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All Journal JIKO (Jurnal Informatika dan Komputer) Jurnal TAM (Technology Acceptance Model) Jurnal Teknologi Komputer dan Sistem Informasi Jurnal Berdaya Mandiri Fahma : Jurnal Informatika Komputer, Bisnis dan Manajemen Jurnal TAM (Technology Acceptance Model) JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi)
Totok Suprawoto
Informatics Department, Universitas Teknologi Digital Indonesia (UTDI), Yogyakarta
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PENGEMBANGAN WISATA TEMATIK SEBAGAI RINTISAN KAWASAN EDUKATIF RAMAH ANAK Faizal, Edi; Suprawoto, Totok; Kurniyati, Nany Noor; Setyowati, Sri
Jurnal Berdaya Mandiri Vol 2, No 1 (2020): Jurnal Berdaya Mandiri (JBM)
Publisher : Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/jbm.v2i1.423

Abstract

Mitra pengabdian PPDM (Program Pengembangan Desa Mitra) ini adalah Tempuran Banyu Kencono dan Kebun Gizi Mandiri yang berlokasi di Desa Pleret Kabupaten Bantul. Mitra 1 merupakan kawasan wisata ditepian sungai (tempuran) dua buah kali (Opak dan Gajah Wong). Sedangkan Mitra 2 merupakan kelompok penggerak PKK sadar gizi. Tujuan kegiatan tahun pertama adalah mengatasi permasalahan kedua mitra yang meliputi Aspek manajemen, promosi, SDM, teknik budidaya dan irisgasi, penanganan pasca panen dan diversifikasi tanaman. Metode pelaksaan melalui pendekatan model participatory rural appraisal, participatory tecnology development, community development, persuasif dan edukatif. Capaian hasil tahun pertama antara lain, (1) terbentuk tim pengelola dan dresscode, (2) tersusun siteplan, (3) tersedia fasilitas playground, (4) tersedia fasilitas budidaya, (5) tersedia fasilitas wisata air dan spot foto, (6) terselenggara event rutin dan insidental, (7) tersedia fasilitas sekretariat, tempat ibadah dan tempat istirahat (gazebo), serta (8) publikasi media cetak dan elektronik (web dan media sosial).
Drop Out Student Clusterization Using the k-Medoids Algorithm Mohammad Guntara; Totok Suprawoto
JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi) Vol 5, No 1 (2022): JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi)
Publisher : JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi)

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

Abstract

Student dropout (resign) is a problem that needs to be addressed as early as possible. The number of students dropping out will decrease the quality of the performance of a university, as well as reduce it as much as possible because it will have an impact on public appreciation. As a first step to reducing it, it requires the clustering of students who experience this. Based on this cluster, a pattern of student tendency to drop out can be identified. The parameters used in this study were the GPA, the study period, the number of credits received, and the number of semesters inactive. To compile a cluster, the k-Medoids algorithm is used with 3 types of clusters. Based on the results of the clustering, it can be seen that the dominance of dropout students is due to GPA <2.00 as much as 38.2% and due to not being active in college as much as 52.2%. To measure the cluster quality, the Silhouette coefficient algorithm is used and the resulting coefficient value is 0.3, meaning that the cluster separation rate weak structure.
KLASIFIKASI DATA MAHASISWA MENGGUNAKAN METODE K-MEANS UNTUK MENUNJANG PEMILIHAN STRATEGI PEMASARAN Totok Suprawoto
JURNAL INFORMATIKA DAN KOMPUTER Vol 1, No 1 (2016): FEBRUARI - AGUSTUS 2016
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (635.192 KB) | DOI: 10.26798/jiko.v1i1.9

Abstract

Analisis cluster merupakan teknik data mining yang bertujuan untuk mengidentifikasi suatu kelompok dari objek yang memiliki karakteristik yang sama. Jumlah kelompok yang dapat diidentifikasi tergantung pada sejumlah data dan jenis dari objeknya. K-Means adalah salah satu metode clustering data yang dibagi kedalam bentuk satu atau lebih cluster/kelompok yang memiliki karakteristik sama. Clustering data mahasiswa menggunakan metode K-Means, terdiri dari nilai rerata ujian nasional (UN) dan indeks prestasi kumulatif (IPK) mahasiswa. Penelitian ini menggunakan data mahasiswa angkatan 2014/2015. Kemudian diperoleh kesimpulan bahwa kelompok mahasiswa dengan nilai rerata UN yang rendah memiliki pengaruh terhadap prestasi akademik mahasiswa yang rendah pada jenjang diploma-3( D-3)  dan strata-1 (S-1). Jika mahasiswa memiliki nilai UN yang tinggi maka prestasi akademik mahasiswa juga tinggi pada semua jenjang. Dari hasil pengelompakan berdasarkan daerah asal sekolah IPK rata-rata yang tertinggi berasal dari propinsi Daerah Istimewa Yogyakarta (DIY) dan Jawa Tengah (Jateng). Kata kunci: K-Means, Cluster, IPK, Nilai Rerata UN
PROTOTIPE INTEGRASI DATA MORBIDITAS PASIEN PUSKESMAS KEDALAM DATA WAREHOUSE DI DINAS KESEHATAN KABUTEN BANTUL Totok - Suprawoto; Enny Itje Sela; Syamsu Windarti
JURNAL INFORMATIKA DAN KOMPUTER Vol 2, No 2 (2017): SEPTEMBER - JANUARI 2018
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1087.488 KB) | DOI: 10.26798/jiko.v2i2.64

Abstract

   Bantul District Health Office (DHO Bantul) is one of the agencies that currently experiencing problems to obtain accurate and current health information. Reports to be made routinely by puskesmas further recapitulated in Bantul Health Office are reports on outpatient morbidity such as the report of Integrated Disease Surveillance (STP), disease report by type, and others.From result of analysis and design of data warehouse based on fact constellation schema which include dimension: time, patient, age group, disease and puskesmas, furthermore can be analyzed further for the purpose of decision making using data mining. Furthermore, it can also be used to analyze patient data from various dimensions (time, patient, age group, illness and puskesmas), and analyze the growth of patient number from each period of time which is useful for the management of DHO Bantul. Successfully built prototype data integration morbidity of outpatient Puskesmas. To ease the burden of the surveillance officer to make a report to DHO Bantul has made the application of Integrated Disease Surveillance (STP). While some types of reports are needed every periodic can be simulated using instaview or pentaho report.
PROTOTIPE INTEGRASI DATA MORBIDITAS PASIEN PUSKESMAS KEDALAM DATA WAREHOUSE DI DINAS KESEHATAN KABUTEN BANTUL Totok Suprawoto; Enny Itje Sela; Syamsu Windarti
Jurnal TAM (Technology Acceptance Model) Vol 7 (2016): Jurnal TAM (Technology Acceptance Model)
Publisher : LPPM STMIK Pringsewu

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (985.014 KB)

Abstract

Bantul District Health Office (DHO Bantul) is one of the agencies that are currently having problems to obtain health information that is accurate and current. The report should be made regularly by the health center then recapitulated in Bantul Health Office is a statement of outpatient morbidity such as Integrated Disease Surveillance (STP) report, a report based on the type of disease and others. The increasing number and complexity of morbidity data in Bantul Health Office environment, as well as the importance of planning and decision making, it is necessary to analyze and design data further using the data warehouse. From the analysis and design of data warehouse based on the fact constellation schema that includes dimensions: time, patient, age, disease and health centers, can then be further analyzed for purposes of making decisions using data mining. Furthermore, it can also be used to analyze patient data from multiple dimensions (time, patient, age, disease and health centers), and to analyze the growing number of patients from each period of benefit to the management of Bantul Health Office.
Perancangan Ulang User Interface Sistem Informasi Akademik dengan Metode Design Thinking Edy Prayitno; Prayitno, Edy; Suprawoto, Totok; Perdana, Ivan Jaka
Jurnal Informatika Komputer, Bisnis dan Manajemen Vol 22 No 2 (2024): Mei 2024
Publisher : LPPM STMIK El Rahma Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61805/fahma.v22i2.132

Abstract

Sistem informasi akademik memainkan peran penting dalam mendukung aktivitas pendidikan di perguruan tinggi. Namun, banyak sistem yang ada saat ini menghadapi masalah antarmuka pengguna (user interface) yang tidak intuitif, yang menyebabkan kesulitan navigasi dan ketidakpuasan pengguna. Penelitian ini bertujuan untuk merancang ulang antarmuka pengguna sistem informasi akademik menggunakan metode Design Thinking, yang berfokus pada pendekatan berpusat pada pengguna.Proses penelitian melibatkan lima tahap utama: empati, definisi, ideasi, prototipe, dan pengujian. Tahap empati dilakukan dengan mengumpulkan data dari 150 pengguna sistem untuk memahami kebutuhan dan permasalahan mereka. Selanjutnya, permasalahan didefinisikan dan solusi inovatif dihasilkan melalui sesi brainstorming pada tahap ideasi. Prototipe antarmuka baru kemudian dikembangkan dan diuji oleh pengguna untuk mendapatkan umpan balik. Hasil penelitian menunjukkan peningkatan signifikan dalam kepuasan dan efisiensi pengguna. Desain baru berhasil meningkatkan kemudahan navigasi, estetika, dan kinerja sistem. Dengan rata-rata kepuasan pengguna meningkat sebesar 50%, penelitian ini membuktikan bahwa Design Thinking adalah pendekatan yang efektif untuk menciptakan solusi desain antarmuka yang lebih baik dan relevan. Temuan ini memberikan panduan praktis bagi institusi pendidikan dalam meningkatkan sistem informasi akademik mereka.
PROTOTIPE INTEGRASI DATA MORBIDITAS PASIEN PUSKESMAS KEDALAM DATA WAREHOUSE DI DINAS KESEHATAN KABUTEN BANTUL Totok Suprawoto; Enny Itje Sela; Syamsu Windarti
Jurnal TAM (Technology Acceptance Model) Vol 7 (2016): Jurnal TAM (Technology Acceptance Model)
Publisher : LPPM STMIK Pringsewu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/jurnaltam.v7i0.65

Abstract

Bantul District Health Office (DHO Bantul) is one of the agencies that are currently having problems to obtain health information that is accurate and current. The report should be made regularly by the health center then recapitulated in Bantul Health Office is a statement of outpatient morbidity such as Integrated Disease Surveillance (STP) report, a report based on the type of disease and others. The increasing number and complexity of morbidity data in Bantul Health Office environment, as well as the importance of planning and decision making, it is necessary to analyze and design data further using the data warehouse. From the analysis and design of data warehouse based on the fact constellation schema that includes dimensions: time, patient, age, disease and health centers, can then be further analyzed for purposes of making decisions using data mining. Furthermore, it can also be used to analyze patient data from multiple dimensions (time, patient, age, disease and health centers), and to analyze the growing number of patients from each period of benefit to the management of Bantul Health Office.
Drop Out Student Clusterization Using the k-Medoids Algorithm Mohammad Guntara; Totok Suprawoto
JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi) Vol 5, No 1 (2022): JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi)
Publisher : Institut Bakti Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/jtksi.v5i1.1069

Abstract

Student dropout (resign) is a problem that needs to be addressed as early as possible. The number of students dropping out will decrease the quality of the performance of a university, as well as reduce it as much as possible because it will have an impact on public appreciation. As a first step to reducing it, it requires the clustering of students who experience this. Based on this cluster, a pattern of student tendency to drop out can be identified. The parameters used in this study were the GPA, the study period, the number of credits received, and the number of semesters inactive. To compile a cluster, the k-Medoids algorithm is used with 3 types of clusters. Based on the results of the clustering, it can be seen that the dominance of dropout students is due to GPA 2.00 as much as 38.2% and due to not being active in college as much as 52.2%. To measure the cluster quality, the Silhouette coefficient algorithm is used and the resulting coefficient value is 0.3, meaning that the cluster separation rate weak structure.
Co-Authors Edi Faizal Edy Prayitno Edy Prayitno Enny Itje Sela Kurniyati, Nany Noor Mohammad Guntara Perdana, Ivan Jaka Sri Setyowati Syamsu Windarti