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Amri, Saeful
Universitas Muhammadiyah Semarang
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Public Health Social Sciences Transportation Other

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Manajemen SLiMS Perpustakaan Universitas Semarang Amri, Saeful; khoirudin, khoirudin; Prasetyo, Noer
Information Science and Library Vol. 2 No. 1 (2021): Juni
Publisher : UPT Perpustakaan Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/jisl.v2i1.3213

Abstract

Perpustakaan Universitas Semarang [USM] sebagai salah satu perpustakaan perguruan tinggi swasta di Indonesia selama ini telah melaksanakan tugas dalam kegiatan di perpustakaan, dalam kesehariannya perpustakaan USM memilih untuk menggunakan perangkat lunak free and open-source software (FOSS)   yang dapat digunakan untuk membangun sistem otomasi perpustakaan. Dalam 5 tahun terakhir aplikasi Senayan Library Management System (SliMS) terbukti mampu dalam meningkatkan mutu pelayanan, data menunjukkan adanya peningkatan dengan   melihat koleksi bahan perpustakaan rata-rata 5,18 persen pertahun. Sedangkan untuk data koleksi judul sebanyak 24.421 (jumlah 38.668 eksemplar). SliMS terbukti mampu menjadi solusi para pengelola perpustakaan dalam mengimplimentasikan sistem otomasi perpustakaan secara mandiri. Senayan Library Management System adalah pertangkat yang tidak membutuhkan dana besar tetapi cukup komplit dikarenakan selalu megembangkan sistemnya (upgrade) dengan menyesuaikan perkembangan zaman dan disesuaikan dengan kebutuhan para pustakawan.Libraries at the University of Semarang [USM] as one of the libraries of private universities in Indonesia have been carrying out tasks library activities, in their daily lives, the USM library chooses to use free open-source software (FOSS) which can be used to build library automation systems. In the last 5 years, the Senayan Library Management System (SliMS) application has been proven to be able to improve the quality of service, the data shows an increase by seeing the library material collection an average of 5.18 percent per year. Meanwhile, the title collection data were 24,421 (total 38,668 copies). SliMS is proven to be a solution for library managers in implementing the library automation system independently. Senayan Library Management System is a device that does not require large funds but is quite complete because it is always developing the system (upgrading) according to the times and adjusted to the needs of librariansKeywords:  Senayan Library Management System (SliMS); Free Open Source Software (FOSS); Digital Library
PENERAPAN RAPID APPLICATION DEVELOPMENT UNTUK MEMBANGUN SISTEM INVENTORY ONLINE MENGGUNAKAN CODEIGNITER 4 Panata, Helmi Prasetio; Daru, April Firman; Khoirudin, Khoirudin; Amri, Saeful
Information Science and Library Vol. 4 No. 2 (2023): Desember
Publisher : UPT Perpustakaan Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/jisl.v4i2.9132

Abstract

Dalam proses pengelolaan barang inventory produk admin gudang mendata data produk, transaksi penerimaan dan transaksi pengeluaran pada sebuah sistem inventory lama. Sistem inventory harus ada pembaruan karena sistem inventory saat ini belum bisa diakses secara online, selain itu belum tersedia juga fitur QR Code yang penting digunakan untuk mengetahui langsung sisa stok yang tersedia digudang tanpa melihat ke sistem terlebih dahulu. Masalah tersebut yang melatarbelakangi pembuatan aplikasi inventory yang dapat diakses secara online. Aplikasi ini menggunakan CodeIgniter 4 dengan MySQL sebagai database. Pembuatan sistem menggunakan metode Rapid Application Development (RAD). Langkah-langkah yang dilakukan dalam hal ini adalah analisis kebutuhan sistem, perancangan sistem dan pengujian sistem bahasa pemrograman yang digunakan adalah Hypertext Markup Language (HTML) dan Hypertext Preprocessor (PHP). Tujuan penelitian ini adalah terbentuknya aplikasi inventory yang dapat diakses admin gudang, kepala gudang dan sales untuk melihat stok yang tersedia di Toko Bangunan Baja 88 secara online. Semua menu dan fitur dapat dijalankan tanpa kendala yang dibuktikan dengan pengujian blackbox testing.In the process of managing product inventory, the warehouse admin records product data, receipt transactions and expenditure transactions in an old inventory system. According to the author, the inventory system needs to be updated because the current inventory system cannot be accessed online, apart from that, the QR Code feature is not yet available, which is important to use to find out directly the remaining stock available in the warehouse without looking at the system first. This problem is the background for the author to create an inventory application that can be accessed online. This application uses CodeIgniter 4 with MySQL as the database. The system was created using the Rapid Application Development (RAD) method. The steps taken in this case are system requirements analysis, system design and system testing. The programming language used is Hypertext Markup Language (HTML) and Hypertext Preprocessor (PHP). The aim of this research is to create an inventory application that can be accessed by warehouse admins, warehouse heads and sales to see the stock available at the 88 Steel Building Store online. All menus and features can be run without problems as proven by black box testing 
Perbandingan Kerangka Model Klasifikasi untuk Pemilihan Metode Kontrasepsi dengan Pendekatan CRIPS-DM Amri, Saeful
Information Science and Library Vol. 1 No. 1 (2020): Juni
Publisher : UPT Perpustakaan Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/jisl.v1i1.2488

Abstract

Rumah Sakit Ibu dan Anak (RSIA) Kusuma Pradja Semarang dalam kesehariannya memberikan pelayanan reproduksi terpadu di Semarang. Dari banyaknya kepesertaan keluarga berencana (KB) perlu diterapkan pengambilan keputusan menggunakan alat kontrasepsi, dalam hal ini perlu dilakukan pendekatan data mining dengan melakukan komparasi 05 kerangka model algoritma klasifikasi yaitu: Decision Tree, Naive Bayes, K-NN, Random Forest, dan Deep Learning demi mendapatkan algoritma terbaik dalam menentukan metode   kontrasepsi yang tepat untuk pasien RSIA Kusuma Pradja Semarang.  Hasil penelitian menunjukkan bahwa Naive Bayes (NB) merupakan model terbaik dalam menentukan metode kontrasepsi.Kusuma Pradja Semarang Mother and Child Hospital (RSIA) in its daily life provides integrated reproductive services in Semarang. Of the many members of family planning (KB) it is necessary to apply decision making using contraception, in this case a data mining approach needs to be done by comparing 05 framework classification algorithm models namely: Decision Tree, Naive Bayes, K-NN, Random Forest, and Deep Learning in order to get the best algorithm in determining the right method of contraception for RSIA Kusuma Pradja Semarang patients.The results showed that Naive Bayes (NB) is the best model in determining contraceptive methods.
Peran Akses E-Skripsi untuk Mahasiswa Universitas Semarang Selama Perkuliahan Online Amri, Saeful; Rifa i, Ahmad; Hanif, Mohammad Burhan
Information Science and Library Vol. 1 No. 2 (2020): Desember
Publisher : UPT Perpustakaan Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/jisl.v1i2.2809

Abstract

Wabah Corona Virus (Covid-19) yang menyerang melalui penularan penyakit dengan sangat cepat dan dapat mengakibatkan kematian menyebabkan manusia harus menjaga jarak satu dengan lainnya agar tidak terjadi penularan yang sangat cepat, hal tersebut berdampak pada beberapa sektor salah satunya adalah pendidikan. Dalam dunia pendidikan di Indonesia, hingga saat ini masih menerapkan metode belajar dalam jaringan (daring). Akses E-Skripsi Universitas Semarang menjadi salah satu solusi dalam mengatasi kendala keterbatasan akses literatur pada mahasiswa. Studi ini menggunakan metode kualitatif. Data dikumpulkan dengan studi kepustakaan. Temuan data selanjutnya dianalisis dengan pendekatan analisis deskriptif. Hasil studi menunjukkan bahwa akses E-Skripsi dapat memberikan solusi bagi mahasiswa. Selain itu, open access memberikan kemudahan dalam menambah literatur yang dibutuhkan, sehingga mahasiswa tetap produktif dalam menyelesaikan studi dikala pandemi.The Corona Virus (Covid-19) outbreak which attacks through disease transmission very quickly and can result in death causes humans to keep their distance from one another so that transmission does not occur very quickly, this has an impact on several sectors, one of which is education. In the world of education in Indonesia, until now, it is still implementing online learning methods. Access to E-Skripsi at the University of Semarang is one solution in overcoming the constraints of limited access to literature for students. This study uses qualitative methods. Data collected by a literature study. Further data findings were analyzed using a descriptive analysis approach. The study results show that E-Skripsi access can provide solutions for students. In addition, open access makes it easy to add to the literature needed, so that students remain productive in completing studies during a pandemic
OPTIMIZATION OF NAÏVE BAYES USING BACKWARD ELIMINATION FOR HEART DISEASE DETECTION Amri, Saeful; Ningrum, Ariska Fitriyana; Arum, Prizka Rismawati
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 11, No 2 (2023): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.11.2.2023.44-50

Abstract

Heart disease is the main cause of death in humans. Even though preventive measures have been taken such as regulating food (diet), lowering cholesterol, and treating weight, diabetes, and hypertension, heart disease remains a major health problem. There are several factors that cause heart disease, including age, type of chest pain, high blood pressure, sugar levels, ECG test values, maximum heart rate, and induced angina. To reduce the percentage of deaths due to heart disease, we need a system that can predict heart disease. The algorithm used in this research is a combination of the Backward Elimination and Naive Bayes algorithms to increase accuracy in diagnosing heart disease. According to the results of this research, the Naive Bayes algorithm has an accuracy value of 78.90% and an Area Under Curve (AUC) value of 0.86, which is included in the good classification category. Combining the Backward Elimination and Naïve Bayes algorithms has an accuracy value of 82.31% and an Area Under Curve (AUC) value of 0.88.
Data Visualization Excellence: Google Data Studio Workshop At Sekolah Indonesia Kuala Lumpur Amri, Saeful; Fadlurohman , Alwan; Ningrum, Ariska Fitriyana; Purwanto, Dannu; Amri , Ihsan Fathoni; Wardani, Amelia Kusuma; Dhani, Oktaviana Rahma
Journal Of Human And Education (JAHE) Vol. 5 No. 1 (2025): Journal of Human And Education (JAHE)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jh.v5i1.2178

Abstract

The development of information technology and the entry of the industrial revolution 4.0 era has led to the inseparability of human activities related to the use of technology. In today's rapidly growing information age, data is one of the most valuable assets. The ability to collect, analyze, and interpret data is becoming a very important skill not only in the world of work but also in education. Education is the foundation for preparing future generations for increasingly complex global challenges, and a good understanding of data can provide a significant competitive advantage. In schools, the ability to analyze and interpret data is becoming an invaluable skill for students. Along with the development of technology, data visualization has become an effective method to convey information in a more comprehensible manner. In this context, Google Data Studio offers a powerful and easy-to-use tool for creating interactive dashboards that help in analyzing and presenting data. Indonesian Migrant Workers (TKI) are Indonesian citizens who live and work abroad. TKI provide a large contribution of foreign exchange to the country of Indonesia. However, there are problems in the field of education for children whose parents work as TKI in Malaysia, especially education that is relevant to success in terms of opening their own jobs abroad. This is considered important because to get jobs in government agencies or companies in Malaysia, the children of TKI working in Malaysia must compete with job seekers who are Malaysian citizens. One alternative that can be taken to overcome competition in getting jobs is to create your own jobs. Opening your own jobs is not an easy thing. Knowledge and insight about this are needed which are given early on to the children of TKI in school. By teaching Google Data Studio in the form of data visualization to students, they not only learn how to read and interpret graphs and diagrams, but also how to present their own data in a more interesting and informative way. This ability will be very useful in the future, both in academic and professional environments. By providing insight into Google Data Studio to students in schools, these students have the provisions to be able to read data and have the opportunity to work and get decent jobs. As a Community Service activity with an international scope, this activity takes partners in Malaysia, namely the Indonesian School-Kuala Lumpur - SIKL which is located in Sentul, Kuala Lumpur, Federal Territory of Kuala Lumpur. The Community Service Team of Muhammadiyah University of Semarang is very receptive to criticism and suggestions so that the implementation of Community Service in the future can be even better.
Komparasi AHP, SAW, TOPSIS, VIKOR, dan MABAC pada Sistem Pengambilan Keputusan Pemilihan Supplier Obat Purnomo Putro, Dwi; Eka Suryani, Puput; Amri, Saeful
Jurnal Transformatika Vol. 23 No. 1 (2025): July 2025
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v23i1.12220

Abstract

The selection of pharmaceutical suppliers is crucial for ensuring consistent drug availability and maintaining service quality in healthcare facilities. This study offers a comparative analysis of five Multi Criteria Decision Making methods (AHP, SAW, TOPSIS, VIKOR, and MABAC) applied to supplier evaluation based on four key criteria: price, delivery time, receipt accuracy, and product quality. Unlike previous studies that employed individual or dual methods, this research evaluates all five methods using the same dataset to assess consistency, sensitivity, and decision reliability. The results show strong ranking consistency across methods, with AHP and SAW producing identical outputs. TOPSIS and VIKOR offer similar outcomes based on proximity and compromise analysis, while MABAC demonstrates high discrimination power for mid-ranked suppliers. Sensitivity tests confirm ranking stability under moderate weight variations. This study provides practical recommendations for selecting appropriate decision methods in pharmaceutical procurement systems based on operational context and desired decision accuracy.
The Impact of Implementing the Independent Curriculum on Elementary School Students' Learning Outcomes Fisabilillah, Muh. Irodat; Ahmadi; Supriadin; Ridwanulhaq, Alfina Fauziah; Masudah, Nurhidayatul; Nur, Indah Manfaati; Haris, M. Al; Amri, Saeful
Jurnal Ilmiah Pendidikan dan Pembelajaran Vol. 9 No. 1 (2025): March
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jipp.v9i1.91548

Abstract

The Independent Curriculum is an essential component in Muhammadiyah Elementary Schools in Semarang, supporting the spirit of learning that has developed over time. However, there is an imbalance in student achievement scores between phases that require data-based tracking. This study aims to evaluate the effectiveness of the Independent Curriculum in improving students' cognitive understanding using the factorial design method. This type of research is quantitative descriptive. The research population is Muhammadiyah Elementary Schools in the independent school category, with a sample of four schools selected using the two-stage cluster random sampling technique. Data collection techniques are observation and questionnaires. The application of analysis methods includes descriptive and inferential statistics. The research results show that the implementation of the Independent Curriculum can significantly improve students' cognitive understanding, as reflected in the increase in the average student achievement scores between the 2022/2023 and 2023/2024 academic years. In addition, the analysis of the elementary school phase shows that the Independent Curriculum can support the development of student competencies in stages according to educational needs in each phase, thereby improving the quality of learning.
Pengelompokan Wilayah Kecamatan di Kabupaten Kendal Berdasarkan Hasil Produksi Buah dan Sayur Dengan Metode K-means Clustering Arum, Prizka Rismawati; Nur, Indah Manfaati; Fitriyani, Indah; Amri, Saeful
Jurnal Pengembangan Rekayasa dan Teknologi Vol. 7 No. 1 (2023): Mei (2023)
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/jprt.v19i1.8212

Abstract

Indonesia dikenal dengan sebutan negara agraris dimana sebagian besar penduduk bekerja di sektor produksi pertanian. Kabupaten Kendal merupakan salah satu kabupaten di Provinsi Jawa Tengah yang sebagian besar wilayahnya merupakan daerah produksi pertanian yang sangat subur. Data yang digunakan dalam kasus ini adalah hasil produksi produksi pertanian buah dan sayur pada 20 kecamatan di Kabupaten Kendal tahun 2022. Salah satu cara untuk mengetahui potensi produksi pertanian dari wilayah kecamatan di Kabupaten Kendal adalah dengan mengelompokkan wilayah yang memiliki karakteristik hampir sama menggunakan K-means clustering. Tujuannya adalah mendapatkan hasil pengelompokkan yang optimal dari masing-masing kelompok yang terbentuk. Berdasarkan hasil analisis, diperoleh pengelompokkan wilayah kecamatan di Kabupaten Kendal menggunakan K-means menjadi 3 cluster. Dimana Klaster 1 terdiri dari 2 kecamatan dengan identifikasi bawang merah, mangga, pisang, dan jambu air memiliki tingkat persentase hasil produksi buah dan sayuran tertinggi. Klaster 2 terdiri dari 2 kecamatan dengan identifikasi pepaya, nangka, petai, dan melinjo memiliki tingkat persentase hasil produksi buah dan sayuran tertinggi. Dan klaster 3 terdapat 16 kecamatan dengan identifikasi cabai rawit, cabai keriting, memiliki tingkat persentase hasil produksi buah dan sayuran tertinggi. Dengan nilai evaluasi yang didapatkan dari Silhouette Index sebesar 0,5546 yang berarti termasuk kedalam kriteria medium structure.
Projection of PT Aneka Tambang Tbk Share Risk Value Based on Backpropagation Artificial Neural Network Forecasting Result Haris, M. Al; Setyaningsih, Laras Indah; Fauzi, Fatkhurokhman; Amri, Saeful
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 2 (2024): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i2.20267

Abstract

PT Aneka Tambang Tbk (ANTAM) received an award as the most sought-after stock issuer in Indonesia in 2016. That stock continued to attract investors in 2022 due to a 105% increase in net profit and a 19% increase in sales from the previous year. Despite the upward trend, investors still had doubts due to the fluctuating movement of ANTAM's stock prices. Therefore, forecasting was needed to determine the future movement of stock prices. The Backpropagation Neural Network method had good capabilities for fluctuating data types. However, this method has the disadvantage of a lengthy iteration process. To handle this limitation, The Nguyen-Widrow weighted setting was applied to address this constraint. The expected Shortfall (ES) method used the forecasting results to measure investment risk. This research uses ANTAM stock closing price data from May 2, 2018, to May 31, 2023. Based on the analysis results, the best architecture was obtained with a configuration of 5-11-1, using Nguyen-Widrow weight initialization and a combination of a learning rate of 0.5 and momentum of 0.9. This architecture yielded a prediction error based on the Mean Absolute Percentage Error (MAPE) of 1.9947%. Risk measurement with the ES method based on the prediction for the next 60 periods showed that at a 95% confidence level, the risk value was 0.002181; at a 90% confidence level, it was 0.002165; at an 85% confidence level, it was 0.002148, and at an 80% confidence level, it was 0.002132.
Co-Authors AHMADI Ali Imron Alwan Fadlurohman Anawai Basman, Aprilla April Firman Daru Arafat, Amaliah Sholeha Ariska Fitriyana Ningrum Dannu Purwanto Dhani, Oktaviana Rahma Eka Suryani, Puput Fauzi, Fatkhurokhman Fisabilillah, Muh. Irodat fitriani, ine Hanif, Mohammad Burhan Haris, M. Al Ihsan Fathoni Amri Indah Fitriyani Indah Manfaati Nur Khoirudin Khoirudin Khoirudin Khoirudin, Khoirudin M. Al Haris M. Al Haris Mandala Adikara Sencoko Manfaati Nur, Indah Masudah, Nurhidayatul Mohammad Ridwan Musa, Fitri Diana Nur, M. Saifudin Panata, Helmi Prasetio Prasetyo, Noer Prizka Rismawati Arum Purnomo Putro, Dwi Puspitasari, Listi Putri, Agata Dwi Putri Putro, Dwi Purnomo Rahman , Budiono Ridwanulhaq, Alfina Fauziah Rifa i, Ahmad Rohani, Imam Safira, Rahma Sawiah Adam, Asriyanti Sitti Sahara Supriadin Supriadin Supriyadin, Supriyadin Wardani, Amelia Kusuma