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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer CESS (Journal of Computer Engineering, System and Science) Jurnal Komtika (Komputasi dan Informatika) Jurnal Consulenza : Jurnal Bimbingan Konseling dan Psikologi Journal of Computer System and Informatics (JoSYC) Jurnal ABDIMAS (Pengabdian kepada Masyarakat) UBJ Universitas Muhammadiyah Yogyakarta Undergraduate Conference Proceeding Computing and Information System Journal Jurnal Komtika (Komputasi dan Informatika)
Uky Yudatama, Uky
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Implementasi Sistem Peramalan Pengadaan Kebutuhan Bahan Baku Pangan Dengan Metode Weighted Moving Average Erlinda, Reza Ena; Yudatama, Uky; Arumi, Endah Ratna
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 9 No 2: April 2022
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2022924700

Abstract

Junkyard Auto Park Cafe merupakan salah satu usaha di bidang pariwisata dan kuliner, dalam proses produksi aneka makanan tersebut dibutuhkan bahan baku pangan. Sebulan sekali proses pembelanjaan bahan baku dilakukan dengan jumlah yang telah ditentukan, namun kelebihan dan kekurangan sering terjadi, hal ini dikarenakan penggunaan yang tidak dapat dipastikan. Penelitian ini bertujuan untuk memudahkan dan meminimalisir kesalahaan dalam melakukan proses pendataan serta mengetahui perkiraan kebutuhan bahan baku pangan dalam jangka waktu ke depan sebagai acuan dalam proses pengambilan keputusan manajerial. Dalam proses penelitian ini digunakan salah satu metode forecasting yaitu Weighted Moving Average (WMA) dikarenakan model ini memiliki sifat yang lebih responsive terhadap adanya perubahan data. Hasil dari rekap data laporan penggunaan bahan baku selanjutnya akan dilakukan proses perhitungan matematis untuk menghasilkan suatu nilai peramalan. Dari penelitian ini dilakukan tiga kali pengujian terhadap bobot yang berbeda, dari percobaan yang dilakukan terhadap masing-masing bobot yang diberikan diperoleh hasil akurasi terbaik pada bobot 0,7 0,2 0,3 dengan nilai MSE 0,0302. Hasil penelitian ini dapat membantu untuk memperkirakan jumlah kebutuhan bahan baku yang diperlukan sehingga mempermudah dalam menentukan pembelanjaanya. AbstractJunkyard Auto Park Cafe is one of the businesses in the tourism and culinary sector, in the production process of various foods, food raw materials are needed, the process of purchasing raw materials is carried out once a month with a predetermined amount so that there are often advantages and disadvantages due to erratic use. This study aims to facilitate and minimize mistakes in carrying out the data collection process and to find out the estimated needs for food raw materials in the future as a reference in the managerial decision-making process. Forecasting is a method as a tool in carrying out an efficient and effective planning. In this research process, one of the forecasting methods is used, namely Weighted Moving Average (WMA) because this model is more responsive to data changes. The results of the data recap of the report on the use of raw materials will then be carried out a mathematical calculation process to produce a forecasting value. From this research, three tests were carried out on different weights, from the experiments carried out on each given weight, the best accuracy results were obtained at a weight of 0.7 0.2 0.3 with an MSE value of 0.0302. The results of this study can help to estimate the amount of raw material needed to make it easier to determine the expenditure. 
Prediksi Produksi Biofarmaka Menggunakan Model Fuzzy Time Series dengan Pendekatan Percentage Change dan Frequency Based Partition Harmadji, Dwi Ekasari; Solikhin, Solikhin; Yudatama, Uky; Purwanto, Agus
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 1: Februari 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2023106267

Abstract

Masa depan biofarmasi semakin cerah. Akibat mahalnya harga obat modern, maka permintaan tanaman obat meningkat di dalam dan luar negeri. Hal ini karena biofarmaka banyak digunakan di industri lain, seperti makanan, minuman, dan kosmetik. Konsumen di seluruh dunia termasuk di Indonesia bergerak menuju produk makanan dan kesehatan yang lebih sehat dengan slogan "kembali ke alam". Dengan demikian permintaan tanaman obat sebagai bahan baku industri lainnya juga meningkat. Untuk mengatasi masalah tersebut diperlukan suatu prediksi untuk menentukan besaran kenaikan atau penurunan jumlah produksi komoditas strategis biofarmaka untuk beberapa tahun ke depan, sehingga Memungkinkan analisis pergerakan tren dari perkembangan data sebelumnya. Saat ini belum dijumpai studi peramalan deret waktu untuk memprediksi produksi biofarmaka dengan tingkat akurasi baik. Dalam eksperimen ini kami mengusulkan model peramalan fuzzy time series berdasarkan pendekatan percentage change sebagai himpunan semesta dan frequency-based partition yang dapat memberikan tingkat akurasi peramalan yang tinggi. Prediksi difokuskan pada biofarmaka untuk empat jenis rimpang yaitu Jahe, Lengkuas, Kencur, dan Kunyit yang dinilai menjadi prioritas utama pengembangan tanaman obat di Indonesia. Dalam penelitian ini menggunakan data sekunder yang diperoleh dari Badan Pusat Statistika tahun 1997-2020. Tujuan dari survei adalah untuk memprediksi dan menganalisa perkembangan produksi biofarmaka untuk empat jenis rimpang. Hasil prediksi menunjukan akurasi luar biasa dengan nilai Mean Absolute Percentage Error yang sangat kecil yakni Jahe 0,03%, Lengkuas 0,02%, Kencur 0,14%, dan Kunyit 0,03%. Dengan demikian hasil eksperimen ini dapat berkontribusi dan digunakan bagi pihak yang berkompeten untuk membantu dalam menentukan kebijakan strategis di masa depan. AbstractBiopharmaceuticals' future is brightening. Due to the exorbitant cost of modern treatment, the desire for medicinal herbs is growing. due to their widespread use in different industries such as food, beverages, and cosmetics. Consumers worldwide, especially in Indonesia, are gravitating towards healthier food and health goods. So the demand for medicinal plants as raw materials increases. To solve this issue, a forecast is required for the next few years on the increase or decline in production of strategic biopharmaca commodities. Currently, no reliable time series forecasting study exists for biopharmaca production. To achieve high predicting accuracy, we present a fuzzy time series forecasting model based on percentage change as a universal set and frequency-based partition. Ginger, Galangal, Kencur, and turmeric are predicted to be the most important rhizomes for biopharmaca research in Indonesia. Secondary statistics from the Central Statistics Agency for 1997–2020 This study's goal was to anticipate and analyze biopharmaca synthesis in four rhizomes. The prediction results are incredibly accurate, with Mean Absolute Percentage Error values of just 0.03%, 0.02%, 0.14%, and 0.03% for Ginger, Galangal, Kencur, and Turmeric, respectively. Thus, competent parties can use the outcomes of this experiment to help determine future strategic policies.
Implementasi Metode Dempster-Shafer Untuk Deteksi Kesehatan Mental Pada Mahasiswa Berbasis Web Jalaluddin, Alif; Arumi, Endah Ratna; Sasongko, Dimas; Pinilih, Sambodo Sriadi; Yudatama, Uky; Arif Yudianto, Muhammad Resa
Journal of Computer System and Informatics (JoSYC) Vol 5 No 2 (2024): February 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i2.4830

Abstract

Mental health is a person's soul condition to budaptasi in its environment to feel happy or get the comfort of life, so as not to experience mental disorders. Often mental health is ignored by most people because it is different from physical health that can be seen directly with the eyes and can be identified easily. Lack of awareness of mental health in the life of the people of Indonesia and the assumption that a person who goes to psychologists is a person inseasonable, often the individual who actually undergoes mental health problems reluctant to get help from experts or deny that he does not have mental health problems. Limitations of time and costs are also one of the constraints of a student reluctant to get help from experts like psychologists. Therefore, a web-based expert system is built with a dempster-shafer method to use as detection on the student and allows the user to know whether the user has a tendency of the problem on its mental health or not before the official consultation is required from the expert. Testing Accuracy Comparison System between the results of the system and experts by using 100 correspondents from students at Muhammadiyah Magelang University (UNIMMA) 89% know mental health and 65% have experienced mental disorders. The results of the SRQ29 data used and were spread among campus students, this study has used 20 sample data and produces 70% expert suit compliance. From the results of expert suitability obtained from the calculation of the system by selecting symptoms and automatically the system will calculate the accuracy of the existing Belief Valident in every symptom. Then the system will take decisions based on the results of the largest calculation value.
Metode Cosine Similarity pada Penilaian Essay Perkaderan Ikatan Mahasiswa Muhammadiyah Anggraini, Novi Kusuma; Yudatama, Uky; Maimunah, Maimunah
CESS (Journal of Computer Engineering, System and Science) Vol. 9 No. 1 (2024): January 2024
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v9i1.55475

Abstract

Perkaderan persyarikatan merupakan suatu program yang dilaksanakan oleh Muhammadiyah baik ditingkat pusat maupun bawahnya dan menjadi bagian inti dalam perjalanan organisasi Muhammadiyah. Perkaderan utama di Muhamamdiyah dibagi menjadi 2 (dua) yaitu Darul Arqam dan Baitul Arqam. Dalam pelaksanaannya juga terdapat evaluasi pembelajaran yaitu pre-test dan post-test. Pre-Test dilaksanakan sebelum materi disampaikan, sedangkan post-test dilaksanakan setelah materi disampaikan. Evaluasi ini berbentuk soal esai yang bersangkut pautan dengan materi yang akan diberikan. Jawaban peserta yang bervariasi dan waktu yang padat menjadi tantangan tersendiri untuk mengoreksinya, dan membutuhkan waktu yang lebih banyak lagi ditambah dengan harus memasukkan nilai ke sistem perkaderan secara manual. Penelitian ini menerapkan text mining dengan menggunakan metode cosine similarity untuk melakukan penilaian otomatis pada soal esai pre-test dan post-test. Hasil perhitungan pada soal pre-test mendapatkan hasil tertinggi dengan tingkat persamaan 77,46% oleh peserta 1 pada soal 4 dan peserta 2 pada soal 3, dan post-test dengan hasil tertinggi 100% oleh peserta 1 pada soal 4. Sedangkan untuk hasil 0,0 yang diperoleh beberapa peserta dikarenakan term antar kunci jawaban dan jawaban peserta tidak memiliki persamaan.
Model Struktural Interpretif untuk Menganalisis Faktor-faktor Pengaruh Media Sosial terhadap Self-Esteem Remaja Yudatama, Uky; Sugiarti, Rini; Suhariadi, Fendy
Jurnal Consulenza : Jurnal Bimbingan Konseling dan Psikologi Vol 7 No 2 (2024): September
Publisher : Program Studi Bimbingan dan Konseling FKIP Universitas Islam Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56013/jcbkp.v7i2.3063

Abstract

Self-esteem is an important aspect of adolescent mental health and can be influenced by various factors related to social media use. Through a literature review and interviews, data were collected and then analyzed using the Interpretive Structural Modeling (ISM) approach to build a structural model depicting the interactions among these factors. The literature review identified nine key factors: Feelings of Loneliness, Types of Social Media Interactions, Content Consumed, Social Support from Social Media, Social Comparison, Cyberbullying, Control over Social Media Use, Parental Involvement, Intensity of Social Media Use, and Identity Development. The ISM model revealed that the factor of feelings of loneliness (F1) is at the fourth or most fundamental level in the hierarchy of factors, while the intensity of social media use (F9) is at the highest level. Therefore, the role of parental involvement (F8) is a crucial foundation to address feelings of loneliness (F1), because if adolescents feel lonely, they may turn to social media as an escape, which can negatively impact self-esteem if not properly controlled. These findings are expected to contribute to the development of effective intervention strategies to enhance adolescent self-esteem.
Prediksi Ketersediaan Stok Kayu dengan Metode Backpropogation dan Jaringan Kohonen (Studi Kasus Ud. Wahyu Nugroho Grabag Magelang) Yulfikar, Muhammad; Yudatama, Uky; Artha, Emilya Ully
Jurnal Komtika (Komputasi dan Informatika) Vol 2 No 2 (2018)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v2i2.2598

Abstract

Jaringan syaraf tiruan merupakan salah satu teknologi komputer dalam bidang kecerdasan buatan yang mampu memahami pola data yang rumit. Salah satu kemampuan teknologi JST adalah mampu memprediksi sebuah keluaran berdasarkan pola data pelatihan yang diberikan saat proses pembelajaran sistem. Pada penelitian ini, JST akan mencoba memprediksi persediaan stok kayu. Backpropagation merupakan algoritma pembelajaran terawasi yang dapat memperbaiki bobot pada masing-masing lapisan penghubung hingga diperoleh bobot terbaik dengan minimum error yang telah diberikan. Sedangkan Kohonen merupakan jaringan yang dipakai untuk membagi pola masukan kedalam beberapa kelompok (cluster). Aplikasi ini memiliki struktur jaringan yang terdiri dari 6 neuron masukan, 100 neuron pada lapisan tersembunyi, dan 1 dan 6 neuron pada lapisan keluaran. Jumlah keseluruhan data yakni 365 data, 250 data digunakan untuk data pelatihan, dan 115 digunakan untuk data pengujian. Mesin pemrediksi ini menggunakan iterasi maksimal sampai 100.000 epochs, konstanta pembelajaran 0.5, momentum 0.9, serta tingkat error minimum 0,001. Dengan variasi nilai dari komponen backpropagation dihasilkan prediksi sebesar kurang dari 150m3/bulan., Sedangkan dari bobot yang dihasilkan akan diprediksi dengan metode Kohonen dan menghasilkan prediksi pengeluaran stok kayu perbulan. Berdasarkan hasil pengujian terhadap 115 data pengujian, prosentase tingkat keakuratan sistem adalah 73,9 % . Pengurangan konstanta pembelajaran dan penambahan data pelatihan mungkin dapat meningkatkan keakuratan sistem dalam melakukan prediksi.
Panduan Jalur Angkutan Umum Menggunakan Algoritma Floyd Warshall Fatmala, Fungki; Yudatama, Uky; Burhanuddin, Auliya
Jurnal Komtika (Komputasi dan Informatika) Vol 3 No 1 (2019)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v3i1.3462

Abstract

Public transportation as one of the most easily found transportation for tourists to visit a tourist destination. There are 12 public transportation lines in Magelang. The large number of public transport lines caused problems for tourists to choose which lines of transportation to get in. The purpose of this research is to develop a guide for public transportation for tourist destination in Magelang usin Floyd Warshall Algorithm. Floyd Warshall's algorithm provides the shortest path recommendation by calculating all vertices, then calculating all possible routes from the initial location to the final destination to determine the total distance travelled on each route. After knowing the total distance on all routes, the system will display the shortest path as a recommendation. From the test results obtained that the system being built is feasible to be used and is able to find the shortest route for determining public transport lines in the city of Magelang Angkutan umum sebagai salah satu transportasi yang paling mudah ditemui untuk digunakan wisatawan dalam mengunjungi suatu objek wisata. Terdapat 12 jalur angkutan umum yang ada di Kota Magelang. Banyaknya jumlah jalur angkutan umum tersebut menjadikan permasalahan bagi wisatawan dalam memilih angkutan yang akan digunakan. Tujuan dari penelitian adalah membangun aplikasi panduan jalur angkutan umum untuk tempat wisata di Kota Magelang dengan menggunakan Algoritma Floyd Warshall. Algoritma Floyd Warshall memberikan rekomendasi jalur terpendek dengan melakukan perhitungan dari semua simpul, kemudian melakukan perhitungan pada semua kemungkinan rute dari lokasi awal sampai lokasi akhir untuk mengetahui total jarak yang dilalui pada masing-masing rute. Setelah diketahui total jarak pada semua rute sistem akan menampilkan jalur terpendek sebagai rekomendasi. Dari hasil pengujian diperoleh bahwa sistemyang telah dibangun layak digunakan dan mampu mencari rute terpendek untuk penentuan jalur angkutan umum di Kota Magelang
Media Konsultasi Penyakit Kulit Pada Balita Menggunakan Metode Certainty Factor Utari, Sudi; Yudatama, Uky; Pujiarto, Bambang
Jurnal Komtika (Komputasi dan Informatika) Vol 3 No 1 (2019)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v3i1.3463

Abstract

The skin, which is the largest part of the human body, is the body's first defense against bacterial and virus attacks. When the skin is exposed to the sun, dry weather, or bacteria, the reaction will spread to other parts of the body, and can even result in death if it is too late to be handled especially if the sufferers are children who are very vulnerable to disease. In this study an expert system was implemented to diagnose skin diseases in infants using the certainty factor method. certainty factor method is very suitable for expert systems that diagnose something that is uncertain. This system makes a diagnosis based on the symptoms felt by the user and then calculates certainty factors based on existing symptoms. Based on the test results by making comparisons between manual calculations and the one carried out by the system it is known that 90.22% of the diagnosis results get the same results so that the system is said to be suitable for use.
Sistem Pakar Diagnosis Hama dan Penyakit pada Tanaman Bunga Sedap Malam dengan Dempster Shafer Nindhy Prastiwi, Maulidina; Uky Yudatama, Uky; Agung Prabowo, Nugroho
Jurnal Komtika (Komputasi dan Informatika) Vol 3 No 2 (2019)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v3i2.3470

Abstract

Nightly flower plants are one of the flower plants that are much in demand by the public. However, as time goes by the production of savory flower plants determines which one of the causes is caused by pests and diseases. Introduction of pests and diseases and its control sometimes not all farmers know it. This research develops an expert system that can help farmers diagnose pests and diseases that attack night flowering plants with the Dempster Shafer method. The results of this study are the application of an expert system that uses pests and tuberose flower diseases. This system will issue this edition to the publication of night flower pests and diseases inputted by users. The amount of this trust value is the result of calculations using the Dempster Shafer method. The conclusion in this study is that an expert system using the Dempster Shafer method for approval to release pests and diseases of the nightly flower plants is very helpful in overcoming the problem of improving the quality of the nightly flower production.
OPTIMIZATION OF LAYING DUCKS FEED COMPOSITION USING THE K-MEANS CLUSTERING ALGORITHM METHOD IN SECANG SUBDISTRICT Arifah, Nur; Primadewi, Ardhin; Yudatama, Uky
Computing and Information System Journal Vol. 1 No. 3 (2025): Data Science, UI/UX, and E-Government for Decision Making
Publisher : IndoCompt Publisher

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

Abstract

Indonesia has significant potential in duck farming, particularly as a source of eggs and meat. However, the productivity of local laying ducks remains low due to the traditional feed management practices still widely used. In Secang District, Magelang Regency, farmers often determine feed composition based on availability and peer recommendations without proper consideration of nutritional requirements. This leads to imbalanced nutrition, negatively affecting egg production. This study aims to provide optimal feed composition recommendations using the K-Means Clustering algorithm. The algorithm clusters feed data based on nutritional content and egg production performance. Through this approach, farmers are expected to gain more accurate and efficient information in determining feed composition, thereby improving productivity, reducing operational costs, and enhancing product quality. Furthermore, this research contributes to the development of knowledge in both information technology and animal husbandry by applying machine learning techniques in the agricultural sector.
Co-Authors AGUS PURWANTO Anggraini, Novi Kusuma Anwar, Tulkhah Mubasyir Ardhin Primadewi Auliya Burhanuddin Bambang Pujiarto Dimas Sasongko Emilya Ully Artha Endah Ratna Arumi, Endah Ratna Erlinda, Reza Ena Fatmala, Fungki Fendy Suhariadi Harmadji, Dwi Ekasari Hasani, Rofi Abul Jalaluddin, Alif Maimunah, Maimunah Muhammad Abdul Karim, Muhammad Abdul Muhammad Resa Arif Yudianto Nindhy Prastiwi, Maulidina Nugroho Agung Prabowo NUR ARIFAH Pamungkas, Eko Joko Sambodo Sriadi Pinilih Sebastian, Devara Avila Solikhin Solikhin Sugiarti, Rini Sukmasetya, Pristi Utari, Sudi Yudianto, Resa Arif Yulfikar, Muhammad Yulfikar, Muhammad