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All Journal Jurnal Media Elektro : Journal of Electrical Power, Informatics, Telecommunication, Electronics, Computer and Control System QARDHUL HASAN: MEDIA PENGABDIAN KEPADA MASYARAKAT Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Tematik : Jurnal Teknologi Informasi Komunikasi Journal of Soft Computing Exploration Journal International of Lingua and Technology Digital Transformation Technology (Digitech) Bulletin of Informatics and Data Science Darma Abdi Karya: Jurnal Pengabdian Kepada Masyarakat
Sussolaikah, Kelik
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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Image Classification using Machine Learning Algorithms to Detect Cloud Types Agustina, Nova; Ihsan, Candra Nur; Sussolaikah, Kelik
TEMATIK Vol 10 No 2 (2023): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Desember 2023
Publisher : LPPM POLITEKNIK LP3I BANDUNG

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

Abstract

Study of atmospheric are currently growing rapidly to analyze the negative effects of climate change, weather and air quality. Unstable atmospheric conditions have a negative impact, as extreme weather. The combination of technology and analysis of atmospheric conditions is currently developing rapidly. While atmospheric research using machine learning technology and algorithms is advancing swiftly, challenges persist in identifying the optimal machine learning model for precise cloud type classification. The application of Machine Learning algorithms in atmospheric research has been widely carried out to predict wind direction and cloud imagery to detect weather using satellite data. Detecting cloud type is important for predicting the upcoming weather. However, to detect the type of cloud, it is necessary to choose the algorithm with the best performance. This study applies the Convolutional Neural Network (CNN) with EfficienNetB3 method, Support Vector Classifier (SVC), XGBoost Classifier (XGB), Extra Tree Classifier (ETC), Random Forest (RF), and Decision Tree (DT) algorithms in classifying cloud images to detect clouds type. The method used in this research involves an experimental approach in the hope of gaining a deeper understanding of the factors that influence the performance of machine learning models in classifying cloud types. The dataset used in this research is 1500 cloud data (1200 training data, 300 testing data). Researchers conducted a comparison of algorithms to find out the best algorithm performance in classifying cloud type images. The results showed that doing the CNN algorithm showed better performance with an average accuracy got of 81.03% compared to the SVC algorithm (34.44%), XGB (33.79%), ETC (39.25%), RF (36.18), and DT (29.35%). Our contribution to this research is that we compare machine learning algorithms to detect cloud types along with the impact and characteristics of cloud types from the prediction results.
Pemanfaatan Packages Pada R Programming Untuk Crawling Data Pada Social Media Sussolaikah, Kelik
Building of Informatics, Technology and Science (BITS) Vol 3 No 3 (2021): December 2021
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (397.586 KB) | DOI: 10.47065/bits.v3i3.1035

Abstract

Social media is one of the many sources of data that can be extracted to obtain various information. In R Programming, there are thousands of packages that can be used to crawl social media data, both the default packages and the developer versions. Difficulty in extracting data will result in less than optimal research, so there is a need for adequate tools to support research. R Programming is able to become a bridge for researchers to explore existing tools, both by utilizing packages and building simple algorithms in R programming. Twitter data crawling is done through an API connection on Twitter with R Programming, so that we can get data by entering keywords according to the desired search both in realtime and at certain times as needed. With these packages it makes it easy to research in crawling social media data such as Twitter and other social media
PELATIHAN MARKETPLACE SHOPEE PADA HOME INDUSTRI Sussolaikah, Kelik; Sulistyowati, Nur Wahyuning; Wihartanti, Liana Vivin; Isharijadi; Wulandari, Meilinda Ike; Nugrahaningtyas, Andien
Qardhul Hasan: Media Pengabdian kepada Masyarakat Vol. 8 No. 2 (2022): AGUSTUS
Publisher : Universitas Djuanda

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (287.66 KB) | DOI: 10.30997/qh.v8i2.5310

Abstract

Home industri merupakan unit usaha yang mampu meningkatkan kesejahteraan masyarakat. Desa Sambirejo kecamatan Geger Kabupaten Madiun adalah salah satu desa yang memiliki banyak industry rumahan. Akan tetapi produk-produk yang dihasilkan masih dipasarkan secara manual, sehingga konsumen yang mengetahui produk tersebut masih terbatas. Dalam situasi pandemic Covid-19, kondisi perekonomian mengalami dampak yang cukup signifikan dan hal ini tentu saja berpengaruh pada tingkat penjualan. Tim pengabdian masyarakat berupaya memberikan solusi atas permasalahan tersebut dengan mengadakan pelatihan marketplace shopee. Strategi pemasaran ini adalah pengalaman baru bagi para pelaku usaha dalam upaya memperluas pemasaran yaitu menggunakan aplikasi shopee sebagai media pemasaran online. Pelatihan dilakukan dengan memaparkan materi mengenai entrepreneur dan pengenalan marketplace shopee. Antusiasme masyarakat dalam mengikuti pelatihan sangat tinggi, terlihat dari keberhasilan para peserta pelatihan ketika praktek langsung menggunakan shopee, para pelaku usaha berhasil mengupload produk mereka dan mulai memasarkannya melalui apllikasi shopee yang terinstal pada smartphone mereka. Diharapkan dengan strategi baru ini, penjualan produk akan meningkat dan semakin meningkatkan kesejahteraan masyarakat desa Sambirejo. Kata Kunci: Home industri, Entrepreneur, Marketplace, Shopee
Decision Support System for Student Exchange Selection in Support of Independent Campus using the MAUT and ROC Methods Rohayani, Hetty; Arini, Zaza Mutiara; Sussolaikah, Kelik; Syam, Syahrull Hi Fi
Bulletin of Informatics and Data Science Vol 2, No 2 (2023): November 2023
Publisher : PDSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61944/bids.v2i2.80

Abstract

Independent campus is an off-campus learning activity as an opportunity for students to hone skills in preparation for entering the world of work. One of the programs held is the exchange of students to be able to study on campuses or companies that join the Ministry of Education and Culture, Research and Technology. With the current independent campus program, almost all universities open up opportunities for students to register. However, because there are too many students who register, the campus has difficulty in choosing some students who can be accepted according to the criteria set by the party. For this reason, a Decision Support System is needed that applies the MAUT method along with the use of ROC to produce the best preference value. The calculation of several data samples resulted in the best final utility value in the selection of independent campus student exchanges in Alternative A2 with the best final utility value of 0.9700
PENGENALAN APLIKASI OBYEK WISATA TELAGA NGEBEL BERBASIS VIRTUAL REALITY DAN ALGORTIMA GREEDY Bhanu Setyawan, Mohammad; Permana Putra, Angga Dian; Sussolaikah, Kelik; Zulkarnain, Ismail Abdurrozaq; Cobantoro, Adi Fajaryanto
Jurnal Media Elektro Vol 13 No 1 (2024): April 2024
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jme.v13i1.15364

Abstract

Ngebel Lake in Ponorogo Regency is a tourist destination that is usually visited by many local or non-local tourists. There is great potential to be developed again to introduce this tourist attraction to outside the region in order to attract tourists. Telaga Ngebel requires the main role of promotion and publication out, so it is very necessary for a technology that is able to realize the equal introduction of Telaga Ngebel attractions and is able to describe tourist objects in real terms. The solution is to utilize Virtual Reality technology that can package the potential of tourist attractions in an attractive, attractive and contemporary manner. The technology displays Telaga Ngebel attractions in 3600 with a 3-dimensional object model and the nearest wahan search feature using the Greedy Algorithm with a virtual reality display. In its preparation using SDLC (Software Development Life Cycle). The final result of making this application in the form of Virtual Reality Telaga Ngebel and also games using the greedy algorithm used as an implementation of games that present the charm of Telaga Ngebel. Based on the results of usability test research with the SUS method obtained a score of 51 or in adjective OK criteria.
The Implementation of Duolingo Application to Enhance English Learning for Millennials Nita, Sekreningsih; Sari, Eka Resty Novieta; Sussolaikah, Kelik; Risky, Satrio Muhammad Fathur
Journal International of Lingua and Technology Vol. 2 No. 1 (2023)
Publisher : Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar, West Sumatra, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/jiltech.v2i1.215

Abstract

With the rapid development of information technology, millennials prefer learning english instantly digitally by using an internet connection that can be accessed anyone, anytime and anywhere. The Duolingo application is one of those modern application that facilitate language acquisition by offering an english course model based on everyday life in a simple way. This research used qualitative method with 30 millennial participants and data collection was carried out by giving questionnaires and direct interviews. The results of the study stated learning english with duolingo that 46,67% can given many opportunites for users society, 56,67 % to learn independently and 36,67% can learn outside of the classroom. Positive impact on millennials become more motivated and practice more often and are skilled in applying it in everyday life. Besides that, the mastery of vocabulary becomes more, it is easy to memorize grammar and pronunciation because this application provides acombination of abilities in pronouncing and translating words from pictures. So Duolingo App is a fun combination of text elements with audio-visual questions. With the gamification system offered by Duolingo app, it can help build interest in learning in a way that is comfortable and doesn't get bored easily when studying, especially by millennials.
Implementasi Media Pembelajaran Menggunakan Google Classroom di Era Digital Nita, Sekreningsih; Sussolaikah, Kelik; Sari, Eka Resty Novieta
Digital Transformation Technology Vol. 4 No. 1 (2024): Periode Maret 2024
Publisher : Information Technology and Science(ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/digitech.v4i1.4114

Abstract

Pesatnya perkembangan teknologi saat ini mempengaruhi dunia pendidikan dalam proses pembelajaran secara online (daring). Banyak aplikasi online yang dapat digunakan sebagai media pembelajaran, seperti Google Classroom. Google Classroom online ini membantu para dosen dalam membuat kelompok kelas, mengatur pembagian dosen, mengatur waktu batas pengumpulan tugas, penilaian tugas dan nilai akhir. Sedangkan tujuan dari penelitian ini untuk mengetahui sejauhmana keberhasilan Google Classroom sebagai media pembelajaran online pengganti tatap muka pada perkuliahan “Algoritma & Pemrograman-I”. Subyek penelitian mahasiswa semester 1 kelas 1b berjumlah 33 mahasiswa, Prodi Teknik Informatika UNIPMA. Metode Penelitian menggunakan kualitatif dengan teknik pengumpulan data studi study literatur, observasi, pembuatan media dan angket. Hasil penelitian adalah pembelajaran daring menggunakan Google Classroom. Keuntungan menggunakan Google Classroom bagi mahasiswa dalam melakukan pembelajaran akan lebih mudah, dapat dilakukan dimana saja tanpa terbatas pada ruang dan waktu. Selain itu, Google Classroom dapat membuat para mahasiswa memiliki karakter disiplin dalam pengerjaaan dan pengumpulkan tugas karena dosen dapat mengatur waktu pengumpulan tugas kepada mahasiswa. Hasil dari penelitian menyatakan penggunaan GC belum sepenuhnya menggantikan tatap muka langsung, 67% menyatakan ragu-ragu, namun demikian 85% Setuju jika tampilan dalam GC mudah digunakan untuk pembelajaran online. Secara keseluruhan pemanfaatan Google Classroom dalam pembelajaran pada Era Digital membawa transformasi positif dan membantu menciptakan lingkungan pembelajaran yang lebih adaptif dan interaktif.
Activity-based function point complexity of use case diagrams for software effort estimation Jayadi, Puguh; Dewi, Renny Sari; Sussolaikah, Kelik
Journal of Soft Computing Exploration Vol. 5 No. 1 (2024): March 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i1.252

Abstract

This study proposes a Function Point Analysis (FPA) based software development effort estimation methodology integrated with Use Case Diagrams. These methods include identifying actor activities, classifying those activities into FPA categories, and calculating Unadjusted Function Points (UFP). Followed by the calculation of Technical Complexity Factors (TCF) and Adjusted Function Points (AFP), this study aims to produce more accurate man-hours estimates. Results show a UFP of 162 TCF of 11, AFP of 123.12, and an estimated effort of 1846.8 hours worked, while the actual effort is 1228 hours. Evaluation of estimates using the metrics Mean Magnitude of Relative Error (MMER) 0.34, Mean Magnitude of Relative Error (MMRE) 0.50, Mean Absolute Error (MAE) 618.80, Mean Balanced Relative Error (MBRE) 0.50, Mean Inverse Balanced Relative Error (MIBRE) 0.34, and Root Mean Squared Error (RMSE) 618.80, showed sufficient precision despite the overestimation. The study suggests the need for adjustments in TCF calculations and considering development environment factors in more detail to improve estimation accuracy. These findings are essential in improving the precision of effort estimation methodologies in software development, particularly in projects that use Use Case Diagrams as the primary framework.
Sistem Pendukung Keputusan Pemilihan Laptop dengan Menerapkan Metode Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) Sussolaikah, Kelik; Lubis, Juanda Hakim; Sallaby, Achmad Fikri; Yuliani, Ega; Mesran, Mesran
Journal of Information System Research (JOSH) Vol 6 No 2 (2025): Januari 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i2.6525

Abstract

The lack of knowledge and information regarding laptop specifications makes ordinary people who want to buy a laptop feel confused about determining which laptop suits their needs. As a tool that can be used to select a laptop, a decision support system is needed. In decision support systems there are several methods, one of which can be used is the MOORA method (Multi-Objective Optimization on the basis of Ratio Analysis). In this research, the author will raise a case to find the best alternative from predetermined criteria to determine comparisons by rating existing alternatives using the MOORA (Multi-Objective Optimization on the basis of Ratio Analysis)method. Based on the relative performance scores, Asus Rog GL552JX (A9) obtained the highest score of 0.217 and ranked first. This was followed by Asus A455LD (A4) with a score of 0.21585 and second place, and Acer Aspire E5-551 (A2) with a score of 0.19785 and third place. Acer One 10 S100X (A10) received the lowest score of 0.1042 and ranked last. Thus, Asus Rog GL552JX (A9) can be considered as the best laptop based on the established criteria in this study.
Sosialisasi Pemanfaatan Aplikasi Canva Sebagai Media Pembelajaran UI /UX Bagi Mahasiswa TIF UNIPMA Nita, Sekreningsih; Sussolaikah, Kelik; Untari, Erny; Susanti P, Andita
Darma Abdi Karya Vol. 4 No. 1 (2025): Darma Abdi Karya: Jurnal Pengabdian Kepada Masyarakat
Publisher : LPPM POLITEKNIK LP3I

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/darmaabdikarya.v4i1.2507

Abstract

Di Era digital saat ini yang semakin maju, khususnya di dunia Pendidikan membutuhkan inovasi dan efektivitas dalam pembelajaran. Di Semester IV (empat) prodi Teknik Informatika UNIPMA ada mata kuliah Interaksi Manusia dan Komputer (IMK) mahasiswa mendapatkan materi tentang User Interface (UI) dan User Experience (UX) atau disingkat dengan UI/UX. Mahasiswa merasa kesulitan untuk memahami tentang UI/UX tersebut. Pendidik (dosen) mencoba mencari tools yang tepat bagaimana cara mudah, cepat, efektif serta efisien memahami materi tersebut yaitu dengan memberi sosialisasi menggunakan aplikasi canva. Alasan memakai canva selain berbasis online, fitur sangat lengkap, selalu up to date, mudah dipahami dan dipraktekkan. Metode pembelajaran yang diberikan dengan cara pelatihan dan praktek langsung menggunakan canva dalam pembuatan UI/UX tersebut. Dan terbukti pada perkuliahan semester IV mahasiswa dengan kemandiriannya dapat mengeksplore aplikasi canva secara maksimal. Hasil akhir sangat memuaskan, semua mahasiswa yang mengambil mata kuliah IMK mendapatkan nilai sangat memuaskan yaitu grade A dan lulus ke semester berikutnyai
Co-Authors Agustina, Nova Arini, Zaza Mutiara Cobantoro, Adi Fajaryanto Erny Untari Hetty Rohayani Ihsan, Candra Nur Isharijadi Jayadi, Puguh Juanda Hakim Lubis Liana Vivin Wihartanti, Liana Vivin Mesran, Mesran Mohammad Bhanu Setyawan Nita, Sekreningsih Nugrahaningtyas, Andien Nugrahanti, Fatim Pasyawati, Putri Ramadhani Permana Putra, Angga Dian Renny Sari Dewi Rifai, M. Hafidz Risky, Satrio Muhammad Fathur Sallaby, Achmad Fikri Sari, Eka Resty Novieta Sulistyowati, Nur Wahyuning Susanti P, Andita Syam, Syahrull Hi Fi Wulandari, Meilinda Ike Yuliani, Ega Zulkarnain, Ismail Abdurrozaq