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All Journal Bulletin of Electrical Engineering and Informatics Jurnal Teknologi Informasi dan Ilmu Komputer Scientific Journal of Informatics Jurnal Informatika Upgris Politeknosain Journal Of Information system and Computer science
Solikhin Solikhin
Department Of Informatics Engineering, STMIK Himsya, Indonesia
Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering

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Prediction of passenger train using fuzzy time series and percentage change methods Solikhin Solikhin; Septia Lutfi; Purnomo Purnomo; Hardiwinoto Hardiwinoto
Bulletin of Electrical Engineering and Informatics Vol 10, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i6.2822

Abstract

In the subject of railway operation, predicting railway passenger volume has always been a hot topic. Accurately forecasting railway passenger volume is the foundation for railway transportation companies to optimize transit efficiency and revenue. The goal of this research is to use a combination of the fuzzy time series approach based on the rate of change algorithm and the Holt double exponential smoothing method to forecast the number of train passengers. In contrast to prior investigations, we focus primarily on determining the next time period in this research. The fuzzy time series is employed as the forecasting basis, the rate of change is used to build the set of universes, and the Holt's double exponential smoothing method is utilized to forecast the following period in this case study. The number of railway passengers predicted for January 2020 is 38199, with a tiny average forecasting error rate of 0.89 percent and a mean square error of 131325. It can also help rail firms identify future passenger needs, which can be used to decide whether to expand train cars or run new trains, as well as how to distribute tickets.
Aplikasi untuk Mencari Kelayakan Siswa Penerima Bantuan Pendidikan dengan Metode Simple Additive Weighting (Studi Kasus : SMK NU Ma'arif Kudus) Syaifuddin Syaifuddin; Solikhin Solikhin; Eko Riyanto
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 9 No 1: Februari 2022
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021864023

Abstract

Setiap periode SMK NU Ma’arif 2 Kudus melaksanakan program penyaluran bantuan kepada peserta didiknya yang kurang mampu. Dalam memberikan bantuan tersebut perlu dilakukan seleksi bagi para calon penerima. Permasalahan yang dihadapi panitia adalah seleksi dilakukan dengan menunjukpara peserta didik secara langsung dan acak sehingga mengalami kesulitan dalam menentukan siapa yang sebenarnya berhak menerima bantuan. Untuk mengatasi masalah tersebut dan mendapatkan calon yang berhak menerima serta mencapai standar yang diinginkan, maka diperlukan Sistem Seleksi Calon Penerima Bantuan Siswa Miskin (BSM) menggunakan Metode Simple Additive Weighting (SAW) sebagai pendukung keputusan.Metode SAW mencari penjumlahan terbobot berdasar pada kriteria penilaian yang telah ditentukan. Kriteria yang digunakan dalam sistem ini yaitu;jumlah penghasilan orang tua, nilai rata-rata rapor, jumlah kerabat/ saudara. Dari hasil pengujian sistem ini diperoleh luaran berupa perankingan nilai akhir mulai dari yang terbesar hingga terkecil. Hasil analisa perbandingan sistem ini dengan sistem lama terkait tingkat keakuratannya adalah 18 dari 30 siswa (60%) pada sistem lama, sedangkan sistem baru adalah 30 dari 30 siswa (100%). Hasil kuesioner terkait uji kelayakan sistem Seleksi Calon Penerima BSM menggunakan Metode SAWini sangat mudah digunakan (Perceived Ease Of Use) dengan nilai akhir 86,3%, dan sangat bermanfaat (Perceived Of Usefulness) dengan nilai akhir 88,3%.Penerapan sistem ini berkontribusi bagi SMK NU Ma’arif 2 Kudus dalam melaksanakan program penyaluran dana BSM secara optimal, transparan, tepat sasaran, dan berkeadilan serta dapat dijadikan sebagai pendukung keputusan bagi pemangku kepentingan.AbstractEvery period SMK NU Ma’arif 2 Kudus carries out educational aid distribution programs to students who are less fortunate. In providing this assistance, it is necessary to select prospective recipients. The problem faced by the committee is that the selection is carried out by directly and randomly appointing students so that they have difficulty determining who is actually entitled to receive assistance. To overcome this problem and get candidates who are entitled to receive and achieve the desired standards, it is necessary to apply the eligibility selection of students receiving educational assistance using the Simple Additive Weighting (SAW) method as decision support. The SAW method seeks a weighted addition based on predetermined assessment criteria. The criteria used in this system are; the amount of parents' income, the average value of report cards, the number of relatives / relatives. From the test results of this system, the output is in the form of a ranking of the final values ranging from largest to smallest. The results of the comparative analysis of this system with the old system regarding the level of accuracy are 18 out of 30 students (60%) in the old system, while the new system is 30 out of 30 students (100%). The results of the questionnaire related to the feasibility test of the application for selection of students receiving educational assistance using the SAW Method are very easy to use (Perceived Ease Of Use) with a final value of 86.3%, and very useful (Perceived Of Usefulness) with a final value of 88.3%. The contribution to SMK NU Ma’arif 2 Kudus in this study was the making of an application to find out the eligibility of student beneficiaries using the SAW method. This can assist the committee in implementing the education aid fund distribution program in an optimal, transparent, on target and equitable manner and can be used as decision support for stakeholders.
Fuzzy Time Series dan Algoritme Average Based Length untuk Prediksi Pekerja Migran Indonesia Solikhin Solikhin; Uky Yudatama
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 6 No 4: Agustus 2019
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3634.511 KB) | DOI: 10.25126/jtiik.2019641177

Abstract

Perkembangan jumlah Pekerja Migran Indonesia (PMI) program Government to Government (G to G) Jepang bidang perawat (nurse) dan perawat orang berusia lanjut (care worker) mengalami naik turun dari tahun 2008 hingga 2018. Untuk dapat menganalisis jumlah PMI yang mengalami naik turun dengan mengukur perkembangan jumlah PMI saat ini dan memprediksikan kondisi tersebut pada masa mendatang, maka diperlukan model prediksi. Dalam penelitian ini diterapkan model fuzzy time series dengan menggunakan algoritme average-based length. Penentuan panjang interval yang efektif dapat mempengaruhi hasil prediksi yaitu dapat meningkatkan keakuratan yang tinggi dalam fuzzy time series. Hasil proses prediksi PMI program G to G Jepang tahun 2019 bidang nurse diperoleh 43.3, bidang care worker diperoleh 300 dan bidang keseluruhan diperoleh 325. Hasil uji kinerja prediksi PMI program G to G Jepang, menggunakan Mean Absolute Percentage Error (MAPE) adalah 24.27% untuk bidang nurse dengan nilai akurasi prediksi 20–50% termasuk dalam kriteria “wajar”, bidang care worker 11.29% dengan nilai akurasi prediksi 10–20% termasuk dalam kriteria “baik”, sedangkan untuk bidang keseluruhan diperoleh 8.41% dengan nilai akurasi prediksi MAPE <10% termasuk dalam kriteria “sangat baik”. Berdasarkan hasil prediksi tersebut dapat digunakan sebagai pendukung keputusan bagi manajemen dalam membuat kebijakan terkait persiapan, perencanaan, penjadwalan, penempatan, dan perlindungan terhadap para calon PMI pada masa mendatang. Dengan demikian dapat meningkatkan kualitas kinerja sumberdaya manusia dalam memberikan pelayanan terbaik terhadap para calon PMI program G to G Jepang.AbstractThe development of the number of Pekerja Migran Indonesia (PMI) Government to Government programs (G to G) in Japan in the field of nurses  and care workers experienced ups and downs from 2008 to 2018. To be able to analyze the number of PMIs experiencing ups and downs by measuring the development of the current number of PMIs and predicting these conditions in the future, a prediction model is needed. In this study fuzzy time series models are applied using an average-based length algorithm. Determining the length of an effective interval can influence the results of predictions, which can increase high accuracy in fuzzy time series. The results of the PMI program G to G Japan prediction process for 2019 in the nurse field were obtained 43.3, the care worker field was obtained 300 and the overall field was 325. The results of the G to G Japan PMI prediction performance test, using the Mean Absolute Percentage Error (MAPE) were 24.27% for nurse field with predictive accuracy value of 20–50% included in the criteria of "reasonable", the field of care worker 11.29% with a prediction accuracy value of 10-20% included in the criteria "good", while for the overall field obtained 8.41% with MAPE prediction accuracy value < 10% is included in the criteria of "very good". Based on the results of these predictions it can be used as a decision support for management in making policies related to preparation, planning, scheduling, placement, and protection of future PMI candidates. Thus it can improve the quality of the performance of human resources in providing the best service to prospective G-G Japan PMI programs.
APLIKASI PRESENSI DENGAN BARCODE SCANNER DAN RASPBERRY PI TERINTEGRASI BOT TELEGRAM Ana Soraya; Eko Riyanto; - Solikhin
Jurnal Informatika Upgris Vol 6, No 2: Desember (2020)
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v6i2.6567

Abstract

In this research, the presence of students' attendance at the Taruna Bulu Vocational School has been observed where the system used is still manual so it requires a computerized system so that archiving is efficient and the homeroom teacher and student guardian can control student attendance.In conducting research, the author uses two sources of data, namely primary data which includes all data obtained by the author directly from sources obtained from the Head of Vocational School Hair Training and secondary data which includes all information obtained from other data that can be used as a support and related to the research theme. These data sources are documents concerning the student attendance information system procedures. In designing the system, it is made based on the needs of SMK Taruna Bulu which is then implemented using the PHP My SQL programming language and integrated Telegram Bot so that it can later be implemented on Taruna Bulu Vocational School.
A machine learning approach in Python is used to forecast the number of train passengers using a fuzzy time series model Solikhin Solikhin; Septia Lutfi; Purnomo Purnomo; Hardiwinoto Hardiwinoto
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.3518

Abstract

Train passenger forecasting assists in planning, resource use, and system management. forecasts rail ridership. Train passenger predictions help prevent stranded passengers and empty seats. Simulating rail transport requires a low-error model. We developed a fuzzy time series forecasting model. Using historical data was the goal. This concept predicts future railway passengers using Holt's double exponential smoothing (DES) and a fuzzy time series technique based on a rate-of-change algorithm. Holt's DES predicts the next period using a fuzzy time series and the rate of change. This method improves prediction accuracy by using event discretization. positive, since changing dynamics reveal trends and seasonality. It uses event discretization and machine-learning-optimized frequency partitioning. The suggested method is compared to existing train passenger forecasting methods. This study has a low average forecasting error and a mean squared error.
Optimalisasi Layanan RT/RW dengan Memanfaatkan Teknologi Informasi Berbasis IoT Solikhin; Martono
Politeknosains Vol 18 No 2 (2019): Jurnal Politeknosains Volume 18 Nomor 2 - September 2019
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM) Politeknik Pratama Mulia Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (852.902 KB)

Abstract

In the area of Meteseh Village, Tembalang District, there is RW XXIX which is located in the Graha Mulia Asri (GMA) III housing complex which is in charge of 5 (five) RT. Neighborhood RW XXIX The GMA III housing estate is classified as new, the area is quite large and has a relatively dense population. The current condition is the problem that is often faced by RT and RW heads in carrying out their main duties and functions (tupoksi), namely in serving their citizens related to various administrative requirements less than optimal, due to one side being unable to leave their rights in carrying out their activities as individuals and heads families so that services to their citizens cannot be ontime but only at certain times, conditions like this clearly have an impact on impeded smoothness in carrying out the tasks of the village or village government in development and society. In addition, in providing important information / news to its citizens, it is also waiting for routine community meeting every month. In an effort to carry out its duties, functions and to organize its environment, RT V RW XXIX housing GMA III needs to make changes and breakthroughs. One of them is the need for support in the use of information technology to help, manage and manage their tasks in order to improve services to the community. In this study he made an IoT-based RT Management Information System to optimize its services.
Perancangan Aplikasi E-KIRT Berbasis Android untuk Meningkatkan Pemasaran dan Penjualan bagi Kelompok Industri Rumah Tangga Solikhin
Politeknosains Vol 15 No 2 (2016): Jurnal Politeknosains Volume 15 Nomor 2 - September 2016
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM) Politeknik Pratama Mulia Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (579.24 KB)

Abstract

This study will produce a system of text-based information security applications using cryptography algorithms Hill Code and Steganography LSB (Least Significant Bit). System information security applications are built to be used for text-based data security. The algorithms used for cryptography is Hill Code with a matrix of 2 x 2sebagai encryption keys, whereas the description used for the inverse of a matrix initial key. Steganography algorithm used is the LSB (Least Significant Bit) insertion in every bit of content (confidential data) into a low bit or bits of the far right. As known to a bitmap (.bmp) 24 bits consist of three pixels in which each pixel is a collection of 8 bits or 1 byte (a value between 0 to 255atau in binary format between 00000000 to 11111111), who presented the value of the intensity of the light that forms the base color namely red, green or blue (red-green-Blue or RGB). Thus in each pixel can be inserted 3 content. The results of the implementation and testing of the system shows that the system is running well, the implementation of the algorithm results are consistent with the manual calculation.
Prediksi Produksi Biofarmaka Menggunakan Model Fuzzy Time Series dengan Pendekatan Percentage Change dan Frequency Based Partition Dwi Ekasari Harmadji; Solikhin Solikhin; Uky Yudatama; Agus Purwanto
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.20231016267

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.
Membangun Sistem Smart Trash Menggunakan Mikrokontroler Motor Servo Panjerino Yuda Hirmawan; Eko Riyanto; Solikhin Solikhin
Jurnal Informatika Upgris Vol 9, No 1: Juni 2023
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v9i1.15444

Abstract

To cultivate good behavior and care for the environment, SD Negeri 2 KuwasenJepara promotes proper waste disposal, but in reality, there are still many students who don't do it. The purpose of this research is to build a smart trash can to socialize waste disposal in an attractive way for students. We use a manual trash can that is integrated with the Arduino Uno. This smart trash system is able to open automatically when it detects movement within <50 cm and vice versa, and can emit a "Thank you for not littering" sound. The performance test results show that the ultrasonic sensor device opens and closes within 3.07 seconds at a distance of 15 centimeters and 3.06 seconds at a distance of 30 centimeters. The feasibility test of the tool obtained a score of ≥76% and an ease of use score of 87.7%.
SMART HYDROPONIC BERBASIS ANDROID DI SMKN 6 KENDAL Muhammad Aji Saputra; Eko Riyanto; Solikhin
Journal of Information System and Computer Vol. 2 No. 1 (2022): Juli 2022
Publisher : Universitas Islam Nahdlatul Ulama Jepara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34001/jister.v2i1.266

Abstract

The rapid development of technology makes people innovate to make new things and leave old ways to simplify and save time a job. One example is monitoring the value of pH, PPM, room temperature and humidity as well as water temperature of hydroponic plants that used to still use conventional tools, now switching to Android-based IoT technology (Smart Hydroponics), especially at SMKN 6 Kendal. IoT is a way of connecting the Arduino sensor modules needed for hydroponic cultivation, where the results of sensor readings will be actually sent to the user's Android smartphone. The Arduino sensors are pH, TDS, DHT 11, ds1820 sensors. With this smart hydroponics, it is hoped that it can help hydroponic cultivators in the SMKN 6 Kendal environment to monitor their gardens anywhere and anytime and control the hydroponic temperature to be maintained below 30 degrees. From the reading of the value of the smart hydroponic sensor, it works well with existing standards and through MAPE calculations with a value below 10%.
Co-Authors Agus Purwanto Ana Soraya Devi Astri Nawangnugraeni Eko Riyanto Eko Riyanto Eko Riyanto Hardiwinoto Hardiwinoto Hardiwinoto Hardiwinoto Harmadji, Dwi Ekasari M. Zakki Abdillah Martono Muhammad Aji Saputra Purnomo . Purnomo Purnomo Septia Lutfi Syaifuddin Syaifuddin Toni Wijanarko Adi Putra Uky Yudatama Yuda Hirmawan