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LOW-COST RASPBERRY-BASED MOBILE PAYMENT SYSTEM FOR CASHLESS TRANSACTION IN GASOLINE STATION Wijanarko, Rahmat Septian; Susanty, Meredita
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 10, No 2 (2019): JURNAL SIMETRIS VOLUME 10 NO 2 TAHUN 2019
Publisher : Universitas Muria Kudus

To embrace the cashless future, PT PERTAMINA collaborate with various banks and LinkAja!, one of e-finance services in Indonesia, to accept cashless payment using QR code technology using mobile application. The cashless payment now accepted in both conventional gas station and self-service gas station. However, at a self-service gas station, customers generally make payments before refueling to an operator located in the control post (before the dispenser area/refueling area). It requires the customer to return to the operator in order to request the change when they stop refueling before reaching the requested volume. This research proposes some modifications toward the fuel dispenser so that the dispenser is able to accept cashless payment, provide correct amount of fuel, and guarantee payment for each transaction even when there are no operators around. The implementation of this prototype improves service at gas station by reducing queue time about three to seven second per vehicle, improve company efficiency by reducing the number of operators in gas station from one operator per dispenser to one operator per station, also, it removes the balancing process performed by the operator at the end of the shift. Sales reports are generated automatically in near real-time.

ESTABLISHING REQUIREMENT IN TEACHING NEW AND RENEWABLE ENERGY Susanty, Meredita; Yunita, Ariana; Setiawan, Erwin
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 10, No 2 (2019): JURNAL SIMETRIS VOLUME 10 NO 2 TAHUN 2019
Publisher : Universitas Muria Kudus

The distinctive shortage in the availability of skilled labor in new and renewable energy sector becomes the issue that has been prevented this country in achieving the national energy mix in 2015 and 2050. Although both formal and non-formal education initiatives already exist to foster new and renewable energy education, the number of graduates cannot outpace the number of required labor. The number of graduates and their competencies must be considered because local labors are facing intense competition with foreign labors due to ASEAN Economic Community policy. This research aims to find a solution to address the educational issue in new and renewable energy education. This research is using iterative methodology from the software engineering domain to identify issues and problems in new and renewable energy education in Indonesia and suggested alternatives to address it. Combination of techniques (questionnaire, interview, studying documentation, and research a similar product) is used in requirement elicitation stage in order to provide multiple perspectives.

Identifikasi Batuan Berdasarkan Data Well Log Menggunakan K-Means Clustering Susanty, Meredita; Ebelaristra, Prinsislamsheeny Brilliantdianty; Rahman, Ahmad Fauzan; Irawan, Ade; Madrinovella, Ikri; Astuti, Weny
Jurnal Migasian Vol. 4 No. 1 (2020): Jurnal Migasian
Publisher : LPPM Akademi Minyak dan Gas Balongan Indramayu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36601/jurnal-migasian.v4i1.96

One of the stages in oil and gas exploration is a Petrophysical analysis, which aims to determine the structure of rock layers below the earth's surface. The petrophysical analysis uses physical properties in a well-log to determine the rock type below the surface. Nowadays, the software for conducting petrophysical analysis has utilized a machine-learning approach to predict rock types. Most of the software uses the supervised learning method to classify rock types. This research uses a different approach, unsupervised learning, to group rock types based on various features in a well-log. Using a publicly available well-log in Stafford, United States, and the k-means clustering algorithm, this study groups the data into 3 clusters. The result is compared with manual analysis interpretation and shows an alignment between them. From the result, it shows that the unsupervised learning method effectively predicts limestone, shale, and evaporites in the well. It classifies the dataset into useful clusters, generates useful lithologies, provides useful rock characterization, and less time-consuming.

Pore Pressure Prediction Using Artificial Neural Network Based On Logging Data WARDANA, RAKA SUDIRA; Susanty, Meredita; B.W, Hapsoro
Jurnal Migasian Vol. 4 No. 1 (2020): Jurnal Migasian
Publisher : LPPM Akademi Minyak dan Gas Balongan Indramayu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36601/jurnal-migasian.v4i1.97

Pore pressure is a critical parameter in designing drilling operations. Inaccurate pore pressure data can cause problems, even incidents in drilling operations. Pore pressure data can be obtained from direct measurement methods or estimated using indirect measurement methods such as empirical models. In the oil and gas industry, most of the time, direct measurement is only taken in certain depth due to relatively high costs. Hence, empirical models are commonly used to fill in the gap. However, most of the empirical models highly depend on specific basins or types of formation. Furthermore, to predict pore pressure using empirical models accurately requires a good understanding in determining Normal Compaction Trendline. This proposed approach aims to find a more straightforward yet accurate method to predict pore pressure. Using Artificial Neural Network Model as an alternative method for pore pressure prediction based on logging data such as gamma-ray, density, and sonic log, the result shows a promising accuracy.

Perbandingan Penggunaan Panel Surya dan Turbin Angin dalam Implementasi Energi Baru Terbarukan (EBT) di Lingkungan Universitas Pertamina Fadillah, Riestiya Zain; Mahendra, Adhytia Ihza; Pangestu, Muhamad Benando; Afriansyah, Afriansyah; Rahman, Ahmad Fauzan; Muhasabah, Alzahid; Susanty, Meredita; Setiawan, Erwin
Jurnal Teknologi Lingkungan Vol. 22 No. 1 (2021)
Publisher : Center for Environmental Technology - Agency for Assessment and Application of Technology

ABSTRACT Health risk characteristics expressed as a Risk Quotient (RQ) can be carried out through an environmental health risk analysis (ARKL) approach. This approach can estimate the public health risk caused by the concentration of risk agents of particulates consisting of PM2.5, PM10, and TSP. The research on the fluctuation of ambient air particulate pollutant and its risk to public health was conducted in each sub-district of Bogor City. Author identified a total of 360 respondents to determine the community anthropometric variable of exposures for time, frequency, and duration. There are several steps that need to be carried out to obtain the RQ value, namely identification of hazards from particulate risk agents, analysis of the dose-response in the form of Reference Concentration (RFC), analysis of the exposure obtained based on anthropometric variables, and the concentration of risk agents as well as characteristics of risk levels. The risk level characteristic shows that the RQ value of TSP is always the highest one, followed by PM10 and PM2.5. The respective RQ values of TSP for male and female residents are 1.85 and 1.53. Cumulatively, the male and female population in Tanah Sareal produced the highest RQ values. Those are 4.44 and 3.36, respectively. At the same time, the lowest cumulative RQ was obtained for male and female residents in East Bogor with RQ values of 2.96 and 2.54. The RQ value of each risk agent or the cumulative RQ that is more than 1 (RQ> 1) is stated to have or has a health risk, so it needs to be controlled, while the RQ value which is less than one (1) is displayed not to need to be controlled but needs to be maintained. Keywords: particulate, risk level, exposure assessment, anthropometric characteristic, environmental health risk assessment Â ABSTRAK Karakteristik risiko kesehatan yang dinyatakan sebagai Risk Quotient (RQ) dapat dilakukan melalui pendekatan Analisis Risiko Kesehatan Lingkungan (ARKL). Pendekatan ini dapat mengestimasi risiko kesehatan masyarakat yang disebabkan oleh konsentrasi agen risiko yaitu PM2,5, PM10, dan TSP di tiap-tiap kecamatan di Kota Bogor. Penulis mengidentifikasi sebanyak 360 responden yang terdiri dari laki-laki dan perempuan untuk menentukan variabel antropometri masyarakat di Kota Bogor, waktu paparan, frekuensi paparan, serta durasi paparan. Ada beberapa tahapan yang perlu dilakukan untuk memperoleh nilai RQ, yaitu identifikasi bahaya dari agen risiko partikulat, analisis dosis-respon berupa Reference Concentration (RfC), analisis pajanan yang diperoleh berdasarkan variabel antropometri dan konsentrasi agen risiko serta karakteristik tingkat risiko. Karakteristik tingkat risiko menunjukkan nilai RQ TSP selalu paling tinggi diikuti PM10, dan terendah adalah RQ PM2,5 dengan nilai tertinggi TSP untuk penduduk laki-laki dan perempuan masing-masing sebesar 1,85 dan 1,53. Secara kumulatif, penduduk laki-laki dan perempuan di Tanah Sareal menghasilkan nilai RQ tertinggi masing-masing sebesar 4,44 dan 3,36. Sedangkan RQ kumulatif terendah diperoleh untuk penduduk laki-laki dan perempuan di Bogor Timur dengan nilai RQ 2,96 dan 2,54. Nilai RQ tiap agen risiko ataupun RQ kumulatif yang lebih dari 1 (RQ>1) dinyatakan memiliki atau terdapat risiko kesehatan sehingga perlu dikendalikan, sementara nilai RQ yang masing kurang dari satu dinyatakan tidak perlu dikendalikan tetapi perlu dipertahankan. Kata kunci: partikulat, tingkat risiko, analisis pajanan, karakteristik antropometri, analisis risiko kesehatan lingkungan

Perbandingan Penggunaan Panel Surya dan Turbin Angin dalam Implementasi Energi Baru Terbarukan (EBT) di Lingkungan Universitas Pertamina Fadillah, Riestiya Zain; Mahendra, Adhytia Ihza; Pangestu, Muhamad Benando; Afriansyah, Afriansyah; Rahman, Ahmad Fauzan; Muhasabah, Alzahid; Susanty, Meredita; Setiawan, Erwin
Jurnal Teknologi Lingkungan Vol. 22 No. 1 (2021)
Publisher : Center for Environmental Technology - Agency for Assessment and Application of Technology

ABSTRACT Health risk characteristics expressed as a Risk Quotient (RQ) can be carried out through an environmental health risk analysis (ARKL) approach. This approach can estimate the public health risk caused by the concentration of risk agents of particulates consisting of PM2.5, PM10, and TSP. The research on the fluctuation of ambient air particulate pollutant and its risk to public health was conducted in each sub-district of Bogor City. Author identified a total of 360 respondents to determine the community anthropometric variable of exposures for time, frequency, and duration. There are several steps that need to be carried out to obtain the RQ value, namely identification of hazards from particulate risk agents, analysis of the dose-response in the form of Reference Concentration (RFC), analysis of the exposure obtained based on anthropometric variables, and the concentration of risk agents as well as characteristics of risk levels. The risk level characteristic shows that the RQ value of TSP is always the highest one, followed by PM10 and PM2.5. The respective RQ values of TSP for male and female residents are 1.85 and 1.53. Cumulatively, the male and female population in Tanah Sareal produced the highest RQ values. Those are 4.44 and 3.36, respectively. At the same time, the lowest cumulative RQ was obtained for male and female residents in East Bogor with RQ values of 2.96 and 2.54. The RQ value of each risk agent or the cumulative RQ that is more than 1 (RQ> 1) is stated to have or has a health risk, so it needs to be controlled, while the RQ value which is less than one (1) is displayed not to need to be controlled but needs to be maintained. Keywords: particulate, risk level, exposure assessment, anthropometric characteristic, environmental health risk assessment Â ABSTRAK Karakteristik risiko kesehatan yang dinyatakan sebagai Risk Quotient (RQ) dapat dilakukan melalui pendekatan Analisis Risiko Kesehatan Lingkungan (ARKL). Pendekatan ini dapat mengestimasi risiko kesehatan masyarakat yang disebabkan oleh konsentrasi agen risiko yaitu PM2,5, PM10, dan TSP di tiap-tiap kecamatan di Kota Bogor. Penulis mengidentifikasi sebanyak 360 responden yang terdiri dari laki-laki dan perempuan untuk menentukan variabel antropometri masyarakat di Kota Bogor, waktu paparan, frekuensi paparan, serta durasi paparan. Ada beberapa tahapan yang perlu dilakukan untuk memperoleh nilai RQ, yaitu identifikasi bahaya dari agen risiko partikulat, analisis dosis-respon berupa Reference Concentration (RfC), analisis pajanan yang diperoleh berdasarkan variabel antropometri dan konsentrasi agen risiko serta karakteristik tingkat risiko. Karakteristik tingkat risiko menunjukkan nilai RQ TSP selalu paling tinggi diikuti PM10, dan terendah adalah RQ PM2,5 dengan nilai tertinggi TSP untuk penduduk laki-laki dan perempuan masing-masing sebesar 1,85 dan 1,53. Secara kumulatif, penduduk laki-laki dan perempuan di Tanah Sareal menghasilkan nilai RQ tertinggi masing-masing sebesar 4,44 dan 3,36. Sedangkan RQ kumulatif terendah diperoleh untuk penduduk laki-laki dan perempuan di Bogor Timur dengan nilai RQ 2,96 dan 2,54. Nilai RQ tiap agen risiko ataupun RQ kumulatif yang lebih dari 1 (RQ>1) dinyatakan memiliki atau terdapat risiko kesehatan sehingga perlu dikendalikan, sementara nilai RQ yang masing kurang dari satu dinyatakan tidak perlu dikendalikan tetapi perlu dipertahankan. Kata kunci: partikulat, tingkat risiko, analisis pajanan, karakteristik antropometri, analisis risiko kesehatan lingkungan

Data Augmentasi Untuk Mengatasi Keterbatasan Data Pada Model Penerjemah Bahasa Isyarat Indonesia (BISINDO) Fadillah, Riestiya Zain; Irawan, Ade; Susanty, Meredita
Jurnal Informatika Vol 8, No 2 (2021): September 2021
Publisher : LPPM Universitas Bina Sarana Informatika

Ada dua sistem bahasa isyarat yang digunakan di Indonesia; Sistem Isyarat Bahasa Indonesia (SIBI) dan Bahasa Isyarat Indonesia (Bisindo). Penggunaan bahasa isyarat di kelompok masyarakat tuli dan difabel rungu di Indonesia masih terpecah. Pemerintah mewajibkan penggunaan SIBI sebagai bahasa pengantar resmi di Sekolah Luar Biasa namun insan rungu Indonesia lebih gemar menggunakan Â Bisindo. Hal ini dikarenakan Bisindo memiliki akar kata yang berasal dari Bahasa Indonesia dan satu gerakan mewakili kata. Tidak seperti SIBI yang menggunakan gerakan isyarat berdasarkan tata bahasa orang mendengar. Gerakan untuk Kesejahteraan Tunarungu Indonesia (Gerkatin) telah meminta pemerintah untuk mengakui Bisindo sebagai bahasa pengantar resmi di Sekolah Luar Biasa namun upaya ini hingga kini belum berhasil. Upaya lain yang dilakukan Gerkatin adalah memberikan kelas pelatihan Bisindo bagi masyarakat umum membantu meningkatkan aksesibilitas Tuli dengan menambah jumlah penerjemah serta memperluas pemahaman Bisindo di masyarakat luas. Penelitian ini mencoba mendukung upaya tersebut dengan mengembangkan model penerjemah Bisindo yang menerjemahkan gestur bahasa isyarat menjadi teks menggunakan pendekatan machine learning dengan arsitektur Convolutional Neural Network (CNN). Keterbatasan dataset Bisindo diatasi dengan melakukan data augmentation. Performa model mencapai nilai akurasi sebesar 94.38%.

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