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SISTEM INFORMASI PREDIKSI JUMLAH PENDUDUK BERBASIS WEBSITE Diandra Chika Fransisca; David Kristian Paath; Padosroha Marbun
Prosiding SNST Fakultas Teknik Vol 1, No 1 (2019): PROSIDING SEMINAR NASIONAL SAINS DAN TEKNOLOGI 10 2019
Publisher : Prosiding SNST Fakultas Teknik

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (376.934 KB)

Abstract

Pengendalian dinamika penduduk oleh pemerintah menjadi hal yang penting untuk menjaga kesejahteraan masyarakat. Pemerintah perlu mengambil kebijakan-kebijakan yang relevan terkait dengan pengendalian tersebut. Perhitungan dalam memprediksi jumlah penduduk merupakan salah satu cara dalam pengendalian dinamika penduduk. Website SISIK (Prediksi Populasi Penduduk) merupakan situs yang dapat menyediakan informasi perhitungan prediksi jumlah penduduk dalam suatu wilayah pada waktu tertentu. Tujuan pembangunan website ini untuk menyediakan informasi yang dapat digunakan sebagai salah satu pertimbangan dalam mengambil kebijakan yang relevan. Pengembangan website dalam penelitian ini menggunakan metode pengembangan perangkat lunak prototype yang terdiri dari proses komunikasi, perencanaan secara cepat, pemodelan perancangan secara cepat, pembentukan prototype dan penyerahan serta umpan balik. Hasil dari proses pengembangan website penelitian ini  mampu menyediakan laporan prediksi jumlah penduduk disuatu wilayah dengan cepat dan tepat. Oleh karena itu, website ini dapat menjadi solusi bagi para pengambil kebijakan seperti pemerintah atau pengusaha untuk menentukan keputusan yang tepat dalam bidang terentu. Website SISIK telah diuji menggunakan uji produk dengan nilai 82,45 dimana nilai ini lebih besar dari nilai batas kelayakan yaitu 75.Kata kunci : logistik, penduduk, prediksi, prototype, website. 
OPTIMISASI PORTOFOLIO SAHAM IDX30 DI ERA COVID-19 DENGAN MODEL MEAN-VARIANCE Diandra Chika Fransisca
STATMAT : JURNAL STATISTIKA DAN MATEMATIKA Vol 4, No 1 (2022)
Publisher : Math Program, Math and Science faculty, Pamulang University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/sm.v4i1.18980

Abstract

Investasi merupakan alokasi uang, saham, reksadana atau sumber daya berharga lainya yang disediakan seseorang pada masa sekarang dan menahannya untuk tidak digunakan sampai masa yang ditentukan sehingga mendapat keuntungan (return). Semakin tinggi return yang diterima maka semakin tinggi juga risiko yang diperoleh. Disisi lain, para investor menginginkan tingkat risiko rendah dengan return yang maksimal. Penelitian ini bertujuan untuk mengaplikasikan model Mean-Variance untuk mengoptimisasi lima saham di Indonesia yaitu TLKM, BBRI, KLBF, MNCN, dan UNTR sehingga diperoleh return yang maksimal dan risiko (variansi) yang minimal. Metode yang digunakan dalam model MeanVariance adalah metode Lagrange. Hasil penelitian diperoleh hanya empat saham portofolio optimal dengan komposisi vektor bobot BBRI = 0,13628, TLKM = 0,013628, KLBF = 0,443232, dan UNTR = 0,196662. Komposisi portofolio optimal ini menghasilkan return rataan sebesar 0,001855 dan variansi sebesar 0,0003679. Sedangkan, saham MNCN memiliki rasio antara rataan dan variansi yang paling terkecil dari kelima saham tersebut. Dengan kata lain, saham MNC tidak menghasilkan komposisi portofolio optimal.
Comparative Analysis of Multinomial Naïve Bayes and Logistic Regression Models for Prediction of SMS Spam Pradana Ananda Raharja; Muhammad Fajar Sidiq; Diandra Chika Fransisca
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 3 (2022): Juli 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i3.4019

Abstract

This research was conducted based on a report from the United States Federal Trade Commission regarding fraud through electronic text messages via SMS that fraudsters use to manipulate potential victims. Usually, scammers spread SMS spam as an intermediary for the crime. The development of a supervised learning algorithm is applied to predict SMS spam into three categories, such as SMS spam, SMS fraud, and promotional SMS. The prediction system is dividing into several stages in the development process, including data labelling, data preprocessing, modelling, and model validation. The known accuracy based on modelling using Logistic Regression using a test size of 15% is 99%, using a test size of 20% is 99%, and using a test size of 25% is 98%. The Multinomial Naïve Bayes algorithm's accuracy with a test size of 15%, 20%, 25% is 97%. So, the SMS spam prediction approach uses the logistic regression method, which has the highest accuracy.
Welch powell algoritma aplication to identify the conflict of lesson timetable (case study: informatics engineering, stikom yos sudarso Purwokerto) Diandra Chika Fransisca; Safar Dwi Kurniawan
International Journal of Technology, Innovation and Humanities Vol 1, No 1 (2020): International Journal of Technology, Innovation and Humanities
Publisher : Indonesian Institute For Counseling, Education and Therapy

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (479.278 KB) | DOI: 10.29210/881801

Abstract

The lecture timetable is a requirement which done each semester by an academic system department in a university. The academic system department faces lecture schedule conflict while they are making it. Welsh Powell algorithm is one of graph theory which can be a solution for the academic system department in a university to avoid the conflict. Accordingly, the purpose of the research is to apply the Welch Powell algorithm for detecting lecture schedule conflict in Informatics Engineering major in STIKOM Yos Sudarso in even semester. The researcher uses two stages of the research method in this study: to collect the data and to implement the model. This research collects the needed data from Informatics Engineering students who take the lecture in even semester. While in the implementation, the researcher collects the model data afterward processed with the Welch Powell algorithm. The conclusion of this research is the Welch Powell algorithm is effective to avoid the conflict of the lesson timetable. The algorithm produces chromatic number 8. It means using the Welch Powell algorithm has 8 conditions course scheduling which can be set so that the conflict does not happen.
Modifikasi Model Logisitik Untuk Peramalan Penduduk Diandra Chika Fransisca
Jurnal HUMMANSI (Humaniora, Manajemen, Akuntansi) Vol 1 No 1 (2018)
Publisher : Sekolah Tinggi Ilmu Komputer YOS SUDARSO Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (565.475 KB) | DOI: 10.33488/1.jh.2018.1.30

Abstract

The logistics model can be modified by adding migration factors as a function to the population. This function considers the existence of limited human migration and interaction by the ability of environmental carrying capacity. This model can be completed qualitatively by using the method of point balance analysis and quantitatively by using the exact undesired metodediferensial. Both of these methods give the same result. If the intrinsic growth rate is greater than for migration then for a long period of time, the model will depend on intrinsic growth factor, environmental carrying capacity and migration rate. Furthermore, if the intrinsic growth is small rather than migration then for a prolonged period of time, the model will depend on minus intrinsic growth, environmental carrying capacity and immigration. Then, if migration growth is the same as migration then the model becomes Malthus model.
Optimalisasi Teknologi Cloud pada Tentara Nasional Indonesia di Institut Teknologi Telkom Purwokerto Bita Parga Zen; Trihastuti Yuniati; Diandra Chika Fransisca; Muhammad Eka Purbaya
Indonesian Journal of Community Service and Innovation (IJCOSIN) Vol 2 No 2 (2022): Juli 2022
Publisher : LPPM IT Telkom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (632.436 KB) | DOI: 10.20895/ijcosin.v2i2.660

Abstract

Kebijakan work from home akibat pandemi Covid-19 telah mengubah cara kerja pegawai, tidak terkecuali prajurit TNI di Korem 071/Wijayakusuma. Sistem kerja yang dilaksanakan secara daring memunculkan kebutuhan untuk saling berbagi berkas atau dokumen. Teknologi cloud memudahkan penggunanya untuk melakukan pekerjaan secara daring. Cloud storage, seperti Google Drive, memiliki beberapa fitur, seperti berbagi dokumen yang dapat disinkronisasi otomatis, sehingga pengguna tidak perlu repot mengunggah berkas untuk disebarkan. Selain itu, dengan disimpan di cloud juga dapat mencegah kemungkinan kerusakan atau kehilangan data. Sayangnya, masih banyak pengguna yang belum terlalu familiar dengan teknologi ini. Sebagai salah satu upaya untuk meningkatkan pengetahuan dan keterampilan pengguna, dosen dan mahasiswa Institut Teknologi Telkom Purwokerto (ITTP) mengadakan kegiatan pengabdian masyarakat berupa pelatihan optimalisasi teknologi cloud, dalam hal ini Google Drive, kepada para prajurit TNI di Korem 071/Wijayakusuma. Kegiatan yang dilaksanakan di ruang TT 104-105 kampus ITTP ini diikuti oleh 66 peserta. Peserta dilatih menggunakan Google Drive melalui web browser dan juga melalui perangkat mobile/smartphone. Peserta sangat antusias dengan diadakannya pelatihan Google Drive ini, terlihat dari hasil kuesioner kepuasan peserta yang menunjukkan rata-rata menjawab sangat setuju dan puas dengan pelatihan ini.
A Customer Relationship Management (CRM) Aprroach with the Spiral Model (Case Study: Information System at Optik Sejahtera) Fransisca, Diandra Chika; Linri, Spanica Pamfilia
International Journal of Supply Chain Management Vol 9, No 5 (2020): International Journal of Supply Chain Management (IJSCM)
Publisher : ExcelingTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59160/ijscm.v9i5.5533

Abstract

Optik Sejahtera is a company engaged in the sale of eye sight/ vision aids or often called glasses. In addition to glasses made of stainless and fiber, there are also many manufacturers in Indonesia that produce glasses from wood. The marketing of wood eyewear products still has problems, among which is still many people do not know about this product. This condition led to stagnant sales transactions in Optik Sejahtera. CRM (Customer Relationship Management) approach method is a marketing activity built on four pillars namely identifying, attracting, maintaining and strengthening brand loyalty, or strengthening relationships to achieve mutually beneficial goal. Therefore, information systems are required with the CRM approach method on Optik Sejahtera to increase sales transactions i.e. with spiral models. Spiral model steps are communication with customers, planning, risk analysis, engineering, construction and launch, and customer evaluation. The systems in this study use the MySQL database.  The results of this study based on analysis system of hypothesis test showed before using the system it took 8,6840 minutes and after using the system it only took 4,3197 minutes. It means, there are changes in sales transactions before and after using the information system in Optik Sejahtera. In other words, the information system on Optik Sejahtera could resulted in an increase of sales transactions. In addition, the results of the study in benefit testing obtained a percentage for utilization of 89.98%, effectiveness of 90%, and efficiency of 92.23%. This means that information systems in Optik Sejahtera using CRM approach with spiral models can increase efficiency in sales transactions.
Applications for Detecting Plant Diseases Based on Artificial Intelligence Zen, Bita Parga; Iqsyahiro Kresna A; Diandra Chika Fransisca
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 4 (2022): Article Research: Volume 6 Number 4, October 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i4.11833

Abstract

Agriculture is an activity to manage biological natural resources with the help of technology and labor. The presence of diseases in plants that suddenly inhibit plant growth is alarming to farmers. So, farmers cannot determine what conditions these plants suffer. This study will discuss the implementation of Artificial Intelligence-based plant disease detection software. At this stage, deep learning models are created using cameras matched with objects. The application development is to detect diseases in plants. The fourth step is testing. This application includes the implementation of Convolutional Neural Network and Recurrent Neural Network, which provides Artificial Intelligence architecture to diagnose plant diseases, and offer solutions to those plants from the results of research with tomato plant sample tests obtained four categories of disease Early Blight disease with a prediction of 100%, Bacterial Spots 90%, Healthy 100%, Late Blight 100% a system that can recommend health care related to crops based on images so that it can help farmers identify types of plant diseases. This application can help farmers to reduce crop failure for farmers caused by plant diseases to improve the quality of agricultural and plantation products
Pelatihan Tableau Untuk Visualisasi Data Secara Cepat dan Mudah FRANSISCA, DIANDRA CHIKA; Raharja, Pradana Ananda
SOROT : Jurnal Pengabdian Kepada Masyarakat Vol 3 No 1 (2024): Januari
Publisher : Fakultas Teknik dan Ilmu Komputer (FASTIKOM) UNSIQ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32699/sorot.v3i1.6331

Abstract

Human consumption of data and information has become very large due to the enormous growth of data. On the other hand, the increasing need for data visualization in various information media (online or offline) has also become very interesting. Data visualization is not only about beautifying the appearance of data but also about making data more quickly understood and engaging. Tableau specializes in data visualization, data storytelling and dashboards. Training to operate Tableau can answer the needs of pupils, students, the general public, teachers and lecturers as participants. This training aims for participants to apply interactive data visualization quickly and easily using Tableau in dashboard creation activities to explain data in visual form. The methods used in implementing this training are preparation methods and implementation methods as well as training. As a result of this training, 34 participants learned about the importance of data visualization. They learned Tableau as a data visualization tool and visualization training using Tableau to create self-ordered dashboards for examples of COVID-19 cases worldwide.
Pelatihan Konten Digital Desa Wisata di Desa Karanggayam Menggunakan Canva Fransisca, Diandra Chika; Amrustian, Muhammad Afrizal
Abdiformatika: Jurnal Pengabdian Masyarakat Informatika Vol. 3 No. 1 (2023): Mei 2023 - Abdiformatika: Jurnal Pengabdian Masyarakat Informatika
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/abdiformatika.v3i1.177

Abstract

Desa Karanggayam, Kabupaten Kebumen adalah salah satu desa yang memiliki keindahan alam perbuktian dan curug sebagai desatinasi wisata. Namun, sejak adanya covid-19 pengunjung desa wisata di Desa Karanggayam menurun drastis dan akhirnya ditutup. Hal ini dikarenakan tidak adanya pemasaran desa wisata secara online di Desa Karanggayam, mengingat dengan adanya covid-19 semua akses promosi wisata tidak dibatasi secara offline. Oleh karena itu, pengabdian masyarakat ini penting sekali untuk memanfaatkan konten digital dalam hal ini aplikasi Canva sebagai media promosi secara online yang menarik. Ada tiga tahapan metode dalam pengabdian masyarakat ini yaitu, persiapan, pelaksanaan dan evaluasi. Hasil pelatihan canva menunjukan para peserta semakin tertarik untuk mempromosikan desa wisatanya karena akses edit konten digital yang praktis dan mudah dipahami. Mitra yang terlibat juga menginginkan pelatihan dengan durasi yang lebih lama.