Garuda - Garba Rujukan Digital

p-Index From 2021 - 2026

2.957

P-Index

This Author published in this journals

All Journal ComEngApp : Computer Engineering and Applications Journal Jurnal Buana Informatika Jurnal Informatika Jurnal Sarjana Teknik Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Teknologi Prosiding SNATIF Jurnas Nasional Teknologi dan Sistem Informasi InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan JOIV : International Journal on Informatics Visualization Jurnal Ilmiah FIFO JRST (Jurnal Riset Sains dan Teknologi) Jurnal Sisfokom (Sistem Informasi dan Komputer) IJISTECH (International Journal Of Information System & Technology) JUMANJI (Jurnal Masyarakat Informatika Unjani) Jurnal Pemberdayaan: Publikasi Hasil Pengabdian Kepada Masyarakat Jurnal Inti Talafa : Jurnal Teknik Informatika Building of Informatics, Technology and Science Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) IJISTECH Techno Urecol Journal. Part E: Engineering Jurnal Informatika: Jurnal Pengembangan IT ABDIMASTEK

Lisna Zahrotun

Universitas Ahmad Dahlan

Author-ID : 487711

Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Social Sciences Other

Published : 36 Documents Claim Missing Document

Claim Missing Document

Articles

1 2 3 4

Penerapan Metode Single Linkage dengan Manhattan Distance Similarity dalam Mengelompokkan Trens Topik Kerja Praktik Tsani Elvia Nita; Lisna Zahrotun
JRST (Jurnal Riset Sains dan Teknologi) Volume 5 No. 1 Maret 2021: JRST
Publisher : Universitas Muhammadiyah Purwokerto

Data laporan judul kerja praktik (KP) biasanya hanya terkumpul di perpustakaan dan jarang dipubilkasikan ke mahasiswa, hal ini menyebabkan kesulitan bagi mahasiswa yang akan mengkasesnya. Berdasarkan permasalahan tersebut, maka dibuatlah suatu program pada penlitian ini untuk pengelompokkan Trend Topik. Metode yang digunakan dalam penelitian ini adalah Manhattan Distance Similariy dan Single Linkage. Sebelum masuk tahapan text mining, perlu dilakukan perancangan diantaranya perancangan basis data dan antar muka (interface). Tahapan dan text mining adalah mengumpulkan data (collect data), penguraian teks (text mining), penyaringan teks (text filtering), pembobotan kata (calculate term count), similarity, pengelompokan, dan pengujian. Hasil dari penelitian ini adalah program yang dapat mengolah data judul KP menjadi pola kelompok Trend Topik KP. Dari 905 data yang di dapatkan, terbentuk 7 kelompok yaitu Sistem Informasi, Multimedia, Jaringan, Web, Kewirausahaan, Magang, dan Pelatihan. Tetapi dari hasil pengujian Purity Test didapatkan nilai sebesar 0,267, yang artinya Manhattan Distance Similarity dan Single Linkage kurang cocok untuk mengelompokkan Judul KP.

Fp-Growth Algorithm For Searching Book Borrowing Transaction Patterns And Study Program Suitability Lisna Zahrotun; Anna Hendri Soleliza Jones
IJISTECH (International Journal of Information System and Technology) Vol 5, No 5 (2022): February
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

The current development of data has reached a sizeable amount. This is due to the development of the world of information technology which consists of data in it. One technique that can handle abundant data is data mining. Data mining methods are widely used to perform large amounts of data analysis. In the academic field, analysis can be used to determine the patterns of students and lecturers. Whereas in library transactions, analysis can be carried out to determine the patterns of existing book borrowing. This is done to determine the tendency of students with certain study programs to borrow any uku transactions. In this study, the aim of this research is to analyze the patterns of borrowing books from the Ahmad Dahlan University library, which includes borrowing transaction data and the book owner's study program. In addition, in this study, a percentage analysis of the suitability of the book borrower study program and the book owner's study program was also carried out. The stages in this research include data collection, data cleaning, data selection, data transformation, searching for association patterns using the FP-Growth method and pattern evaluation. The test used in this research is the lift ratio. The results of this study are publications in international journals that are in the draft process. Apart from that, the results of this study provide information on the analysis of patterns of lending books in libraries using the FP-Growth method. The resulting pattern is 103 patterns with a support count value of 5 and a confident 10% with the 2 itemset rule, this means that the level of book borrowing is still low. While the results of the analysis of the suitability of books in the study program with the borrower were 31% in accordance with the study program, namely Pharmacy and Public Health Sciences, meaning that there were 69% of students who borrowed books from the library that were not in accordance with their study program.

Penerapan Data Mining Untuk Penentuan Penerima Beasiswa Dengan Metode K-Nearest Neighbor (K-NN) Fiqriany Karepesina; lisna zahrotun
Techno (Jurnal Fakultas Teknik, Universitas Muhammadiyah Purwokerto) Vol 24, No 1 (2023): Techno Volume 24 NO.1 April 2023
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/techno.v24i1.9084

Dalam beberapa instansi pengelolaan beasiswa masih menggunakan microsoft excel dan pemilihan penerima beasiswa masih menggunakan seleksi administrasis ecara manual. Salah satu pengolahan data dalam jumlah yang besar adalah data mining. Oleh karena itu penelitian ini bertujuan untuk menerapkan data mining dengan metode k-nearest neighbor (K-NN) untuk penentuan penerima beasiswa. Metode pengumpulan data dengan metode data private, studi literatur, dan wawancara. Tahapan data mining yaitu cleaning, selection, transformation, knowledge deiscovery, pattern evaluation, knowledge presentation. Pengujian sistem yaitu dengan menggunakan confusion matrix untuk mengetahui nilai akurasi. Hasil dari penelitian ini adalah klasifikasi untuk menentukan penerima beasiswa menggunakan metode k-nearest neighbor dimana hasil pengujian dengan confusion matrix dan kurva ROC (Receiver Operation Characteristic) di peroleh hasil akurasi terbaik sebesar 77% dengan nilai AUC (Area Under Curve) 0,90 dari jumlah data training 115, data testing 555 dan nilai K adalah 4. Karena nilai AUC berada diantara rentang 0.80 – 0.90, maka metode tersebut termasuk dalam kategori good classification (sangat baik).

Strategy for improving and empowering MSMEs through grouping using the AHC method Zahrotun, Lisna; Amanatullah, Yosyadi Rizkika; Linarti, Utaminingsih; Soleliza Jones, Anna Hendry
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 13, No 1 (2024): MARET
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v13i1.2021

The high number of migrants in the city of Yogyakarta has resulted in increased opportunities for Micro, Small and Medium Enterprises (MSMEs) in Culinary and Handicrafts. The large amount of data collected by the Cooperative Office, which reached thousands, caused inas to have difficulties in determining what training was needed by MSMEs and also difficulties in choosing which MSMEs would receive training held by the Cooperative Office. In addition, the Yogyakarta Cooperatives and UMKM Office had difficulties in selecting which UMKM needed to receive these trainings. Grouping can be used as a strategy in selecting MSMEs and determining training according to their individual needs. The purpose of this study was to group SMEs using the Agglomerative Hierarchical Clustering Single Linkage method and its application to provide recommendations for MSME groups to the Yogyakarta Cooperative and MSME Office. The results of the recommendations for the number of groups can be used in providing implementation, design, and evaluation of the development and empowerment of MSME data in the City of Yogyakarta. This study uses the Agglomerative Hierarchical Clustering Single Linkage method. The stages in this research are Load Data, Cleaning Data, Data Selection, Transformation Data, Clustering Process with AHC single linkage, Silhouette Coefficient, and Knowledge Representation. This research resulted in 2 group recommendations from a total of 1336 Culinary MSME data and 3 group recommendations from a total of 145 Handicraft MSME data. The results of the silhouette score test in the Culinary Sector are included in the strong structure category with a value of 0.79 and the Crafts Sector is included in the Medium Structure category with a value of 0.615. From the number of these groups, recommendations were obtained for improving a service in increasing MSMEs, especially those with a turnover of less than 10 million, marketing purposes within the Yogyakarta area, and not having financial assistance from the government. The high number of immigrants in the city of Yogyakarta has resulted in increased opportunities for Micro, Small and Medium Enterprises (MSMEs) in the Culinary and Crafts sector. The large number of MSMEs creates increasingly higher competitiveness. Apart from that, the large amount of data collected by the Department of Cooperatives and MSMEs, which reaches thousands, causes the Department to have difficulties in efforts to improve and empower these MSMEs. Grouping is one method that can be used as a strategy in mapping MSMEs, especially in efforts to improve and empower MSMEs through training conducted by the Department. The aim of this research is to group MSMEs using the Agglomerative Hierarchical Clustering (AHC) method in an effort to achieve strategies for improving and empowering MSMEs. The focus of this research is[a1] MSMEs in the craft sector and MSMEs in the culinary sector. The results of this research provide 2 group recommendations from a total of 1336 Culinary MSME data and 3 group recommendations from a total of 145 Craft MSME data. The silhouette score test results in the Culinary Sector are in the strong structure category with a value of 0.79 and in the Crafts Sector are in the Medium Structure category with a value of 0.615. From the number of groups in the two MSMEs, strategies were obtained to improve and empower MSMEs, especially those with a turnover of less than 10 million, marketing objectives within the Yogyakarta area, and not having capital assistance from the government. [a1]the result of the revision of the Abstract

Implementasi Data Mining untuk Estimasi Produksi Cabai menggunakan Metode Exponential Smoothing Lintang Fauziyatu Azmi; Zahrotun, Lisna
Jurnal Buana Informatika Vol. 15 No. 01 (2024): Jurnal Buana Informatika, Volume 15, Nomor 01, April 2024
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jbi.v15i1.8333

Cabai merupakan komoditas hortikultura yang banyak dibudidayakan dan berpengaruh pada fluktuasi ekonomi di Kabupaten Sleman. Dalam upaya menstabilkan fluktuasi harga dan pertumbuhan ekonomi di Kabupaten sleman, maka perlu dilakukan estimasi produksi cabai untuk periode ke depan. Estimasi produksi cabai yang dilakukan dalam penelitian ini menggunakan tiga jenis metode Exponential Smoothing dengan kombinasi parameter alpha, beta, dan gamma. Penelitian ini bertujuan untuk mengembangkan model estimasi produksi cabai dengan menggunakan Single, Double, dan Triple Exponential Smoothing. Hasil penelitian ini menunjukkan bahwa Triple Exponential Smoothing adalah metode yang paling tepat digunakan untuk mengestimasi produksi cabai di masa mendatang, dengan persentase tingkat error sebesar 6.5%.

Pengelompokkan Mahasiswa Akademik Keperwatan Berdasarkan Asal Sekolah dan Nilai Akademik Menggunakan Metode Clustering K-Means Zahrotun, Lisna; Fajri, Yunus; Jones, Anna Hendri Soleliza; Purwaningsih, Eni
Building of Informatics, Technology and Science (BITS) Vol 3 No 3 (2021): December 2021
Publisher : Forum Kerjasama Pendidikan Tinggi

Nursing Academic of Karya Bakti Husada (AKPER KBH) Bantul is one of the academics that opened the 2000 department. Based on an interview with the Director of AKPER KBH, the registration requirements to become a student of the Academy are currently graduates from all majors and all high schools. AKPER KBH has not analyzed student data whether there is a relationship between high school history and passing grades of GPA as an evaluation material in the learning process, although at this time with the variation of new students causing difficulty in learning difficult compared to before, while GPA achievement is very important in finding job after graduation. The purpose of this study is to classify academic data of AKPER students based on data on school origin, GPA scores, and Medical Surgical Nursing II (KMB II), Mental Nursing II (Kep Jiwa II), Child Nursing II (Kep Anak II), Maternity Nursing II (Kep Maternitas II), and Medical Surgical Nursing ( KMB V). The stages in this study include data collection, data search, data selection, data transformation, data grouping using the K-Means method and knowledge representation, the test used in this study is the purity test. From the experiments conducted, the accuracy value is 0.924 with the number of clusters 3

Decision Support System for Selection of Villages Receiving Plant Seed Assistance in Belitung Regency Using the Simple Additive Weighting (SAW) Method Aryandita, Muhammad Dwinda Agust; Zahrotun, Lisna
Urecol Journal. Part E: Engineering Vol. 3 No. 1 (2023): January-June
Publisher : Konsorsium LPPM Perguruan Tinggi Muhammadiyah 'Aisyiyah (PTMA) Koordinator Wilayah Jawa Tengah - DIY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53017/uje.254

The Belitung Regency Regional Food and Agriculture Security Service has a program for distributing plant seed assistance. This program aims to support the Food Security program in Belitung Regency. The problem encountered in the distribution of this assistance was in the selection of prospective beneficiaries which was carried out subjectively and based on activity alone, this resulted in the distribution of assistance not being on target. This study aims to create a decision support system that can select villages as recipients of plant seed assistance using the Simple Additive Weighting method. The stages of this research started with problem identification and research objectives, data collection, data analysis, determining criteria and weighting, then implementing the SAW method, system design, implementation, system testing, and conclusions. The results of this study are a system that can rank selected villages as recipients of plant seeds. With this system, the selection of villages that will receive plant seed assistance from the Food Security and Agriculture Service of the Belitung Regency can be carried out easily and efficiently. Based on tests carried out using Usability Testing with SUS obtaining a value of 81.75 and included in the Acceptable category. Tests using validity carried out also have the same results between manual calculations and calculations from the system so that the results obtained are stated to be valid. The last test was carried out using the Blackbox method which yielded a value of 100% in terms of the functionality of all the features in the system. Looking at the three test results, it can be concluded that the system that has been built is feasible to use.

Analisis Data Masuk Kuliah Dengan Data Kelulusan Mahasiswa Menggunakan Metode Apriori Dwiyanti, Ryzky Aulia; Zahrotun, Lisna; Linarti, Utaminingsih
Jurnal Sarjana Teknik Informatika Vol. 12 No. 3 (2024): Oktober
Publisher : Program Studi Informatika, Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jstie.v12i3.26400

Evaluasi keberhasilan penyelenggara program studi di perguruan tinggi merupakan aktivitas yang sering dilakukan oleh Fakultas Y Universitas X. Fakultas melakukan evaluasi dengan bentuk evaluasi studi terhadap mahasiswa. Namun selama adanya proses evaluasi studi tersebut, jumlah kelulusan mahasiswa Fakultas Y setiap tahunnya masih di bawah 50%, sehingga perlu dilakukan identifikasi penyebab mahasiswa tidak lulus tepat waktu. Identifikasi tersebut dilakukan dengan pencarian hubungan antara data mahasiswa sebelum masuk kuliah dan data kelulusan mahasiswa. Penelitian ini melakukan analisis pola asosiasi antara data masuk kuliah dengan data kelulusan mahasiswa Fakultas Y tahun 2014-2015 dengan data kelulusan mahasiswa tahun 2018-2019. Penelitian ini memperoleh pola asosiasi yaitu pada dataset prodi U. Tahapan penelitian meliputi seleksi data, pembersihan data, transformasi data, penerapan metode apriori dan pengujian menggunakan lift rasio. Penelitian ini menghasilkan pola asosiasi data masuk kuliah dengan data kelulusan yang dapat dijadikan rekomendasi prodi U. Data masuk yang saling berelasi dengan data kelulusan lama studi diantaranya adalah nilai rata-rata mata Pelajaran Bahasa Indonesia, nilai rata-rata kimia, nilai computer range, nilai rata-rata fisika dibawah 50 dan nilai rata-rata matematika range 50-<60. Sedangkan datamasuk yang saling berelasi data kelulusan nilai IPK diantaranya nilai rata-rata elektronika, nilai rata-rata computer dibawah 50 dan berasal dari SMA. Dengan nilai lift yang dihasilkan yaitu rata-rata 1,01-2,20 yang artinya berkorelasi positif.

Penerapan Data Mining Dalam Pemberian Kelayakan Kredit Nasabah Pada Badan Usaha Milik Desa Gedong Gincu Dengan Metode Naïve Bayes Hanifatun, Farras; Zahrotun, Lisna
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 1 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i1.5939

BUMDes Gedong Gincu is a rural business that provides savings and loan services to village communities. BUMDes Gedong Gincu in determining customers is still very simple, namely by looking at where the customer comes from and how close they are to previous customers who have applied for credit, so it is not a guarantee whether or not the new customer is eligible to get a loan at BUMDes Gedong Gincu. Another problem that occurs is the lack of thoroughness by BUMDes administrators in assessing customers. The aim of this research is to apply the Naïve Bayes method in determining the credit worthiness of customer applications. The method used in this research is Naïve Bayes with testing using a confusion matrix. Research stages include data selection, data cleaning, data transformation, application of the Naïve Bayes method, testing. The result of this research is an application that can facilitate BUMDes Gedong Gincu in evaluating the feasibility of providing credit. The test results using 186 data using the confusion matrix method, an accuracy of 67% was obtained. However, based on SUS testing by users, they got a result of 82.25. This indicates that this application is good and suitable for use by BUMDes Gedong Gincu.

Pelatihan Pembuatan Game Sederhana bagi Guru-Guru TK ABA Ngabean Zahrotun, Lisna; Soyusiawaty, Dewi; Ramadhan, Imam; Hapsari, Intan
ABDIMASTEK Vol. 2 No. 2 (2023): Desember
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32528/abdimastek.v2i2.1323

Pendidikan memiliki peran krusial dalam membentuk masa depan generasi muda, terutama di tengah perubahan cepat di era digital. Guru memegang peran penting dalam memastikan bahwa siswa tidak hanya memahami materi pelajaran, tetapi juga memperoleh keterampilan hidup yang relevan dengan tuntutan kehidupan sehari-hari. Pelatihan ini adalah meningkatkan kompetensi digital guru, khususnya dalam pemanfaatan Scratch untuk pembelajaran yang interaktif dan kreatif. Scratch, sebagai aplikasi pemrograman visual, dirancang untuk mempermudah pembelajaran dasar-dasar pemrograman, terutama bagi pemula dan anak-anak. Melalui blok-blok pemrograman visual, pengguna dapat membuat proyek-proyek interaktif, animasi, dan permainan. Scratch menjadi sarana inspiratif untuk kreativitas, pengembangan kemampuan pemecahan masalah, dan mendorong inovasi dalam proses pembelajaran. Pelaksanaan kegiatan ini menghadapi beberapa tantangan, termasuk kurangnya pemahaman guru terhadap teknologi. Solusi yang diusulkan melibatkan kegiatan pelatihan yang fokus pada penggunaan teknologi bagi guru di TK ABA Ngabean, dengan harapan meningkatkan pemahaman mereka terhadap sistem komputer dan penerapan teknologi dalam pembelajaran. Dengan demikian, pengabdian Masyarakat ini ini bertujuan menggali potensi Scratch sebagai alat pembelajaran dalam pembuatan game sederhana yang mendukung perkembangan digital guru dan mendorong inovasi dalam pendidikan anak usia dini

Co-Authors Amanatullah, Yosyadi Rizkika Anita Rahmawati Anna Hendri Soleliza Jones Ansari Ansari Arfiani Nur Khusna Aryandita, Muhammad Dwinda Agust Dewi Soyusiawaty Dwiyanti, Ryzky Aulia Elyana, Ade Eni Purwaningsih Fajri, Yunus Fiqriany Karepesina Hanifatun, Farras Hapsari, Intan Herri Kurnia Ika Arfiani Ika Kurnia Saputri Indri Dwi Lestari Jones, Anna Hendri Soleliza Juniarti, Rahmat Kurnia, Herri Lintang Fauziyatu Azmi Muhammad Faishal Mushlihudin Mushlihudin Mushlihudin Mushlihudin Mushlihudin, Mushlihudin Mushlihudin, Mushlihudin Purwayoga, Vega Ramadhan, Imam Rusydi Umar Sabila, Liya Yusrina Soleliza Jones, Anna Hendri Soleliza Jones, Anna Hendry Suandi As, Banu Harli Trimulya Taufik Mufti Haryadi Tedy Setiadi Tsani Elvia Nita Utaminingsih Linarti, Utaminingsih

Title

Found 36 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 36 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 36 Documents
Search