a whole can threaten the success of agricultural production. Predictions of agricultural yields for food commodities are heavily influenced by climate change. The method used for analysis is Linear Regression and also uses the python library.
Analisis Faktor Utama Penentu Harga Rumah di Surakarta Menggunakan Principal Component Analysis Muhammad Rais Ramadhani; Nurmalitasari
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2023
Publisher : Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta

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Abstract

Residence is often referred to as one of the primary needs. Therefore, it is important to formulate a well-planned series of actions to ensure that every family has a dwelling of their own. In this planning process, an analysis of the factors determining house prices is necessary to serve as a basis for finding suitabel housing. The objective of this research is to conduct a Principal Component Analysis (PCA) on the main factors determining house prices using the dataset from Surakarta. The identified factors that contribute to house prices include the number of bedrooms, the number of bathrooms, the size of the house, the distance from the house to the city center, and the distance from the house to the nearest hospital. The analysis is performed using the PCA library in Python, resulting in two main factors with a variance above 90%. The first component represents accessibility factors, specifically the distance from the house to the city center and the distance from the house to the nearest hospital. On the other hand, the second component represents spatial and accommodation factors, including the number of bedrooms, the number of bathrooms, and the size of the house.
Prediksi Pemberian Dana Pengembangan Ke Universitas Menggunakan Model Regresi Logistik Rico Yoga Pradana; Nurmalitasari Nurmalitasari
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2023
Publisher : Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta

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

Abstract

Perguruan tinggi atau universitas tentu saja ingin mendapatkan suatu penghargaan atau dana pengembangan dari pihak terkait dikarenakan dengan melakukan pemberian dana pengembangan kepada perguruan tinggi dapat meningkatkan sarana dan prasarana universitas dan menghasilkan lulusan mahasiswa dengan ilmu yang kompeten. Penelitian ini digunakan untuk memprediksi penyaluran dana pengembangan ke universitas yang tepat menggunakan model machine learning regresi logistik. Hasil penelitian menunjukkan bahwa keberhasilan siswa dengan menggunakan model regresi skor akurasi model 54%.
Co-Authors AA Sudharmawan, AA Abdullah Sajad Adenta Sari, Nur Avia Aditya Gema Pratama Afu Ichsan Pradana Agus Mardiyono Ahmad Tomi Aines Nafis Husna Alliya, Sania Qorrii Aprilisa Arum Sari Ashary Vermaysha Asmara Andhini Awang Long, Zalizah Bangun Prajadi Cipto Utomo Bima Setya Gumelar Dwi Hartanti Dwiki Rasya Rahadian Ega Muhammad Atsir Eko Purwanto Eko Purwanto Fadilah Nuria Handayani FAULINDA ELY NASTITI Hapsari, Theresia Pinaka Ratna Ning Hasanah, Herliyani Imam Sujadi Intan Diasih Irawan, Ridwan Dwi JOKO SUSANTO Lindha Juniarta Suseno Lucky Marsella Miftahul Hasanah Miftakhul Jannah, Ulfarida Moh Muhtarom Mohammad Yusuf Nugroho Muhammad Hafizh Al Mustofa Muhammad Ilham 'Aziiz Alfarobi Muhammad Ilham Arsyam Muhammad Rais Ramadhani Novemy Triyandari Nugroho Nugroho Arif Sudibyo Nugroho, Mohammad Yusuf Nurchim Permatasari, Hanifah Pipin Widyaningsih Rafel Fernando Rahmawati Desi Tri Wulandari Ratna Puspita Indah Rico Yoga Pradana Rifki Hidayat Rizqi Saputra Sajad, Abdullah Sari, Nur Avia Adenta Septi Dwi Supriati Setiawati, Neha Poetri Singgih Purnomo Sofa Marwati SRI SUMARLINDA Sulami, Atik Syaiful Nur Wardani Syawaludin, M Ainur Tariq Taufik Hidayat Tri Atmojo Kusmayadi Tri Wulandari, Rahmawati Desi Ulfarida Miftakhul Jannah Utami, Maulinda Devi Vihi Atina Viona Putri Ardiana Widya Monika Sari Yuliana Dewi Proboningrum Yusmawan Dwi Suseno Zalizah Awang Long Zalizah Awang Long